Time-domain spectroscopy encompasses a wide range of techniques, such as Fourier-transform infrared, pump-probe, Fourier-transform Raman, and two-dimensional electronic spectroscopies. These methods enable various applications, such as molecule characterization, excited state dynamics studies, or spectral classification. Typically, these techniques rarely use sampling schemes that exploit the prior knowledge scientists typically have before the actual experiment. Indeed, not all sampling coordinates carry the same amount of information, and a careful selection of the sampling points may notably affect the resulting performance. In this work, we rationalize, with examples, the various advantages of using an optimal sampling scheme tailored to the specific experimental characteristics and/or expected results. We show that using a sampling scheme optimizing the Fisher information minimizes the variance of the desired parameters. This can greatly improve, for example, spectral classifications and multidimensional spectroscopy. We demonstrate how smart sampling may reduce the acquisition time of an experiment by one to two orders of magnitude, while still providing a similar level of information.
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http://dx.doi.org/10.1063/5.0206838 | DOI Listing |
J Med Eng Technol
December 2024
Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran.
Nowadays, photoplethysmograph (PPG) technology is being used more often in smart devices and mobile phones due to advancements in information and communication technology in the health field, particularly in monitoring cardiac activities. Developing generative models to generate synthetic PPG signals requires overcoming challenges like data diversity and limited data available for training deep learning models. This paper proposes a generative model by adopting a genetic programming (GP) approach to generate increasingly diversified and accurate data using an initial PPG signal sample.
View Article and Find Full Text PDFBMC Plant Biol
December 2024
College of Agronomy and Biotechnology, Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming, 650201, China.
Background: Yellow nutsedge (Cyperus esculentus, known as 'YouShaDou' in China, YSD) and purple nutsedge (Cyperus rotundus, known as 'XiangFuZi' in China, XFZ), closely related Cyperaceae species, exhibit significant differences in triacylglycerol (TAG) accumulation within their tubers, a key factor in carbon flux repartitioning that highly impact the total lipid, carbohydrate and protein metabolisms. Previous studies have attempted to elucidate the carbon anabolic discrepancies between these two species, however, a lack of comprehensive genome-wide annotation has hindered a detailed understanding of the underlying molecular mechanisms.
Results: This study utilizes transcriptomic analyses, supported by a comprehensive YSD reference genome, and metabolomic profiling to uncover the mechanisms underlying the major carbon perturbations between the developing tubers of YSD and XFZ germplasms harvested in Yunnan province, China, where the plant biodiveristy is renowned worldwide and may contain more genetic variations relative to their counterparts in other places.
Sci Rep
December 2024
School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing, 401331, China.
In the field of rehabilitation, although deep learning have been widely used in multitype gesture recognition via surface electromyography (sEMG), their higher algorithmic complexity often leads to low computationally inefficient, which compromise their practicality. To achieve more efficient multitype recognition, We propose the Residual-Inception-Efficient (RIE) model, which integrates Inception and efficient channel attention (ECA). The Inception, which is a multiscale fusion convolutional module, is adopted to enhance the ability to extract sEMG features.
View Article and Find Full Text PDFPharmacy (Basel)
December 2024
R&D for Clinical Activity in Telemedicine, Italian National Health Agency-AGENAS, 00187 Rome, Italy.
Atrial fibrillation (AF) is one of the most common cardiac arrhythmias of clinical relevance and a major cause of cardiovascular morbidity and mortality. Following a diagnosis of AF, patients are directed towards therapy with anticoagulant drugs to reduce the thromboembolic risk and antiarrhythmics to control their cardiac rhythm, with periodic follow-up checks. Despite the great ease of handling these drugs, we soon realized the need for follow-up models that would allow the appropriateness and safety of these pharmacological treatments to be monitored over time.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
International Research Center for Food and Health, Laboratory of Quality and Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai Engineering Research Center of Aquatic-Product Process & Preservation, College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China.
Accurate methods for assessing food freshness through colorimetric pH response play a critical role in determining food spoilage and ensuring food quality standards. This study introduces a novel unlabeled DNA sequence, poly-dA, designed to exploit the colorimetric properties of both the single strand and the fold-back A-motif structure in conjunction with gold nanoparticles (AuNPs) under varying pH conditions. When exposed to storage temperatures of 4 °C and 25 °C, the color variations in the AuNP solution, influenced by pH level changes in mutton and sea bass samples' different storage periods, are easily discernible to the naked eye within a minute.
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