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Reconstructing suspended sediment concentrations in the Mekong River Basin via semi-supervised-based deep neural networks

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science of the Total Environment 2024年 955卷 176758页

作者： Nguyen, Thi Thu Ha Vu, Duc Quang Doan, Ngoc Phu Chi, Huynh Thi Khanh Li, Peixin Binh, Doan Van An, Yimeng Dung, Pham Tuan Hoang, Tuan A. Son, Mai Thai Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City Viet Nam Department of Computer Science and Information System Thai Nguyen University of Education Viet Nam School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom College of Economics and Management Nanjing University of Aeronautics and Astronautics China Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat City Viet Nam

The Mekong River Basin (MRB) is crucial for the livelihoods of over 60 million people across six Southeast Asian countries. Understanding long-term sediment changes is crucial for management and contingency plans, but the sediment concentration data in the MRB are extremely sporadic, making analysis challenging. This study focuses on reconstructing long-term suspended sediment concentration (SSC) data using a novel semi-supervised machine learning (ML) model. The key idea of this approach is to exploit abundant available hydroclimate data to reduce training overfitting rather than solely relying on sediment concentration data, thus enhancing the accuracy of the employed ML models. Extensive experiments on daily hydroclimate and SSC data obtained from 1979 to 2019 at the three main stations (i.e., Chiang Saen, Nong Khai, and Mukdahan) are conducted to demonstrate the superior performance of the proposed method compared to the state-of-the-art supervised techniques (i.e., Random Forest, XGBoost, CatBoost, MLP, CNN, and LSTM), and surpasses existing semi-supervised methods (i.e., CoReg, ⊓ Model, ICT, and Mean Teacher). This approach is the first semi-supervised method to reconstruct sediment data in the field and has the potential for broader application in other river systems. © 2024 The Author(s)

关键词： Self-supervised learning

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Phase transition in magic with random quantum circuits

arXiv

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arXiv 2023年

作者： Niroula, Pradeep White, Christopher David Wang, Qingfeng Johri, Sonika Zhu, Daiwei Monroe, Christopher Noel, Crystal Gullans, Michael J. Joint Center for Quantum Information and Computer Science University of Maryland and NIST College ParkMD20742 United States Joint Quantum Institute University of Maryland and NIST College ParkMD20742 United States Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States IonQ Inc. College ParkMD20740 United States Duke Quantum Center Department of Electrical & Computer Engineering Department of Physics Duke University DurhamNC27701 United States

Magic is a property of quantum states that enables universal fault-tolerant quantum computing using simple sets of gate operations. Understanding the mechanisms by which magic is created or destroyed is, therefore, a crucial step towards efficient and practical fault-tolerant computation. We observe that a random stabilizer code subject to coherent errors exhibits a phase transition in magic, which we characterize through analytic, numeric and experimental probes. Below a critical error rate, stabilizer syndrome measurements remove the accumulated magic in the circuit, effectively protecting against coherent errors;above the critical error rate syndrome measurements concentrate magic. A better understanding of such rich behavior in the resource theory of magic could shed more light on origins of quantum speedup and pave pathways for more efficient magic state generation. © 2023, CC BY.

关键词： Random errors

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Giant Thermomechanical Bandgap engineering in Quasi-two-dimensional Tellurium

arXiv

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arXiv 2023年

作者： Hussain, Naveed Ahmed, Shehzad Tep, Hüseyin U. Ullah, Kaleem Shahzad, Khurram Wu, Hui Shcherbakov, Maxim R. Department of Electrical Engineering and Computer Science University of California Irvine IrvineCA92697 United States State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing100084 China College of Physics and Optoelectronic Engineering Shenzhen University Guangdong518060 China Micro and Nano-Technology Program School of Natural and Applied Sciences Middle East Technical University Ankara06800 Turkey Department of Electrical and Computer Engineering University of Delaware NewarkDE19711 United States Department of Physics Middle East Technical University Ankara06800 Turkey

