Results 131 to 140 of about 655,816 (301)
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point +7 more
wiley +1 more source
A representation learning-based time series label propagation for smart grid attack detection
The rising incidence of cyber attacks targeting smart grids underscores the urgent need for robust protection mechanisms. Most of the existing smart grid cyber attack detection schemes need correctly labeled data for training.
Smruti P. Dash, Kedar V. Khandeparkar
doaj +1 more source
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
Development of human monoclonal antibodies against TARM1 by yeast display
Human monoclonal antibodies against TARM1 are generated by yeast display‐guided selection. These antibodies bind to soluble and cell‐surface forms of TARM1. Also, these antibodies exhibit agonistic activity in the NFAT‐GFP reporter assay, indicating that TARM1 signaling can be functionally modulated by antibodies and suggesting TARM1 as a potential ...
Rikio Yabe +5 more
wiley +1 more source
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Pattern Representation of Gas Concentration Time Series Based on Piecewise Linear Method
The paper indicated it not only has low efficiency of data mining to directly use original gas concentration time series to forecast short-term concentration,query similarity and classify and cluster time series,but also affects accuracy and reliability ...
XU Hui~ +3 more
doaj
Time series classification (TSC) has numerous applications across various domains. This research introduces a federated hybrid TSC method that combines image-based time series representation techniques with Convolutional Neural Networks (CNNs) in a ...
Felipe A. R. Silva +6 more
doaj +1 more source
Attention as Robust Representation for Time Series Forecasting
Time series forecasting is essential for many practical applications, with the adoption of transformer-based models on the rise due to their impressive performance in NLP and CV. Transformers' key feature, the attention mechanism, dynamically fusing embeddings to enhance data representation, often relegating attention weights to a byproduct role.
Peisong Niu +4 more
openaire +2 more sources
Screening and epitope characterization of Nidogen‐2‐specific nanobodies
Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen +9 more
wiley +1 more source
Random Walks and Non-Linear Paths in Macroeconomic Time Series: Some Evidence and Implications [PDF]
This paper investigates whether the inherent non-stationarity of macroeconomic time series is entirely due to a random walk or also to non-linear components. Applying the numerical tools of the analysis of dynamical systems to long time series for the US,
Franco Bevilacqua, Adriaan van Zon
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