Academic Articles & Research Papers

Photocatalytic degradation using Bi-doped SnS Quantum dots and phytotoxicity evaluation of treated effluents through seed germination

Quantum dots (QDs) are employed in photocatalytic applications because of their distinctive optical characteristics, such as high absorption coefficients and tunable bandgaps, enabling efficient visible light absorption and charge carrier g...

Dielectric and impedance spectroscopic studies of three phase graphene/titania/poly(vinyl alcohol) nanocomposite films

Flexible dielectric polymer composites with high dielectric permittivity and low dielectric loss have many applications in different areas of electronic industry. In this paper, we propose synthesis of flexible dielectric materials with eff...

Editorial: Optical imaging and neurorehabilitation strategies after stroke

Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach

The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), th...

Rapid profiling of carcinogenic types of Helicobacter pylori infection via deep learning analysis of label-free SERS spectra of human serum

WHO classified Helicobacter pylori as a Group I carcinogen for gastric cancer as early as 1994. However, despite the high prevalence of H. pylori infection, only about 3 % of infected individuals eventually develop gastric cancer, with the ...

Rapid identification of bloodstream infection pathogens and drug resistance using Raman spectroscopy enhanced by convolutional neural networks

Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can ...

Machine learning and soil sciences: a review aided by machine learning tools

Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...

AutodiDAQt: Simple Scientific Data Acquisition Software with Analysis-in-the-Loop

Scientific data acquisition is a problem domain that has been underserved by its computational tools despite the need to efficiently use hardware, to guarantee validity of the recorded data, and to rapidly test ideas by configuring experime...

A novel method based on high-resolution imaging spectroscopy to predict fine-root traits and the economics space of fresh tree roots.

Guiding functional near-infrared spectroscopy research on sedentary behavior and brain health.

Applications of machine learning in spectroscopy

The way to analyze data in spectroscopy has changed substantially. At the same time, data science has evolved to the point where spectroscopy can find space to be housed, adapted and be functional. The integration of the two sciences has in...

Portable NIR Spectroscopy Combined with Machine Learning for Kiwi Ripeness Classification: An Approach to Precision Farming

This study aims to evaluate and classify the ripening stages of yellow-fleshed kiwifruit by integrating spectral and physicochemical data collected from the pre-harvest phase through 60 days of storage. A portable near-infrared (NIR) spectr...

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

Fate of hydrogen sulphide on refractory oxide nanoparticles via foundation model-accelerated atomistic modelling and in situ spectroscopy.

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

Optical Rotation Approach to Search for the Electric Dipole Moment of the Electron

The P , T -odd Faraday effect (i.e., rotation of the polarization plane of light propagating through a medium in presence of the external electric field due to P , T symmetry violating interactions) is considered for sev...