Mechanical straining-induced bandgap modulation in two-dimensional (2D) materials has been confined to volatile and narrow modulation due to substrate slippage and poor strain transfer. We report the thermomechanical modulation of the inherent bandgap in quasi-2D tellurium nanoflakes (TeNFs) via non-volatile strain induction during hot-press synthesis. We leveraged the coefficient of thermal expansion (CTE) mismatch between TeNFs and growth substrates by maintaining a high-pressure enforced non-slip condition during thermal relaxation (623 to 300K) to achieve the optimal biaxial compressive strain of -4.6 percent in TeNFs/sapphire. This resulted in an enormous bandgap modulation of 2.3 eV, at a rate of up to ~600 meV/%, which is two-fold larger than reported modulation rate. Strained TeNFs display robust band-to-band radiative excitonic blue photoemission with an intrinsic quantum efficiency (IQE) of c.a. 79.9%, making it promising for energy efficient blue LEDs and nanolasers. Computational studies reveal that biaxial compressive strain inhibits exciton-exciton annihilation by evading van-Hove singularities, hence promoting radiative-recombination. Bandgap modulation by such nonvolatile straining is scalable to other 2D semiconductors for on-demand nano(opto)-electronics. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy gap

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OPRLM: A Web Tool and a Database for Positioning and Simulations of Proteins in Realistic Lipid Membranes

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Journal of Molecular Biology 2025年第15期437卷 168966页

作者： Park, Sang-Jun Schnitzer, Kyle A. Kovalenko, Alexey Cherepanov, Stanislav Patro, L. Ponoop Prasad Song, Zigang Pogozheva, Irina D. Lomize, Andrei L. Im, Wonpil Department of Computer Science and Engineering Lehigh University 111 Research Drive Bethlehem 18015 PA United States Department of Electrical Engineering and Computer Science College of Engineering University of Michigan 1221 Beal Ave Ann Arbor 48109-2102 MI United States Department of Computer Science College of Literature Science and the Arts University of Michigan 2260 Hayward Street Ann Arbor 48109-2121 MI United States Biophysics Program University of Michigan 930 N. University Avenue Ann Arbor 48109-1065 MI United States Department of Biological Sciences Lehigh University 111 Research Drive Bethlehem 18015 PA United States Department of Medicinal Chemistry College of Pharmacy University of Michigan 428 Church St. Ann Arbor 48109-1065 MI United States

Molecular dynamics (MD) simulations in explicit lipid bilayers enable modeling of protein-lipid interactions essential for membrane protein functions and regulation. The newly developed computational web tool, OPRLM (Orientations of Proteins in Realistic Lipid Membranes), automates the assembly of membrane protein structures with explicit lipids corresponding to 18 biological membrane types with symmetric or asymmetric lipid distributions, as well as 5 types of two-component lipid bilayers with varying cholesterol content. Built upon the CHARMM-GUI toolset and the PPM method, OPRLM simplifies the setup of complex simulation system involving integral and/or peripheral membrane proteins with explicit lipid mixtures and generates all necessary files for subsequent all-atom MD simulations. OPRLM has successfully generated protein-membrane systems for 286 tested protein structures in various biomembranes, including 138 structures containing ligands. The OPRLM database, an advanced successor of the OPM database, includes explicit protein-lipid systems for tested proteins in their native biomembranes. It provides coordinates of integral and peripheral membrane proteins from the Protein Data Bank embedded in planar or curved implicit lipid bilayers. Additionally, it includes the classification of proteins into types, superfamilies, and families, along with the information on intracellular localizations and membrane topology and visualization options. The OPRLM web tool and the database are publicly accessible at https://***. © 2025 The Authors

关键词： biomembrane explicit lipid lipid bilayer peripheral membrane protein transmembrane

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Implantable Biosensor for Continuous Serotonin Detection in Freely Moving Crayfish

