Results 101 to 110 of about 246,578 (242)

Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore

Advanced Functional Materials, EarlyView.
To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul, Archith Rayabharam, Lisa Almonte, Eveline Rigo, Joshy Joseph, Ashutosh Kumar, Zhuxin Dong, Narayana Aluru, Gregory Timp   +8 more
wiley   +1 more source

Modification of the LSTM Model in Time Series Data Prediction

Lontar Komputer
Accurate stock price forecasting is crucial in supporting investment decision-making, especially during stock price fluctuations. This research aims to improve the accuracy of stock price prediction on time series data through modification of the Long ...
Daniel Robi Sanjaya, Bayu Surarso, Tarno Tarno   +2 more
doaj   +1 more source

Stock Price Pattern Prediction Based on Complex Network and Machine Learning

Complexity, 2019
Complex networks in stock market and stock price volatility pattern prediction are the important issues in stock price research. Previous studies have used historical information regarding a single stock to predict the future trend of the stock’s price ...
Hongduo Cao, Tiantian Lin, Ying Li, Hanyu Zhang   +3 more
doaj   +1 more source

Programmable DNA‐Peptide Hybrid Nanostructures for Potent Neutralization of Multiple Influenza a Virus Subtypes

Advanced Functional Materials, EarlyView.
A multivalent antiviral platform based on honeycomb‐shaped DNA nanostructures (HC–Urumin) is developed to enhance the potency and breadth of the host defense peptide Urumin. Through spatially patterned trimeric presentation, HC–Urumin disrupts influenza A virus entry, improves cell viability, and reduces disease severity in vivo‐offering a modular and ...
Saurabh Umrao, Abhisek Dwivedy, Payton L. Haak, Dhanush Gandavadi, Laurie A. Rund, Chi Chen, Vineetha Mareddy, Lifeng Zhou, Jinwei Duan, Ying Fang, Andrew J. Steelman, Xing Wang   +11 more
wiley   +1 more source

GAN-Enhanced Nonlinear Fusion Model for Stock Price Prediction

International Journal of Computational Intelligence Systems
Stock price prediction is a significant field of finance research for both academics and practitioners. Numerous studies have proved that the stock movement can be fully reflect various internal features of stock price including non-stationary behavior ...
Yingcheng Xu, Yunfeng Zhang, Peide Liu, Qiuyue Zhang, Yuqi Zuo   +4 more
doaj   +1 more source

GRU_vader: Sentiment-Informed Stock Market Prediction

Mathematics
Stock price prediction is challenging due to global economic instability, high volatility, and the complexity of financial markets. Hence, this study compared several machine learning algorithms for stock market prediction and further examined the ...
Akhila Mamillapalli, Bayode Ogunleye, Sonia Timoteo Inacio, Olamilekan Shobayo   +3 more
doaj   +1 more source

Implementasi Model Fungsi Transfer dan Neural Network untuk Meramalkan Harga Penutupan Saham (Close Price)

Jurnal Matematika, 2019
The multivariate forecasting model is a model of forecasting that takes into the causal relationship between a prediction factor with one or more independent variables. This study uses multivariate  forecasting model that are transfer function and neural
Nila Rahmawati, Trianingsih Eni Lestari
doaj   +1 more source

High‐Rate FA‐Based Co‐Evaporated Perovskites: Understanding Rate Limitations and Practical Considerations to Overcome Their Impact

Advanced Functional Materials, EarlyView.
Vacuum‐based deposition is promising for perovskite solar cells to be successfully commercialized. However, co‐evaporation, the most common vapor phase deposition technique, suffers from very low deposition rates. In this work, we reveal that high deposition rates can lead to carbon flakes depositing into the perovskite absorber layers due to material ...
Thomas Feeney, Aleksandra Miaskiewicz, Julian Petry, Felix Laufer, Roja Singh, Stefanie Severin, Viktor Škorjanc, Alexander Diercks, Suresh Maniyarasu, Lars Korte, Steve Albrecht, Ulrich W. Paetzold, Marcel Roß, Paul Fassl   +13 more
wiley   +1 more source

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

Advanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo, Ewa Anna Oprzeska‐Zingrebe, Mariana Kozlowska, Lennart Hilbert, Iliya D. Stoev   +4 more
wiley   +1 more source

Fusion of Technical Indicators and Sentiment Analysis in a Hybrid Framework of Deep Learning Models for Stock Price Movement Prediction

IEEE Access
Stock price movement prediction is challenging due to unpredictable fluctuations and the significant impact of market sentiment and news. Accurate prediction models can enhance investor decision-making and control over stock price movements.
Fatemeh Moodi, Amir Jahangard Rafsanjani, Sajjad Zarifzadeh, Mohammad Ali Zare Chahooki   +3 more
doaj   +1 more source