Implantable Biosensor for Continuous Serotonin Detection in ...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Jinjing Han Tawen Ho Justin M. Stine Michael A. Straker Jens Herberholz Reza Ghodssi Department of Electrical and Computer Engineering University of Maryland College Park MD USA Institute for System Research University of Maryland College Park MD USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park MD USA Department of Psychology University of Maryland College Park MD USA Program in Neuroscience and Cognitive Science University of Maryland College Park MD USA Fischell Department of Bioengineering University of Maryland College Park MD USA

This work presents, for the first time, an implantable biosensor for continuous in vivo serotonin (5-HT) monitoring in freely moving crayfish. 5-HT is an important neurotransmitter that regulates animal behaviors. Conventional methods for detecting 5-HT do not provide real-time information. Our approach facilitates continuous electrochemical monitoring of 5-HT levels without impeding animal natural behavior. The sensing system shows a linear range of 0.4 - 1.2 μΜ with a sensitivity of 0.07 μΑ/μΜ for 5-HT detection. With a 3D-printed package, the sensor can be easily attached to crayfish dorsal carapace allowing electrodes implantation into crayfish heart to monitor neurohormonal dynamics of 5-HT. The implantable biosensor system displayed a significant increase in oxidation currents after 5-HT injections. The device successfully demonstrates the application for in vivo detection of 5-HT in the hemolymph (i.e., blood) of freely behaving crayfish underwater.

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Optimizing System-on-Chip Performance Using AI and SDN: Approaches and Challenges

Optimizing System-on-Chip Performance Using AI and SDN: Appr...

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International Conference on Software Defined Systems (SDS)

作者： Mohammad Alja'afreh Muath Obaidat Ali Karime Sahel Alouneh Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) UAE Computer Science- City University of New York USA Department of Electrical and Computer Engineering The Royal Military College of Canada Canada Cybersecurity Program Al Ain University UAE and German Jordanian University Jordan

The advancement of modern multimedia and data-intensive classes of applications demands the development of hardware that delivers better performance. Due to the evolution of 5G, Edge-Computing, the Internet of Things, Software-Defined networks, etc., the data produced by the devices such as sensors are increasing. A software-Defined network is a powerful paradigm that is capable of automating networking and cloud computing. Software-Defined Network has controllers, devices, and applications which produce a huge amount of data. The processing of data inside the device as well as between the devices needs a better hardware architecture with more cores to ensure speedy performance. The System-on-Chip approach alone will not be capable to handle this dense core comprised of hardware. We have to blend Network-on-Chip along with System-on-Chip to increase the potential to include more cores capable to handle more threads. Artificial Intelligence, a key enabler in next-generation devices is capable of producing a better architecture design with optimized performance. In this paper, we are discussing and endeavouring how System-on-Chip, Network-on-Chip, Software-Defined Networks, and Artificial Intelligence can be physically, logically, and contextually incorporated to deliver improved computation and networking outcomes.

关键词： Performance evaluation computer architecture Network-on-chip Solids Hardware Software Artificial intelligence

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Ramsey envelope modulation in NV diamond magnetometry

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Physical Review B 2022年第5期106卷 054110-054110页

作者： Jner Tzern Oon Jiashen Tang Connor A. Hart Kevin S. Olsson Matthew J. Turner Jennifer M. Schloss Ronald L. Walsworth Department of Physics University of Maryland College Park Maryland 20742 USA Quantum Technology Center University of Maryland College Park Maryland 20742 USA Department of Electrical Engineering and Computer Science University of Maryland College Park Maryland 20742 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Lincoln Laboratory Massachusetts Institute of Technology Lexington Massachusetts 02421 USA

Nitrogen-vacancy (NV) spin ensembles in diamond provide an advanced magnetic sensing platform, with applications in both the physical and life sciences. The development of isotopically engineered NV15 diamond offers advantages over naturally occurring NV14 for magnetometry, due to its simpler hyperfine structure. However, for sensing modalities requiring a bias magnetic field not aligned with the sensing NV axis, the absence of a quadrupole moment in the N15 nuclear spin leads to pronounced envelope modulation effects in time-dependent measurements of NV15 spin evolution. While such behavior in spin echo experiments are well studied, analogous effects in Ramsey measurements and the implications for magnetometry remain underexplored. Here, we derive the modulated NV15 Ramsey response to a misaligned bias field, using a simple vector description of the effective magnetic field on the nuclear spin. The predicted modulation properties are then compared to experimental results, revealing significant magnetic sensitivity loss if unaddressed. We demonstrate that double-quantum coherences of the NV S=1 electronic spin states dramatically suppress these envelope modulations, while additionally proving resilient to other parasitic effects such as strain heterogeneity and temperature shifts.

关键词： NV centers Quantum metrology Quantum sensing Nitrogen vacancy centers in diamond Magnetization measurements Numerical approximation & analysis Perturbation theory

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Mechanically reprogrammable Pancharatnam-Berry metasurface for microwaves

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Advanced Photonics 2022年第1期4卷 69-79页

作者： Quan Xu Xiaoqiang Su Xueqian Zhang Lijuan Dong Lifeng Liu Yunlong Shi Qiu Wang Ming Kang Andrea Alù Shuang Zhang Jiaguang Han Weili Zhang Tianjin University Center for Terahertz Waves and College of Precision Instrument and Optoelectronics EngineeringKey Laboratory of Optoelectronic Information Technology(Ministry of Education of China)TianjinChina Shanxi Datong University Institute of Solid State Physics and College of Physics and Electronic ScienceShanxi Province Key Laboratory of Microstructure Electromagnetic Functional MaterialsDatongChina Wuhan University of Technology School of Information EngineeringWuhanChina Tianjin Normal University College of Physics and Materials ScienceTianjinChina City University of New York Advanced Science Research CenterPhotonics InitiativeNew YorkUnited States City University of New York Graduate CenterPhysics ProgramNew YorkUnited States University of Hong Kong Faculty of ScienceDepartment of PhysicsHong KongChina University of Hong Kong Department of Electrical and Electronic EngineeringHong KongChina Guilin University of Electronic Technology Guangxi Key Laboratory of Optoelectronic Information ProcessingSchool of Optoelectronic EngineeringGuilinChina Oklahoma State University School of Electrical and Computer EngineeringStillwaterOklahomaUnited States

Metasurfaces have enabled the realization of several optical functionalities over an ultrathin platform,fostering the exciting field of flat *** metasurfaces are achieved by arranging a layout of static meta-atoms to imprint a desired operation on the impinging wavefront,but their functionality cannot be *** and programmability of metasurfaces are the next important step to broaden their impact,adding customized on-demand functionality in which each meta-atom can be individually *** demonstrate a mechanical metasurface platform with controllable rotation at the meta-atom level,which can implement continuous Pancharatnam–Berry phase control of circularly polarized *** the proof-of-concept experiments,we demonstrate metalensing,focused vortex beam generation,and holographic imaging in the same metasurface template,exhibiting versatility and superior *** dynamic control of electromagnetic waves using a single,low-cost metasurface paves an avenue towards practical applications,driving the field of reprogrammable intelligent metasurfaces for a variety of applications.

关键词： reprogrammable metasurfaces Pancharatnam-Berry phase mechanical metasurfaces microwaves

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Electrochemical measurement of serotonin by Au-CNT electrodes fabricated on microporous cell culture membranes

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Microsystems & Nanoengineering 2020年第1期6卷 494-506页

作者： Ashley A.Chapin Pradeep R.Rajasekaran David N.Quan Liangbing Hu Jens Herberholz William E.Bentley Reza Ghodssi Fischell Department of Bioengineering College ParkMD 20742USA Institute for Systems Research College ParkMD 20740USA Department of Materials Science and Engineering College ParkMD 20740USA Department of Psychology and Neuroscience and Cognitive Science Program College ParkMD 20740USA Institute for Bioscience and Biotechnology Research RockvilleMD 20850USA Robert E.Fischell Institute for Biomedical Devices RockvilleMD 20850USA Department of Electrical and Computer Engineering College ParkMD 20742USA

Gut–brain axis(GBA)communication relies on serotonin(5-HT)signaling between the gut epithelium and the peripheral nervous system,where 5-HT release patterns from the basolateral(i.e.,bottom)side of the epithelium activate nerve *** have been few quantitative studies of this gut-neuron signaling due to a lack of real-time measurement tools that can access the basolateral gut *** vitro platforms allow quantitative studies of cultured gut tissue,but they mainly employ offline and endpoint assays that cannot resolve dynamic molecular-release ***,we present the modification of a microporous cell culture membrane with carbon nanotube-coated gold(Au-CNT)electrodes capable of continuous,label-free,and direct detection of 5-HT at physiological *** characterization of single-walled carbon nanotube(SWCNT)-coated Au electrodes shows increased electroactive surface area,5-HT specificity,sensitivity,and saturation time,which are correlated with the CNT film drop-cast *** microliters of CNT films,with a 10-min saturation time,0.6μA/μM 5-HT sensitivity,and reliable detection within a linear range of 500 nM–10μM 5-HT,can be targeted for high-concentration,high-time-resolution 5-HT *** films(12.5μL)with a 2-h saturation time,4.5μA/μM 5-HT sensitivity,and quantitative detection in the linear range of 100 nM–1μM can target low concentrations with low time *** electrodes achieved continuous detection of dynamic diffusion across the porous membrane,mimicking basolateral 5-HT release from cells,and detection of cell-released 5-HT from separately cultured RIN14B cell ***-integrated cell culture systems such as this can improve in vitro molecular detection mechanisms and aid in quantitative GBA signaling studies.

关键词： release saturation dynamic

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Heterogeneous Oblique Double Random Forest

arXiv

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arXiv 2023年

作者： Ganaie, M.A. Tanveer, M. Beheshti, I. Ahmad, N. Suganthan, P.N. Department of Robotics University of Michigan Ann ArborMI United States Department of Mathematics Indian Institute of Technology Indore Simrol Indore453552 India Department of Human Anatomy and Cell Science Rady Faculty of Health Sciences Max Rady College of Medicine University of Manitoba WinnipegMB Canada Department of International Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan KINDI Center for Computing Research College of Engineering Qatar University Doha Qatar

The decision tree ensembles use a single data feature at each node for splitting the data. However, splitting in this manner may fail to capture the geometric properties of the data. Thus, oblique decision trees generate the oblique hyperplane for splitting the data at each non-leaf node. Oblique decision trees capture the geometric properties of the data and hence, show better generalization. The performance of the oblique decision trees depends on the way oblique hyperplanes are generate and the data used for the generation of those hyperplanes. Recently, multiple classifiers have been used in a heterogeneous random forest (RaF) classifier, however, it fails to generate the trees of proper depth. Moreover, double RaF studies highlighted that larger trees can be generated via bootstrapping the data at each non-leaf node and splitting the original data instead of the bootstrapped data recently. The study of heterogeneous RaF lacks the generation of larger trees while as the double RaF based model fails to take over the geometric characteristics of the data. To address these shortcomings, we propose heterogeneous oblique double RaF. The proposed model employs several linear classifiers at each non-leaf node on the bootstrapped data and splits the original data based on the optimal linear classifier. The optimal hyperplane corresponds to the models based on the optimized impurity criterion. The experimental analysis indicates that the performance of the introduced heterogeneous double random forest is comparatively better than the baseline models. To demonstrate the effectiveness of the proposed heterogeneous double random forest, we used it for the diagnosis of Schizophrenia disease. The proposed model predicted the disease more accurately compared to the baseline models. © 2023, CC BY-NC-ND.

关键词： Decision trees

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