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Separations ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 191
Author(s):  
Irene Dini ◽  
Ritamaria Di Lorenzo ◽  
Antonello Senatore ◽  
Daniele Coppola ◽  
Sonia Laneri

The determination of alcohol, SO2, and total acids in wine through conventional laboratory techniques have some limitations related to the amount of the samples, analytical preparation of laboratory staff, and time to carry out the analysis. In recent years, spectroscopic and chromatographic methods have been proposed to determinate simultaneously multiple analytical parameters. The new methods claim the speed of analysis and easy execution. However, they need a validation process that guarantees the reliability of the results to be used in official determinations. This study aimed to evaluate the usefulness of FT-infrared reflectance (FT-IR) to quantify total acid, alcohol, and SO2 concentration in the wines. For this purpose, 156 DOC Italian wines were tested with IR technology, and results were compared to those obtained by official analysis methods. The comparison was performed using two non-parametric statistical methods: the Bland & Altman test and Passing & Bablok regression. Our results showed that the spectrophotometric methods make errors due to interfering contaminants in the sample that can be corrected by blank determination. Therefore, the spectrophotometric methods that use the infrared region of the electromagnetic spectrum can be used by the wine industry and regulators for the wine routine as an alternative to official methodologies.


Molecules ◽  
2021 ◽  
Vol 26 (16) ◽  
pp. 4918
Author(s):  
Mihkel Kaljurand ◽  
Piret Saar-Reismaa ◽  
Merike Vaher ◽  
Jelena Gorbatsova ◽  
Jekaterina Mazina-Šinkar

Flow analysis is the science of performing quantitative analytical chemistry in flowing streams. Because of its efficiency and speed of analysis, capillary electrophoresis (CE) is a prospective method for the monitoring of a flow composition withdrawn from various processes (e.g., occurring in bioreactors, fermentations, enzymatic assays, and microdialysis samples). However, interfacing CE to a various flow of interest requires further study. In this paper, several ingenious approaches on interfacing flow from various chemical or bioprocesses to a capillary electrophoresis instrument are reviewed. Most of these interfaces can be described as computer-controlled autosamplers. Even though most of the described interfaces waste too many samples, many interesting and important applications of the devices are reported. However, the lack of commercially available devices prevents the wide application of CE for flow analysis. On the contrary, this fact opens up a potential avenue for future research in the field of flow sampling by CE.


2021 ◽  
Vol 132 ◽  
pp. S82-S83
Author(s):  
Go Hun Seo ◽  
So Young Kim ◽  
Bong Jik Kim ◽  
Doo Yi Oh ◽  
Jin Hee Han ◽  
...  

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1768
Author(s):  
Miroslav Rievaj ◽  
Eva Culková ◽  
Damiána Šandorová ◽  
Zuzana Lukáčová-Chomisteková ◽  
Renata Bellová ◽  
...  

This short review deals with the properties and significance of the determination of selenium, which is in trace amounts an essential element for animals and humans, but toxic at high concentrations. It may cause oxidative stress in cells, which leads to the chronic disease called selenosis. Several analytical techniques have been developed for its detection, but electroanalytical methods are advantageous due to simple sample preparation, speed of analysis and high sensitivity of measurements, especially in the case of stripping voltammetry very low detection limits even in picomoles per liter can be reached. A variety of working electrodes based on mercury, carbon, silver, platinum and gold materials were applied to the analysis of selenium in various samples. Only selenium in oxidation state + IV is electroactive therefore the most of voltammetric determinations are devoted to it. However, it is possible to detect also other forms of selenium by indirect electrochemistry approach.


2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Alba Alvarez-Martin ◽  
John George ◽  
Emily Kaplan ◽  
Lauren Osmond ◽  
Leah Bright ◽  
...  

AbstractTwo mass spectrometry (MS) methods, solid-phase microextraction gas chromatography (SPME–GC–MS) and direct analysis in real time (DART-MS), have been explored to investigate widespread efflorescence observed on exhibited objects at the Smithsonian’s National Museum of the American Indian in New York (NMAI-NY). Both methods show great potential, in terms of speed of analysis and level of information, for identifying the organic component of the efflorescence as 2,2,6,6-tetramethyl-4-piperidinol (TMP-ol) emitted by the structural adhesive (Terostat MS 937) used for exhibit case construction. The utility of DART-MS was proven by detecting the presence of TMP-ol in construction materials in a fraction of the time and effort required for SPME–GC–MS analysis. In parallel, an unobtrusive SPME sampling strategy was used to detect volatile organic compounds (VOCs) accumulated in the exhibition cases. This sampling technique can be performed by collections and conservation staff at the museum and shipped to an off-site laboratory for analysis. This broadens the accessibility of MS techniques to museums without access to instrumentation or in-house analysis capabilities.


:Graphics processing unit (GPU) is a computer programmable chip that could perform rapid mathematical operations that can be accelerated with massive parallelism. In the early days, central processing unit (CPU) was responsible for all computations irrespective of whether it is feasible for parallel computation. However, in recent years GPUs are increasingly used for massively parallel computing applications, such as training Deep Neural Networks. GPU’s performance monitoring plays a key role in this new era since GPUs serve an inevitable role in increasing the speed of analysis of the developed system. GPU administration comes in picture to efficiently utilize the GPU when we deal with multiple workloads to run on the same hardware. In this study, various GPUparameters are monitored and help to keep them in safe levels and also to keep the improved performance of the system. This study,


Handwriting is one of the most natural ways of communication among people. The handwriting recognition task is the main concern of scientific community because handwriting can be varies with the same person or from one person to another hence the prediction of human behavior through handwriting is a complex task. Earlier the handwriting analysis has been done by graphologists but due to the modernization and the arrival of digital world the handwriting analysis can be done with the help of computer aided machines. Different software and algorithms has been defined to do the analysis. In the new world of machine learning handwriting recognition and the prediction of human behavior can be done by using different techniques of machine learning which increase the speed of analysis This paper studies the recent advances and the trends in the field of handwriting recognition by machine learning


2019 ◽  
Vol 2 (3) ◽  
pp. 60 ◽  
Author(s):  
Felix Kaspar ◽  
Robert T. Giessmann ◽  
Niels Krausch ◽  
Peter Neubauer ◽  
Anke Wagner ◽  
...  

Efficient reaction monitoring is crucial for data acquisition in kinetic and mechanistic studies. However, for conversions of nucleosides to their corresponding nucleobases, as observed in enzymatically catalyzed nucleoside phosphorylation reactions, the current analytical arsenal does not meet modern requirements regarding cost, speed of analysis and high throughput. Herein, we present a UV/Vis spectroscopy-based assay employing an algorithm for spectral unmixing in a 96-well plate format. The algorithm relies on fitting of reference spectra of nucleosides and their bases to experimental spectra and allows determination of nucleoside/nucleobase ratios in solution with high precision. The experimental procedure includes appropriate dilution of a sample into aqueous alkaline solution, transfer to a multi-well plate, measurement of a UV/Vis spectrum and subsequent in silico spectral unmixing. This enables data collection in a high-throughput fashion and reduces costs compared to state-of-the-art HPLC analyses by approximately 5-fold while being 20-fold faster and offering comparable precision. Additionally, the method is robust regarding dilution and sample transfer errors as it only considers spectral form and not absolute intensity. It can be applied to all natural nucleosides and nucleobases and even unnatural ones as demonstrated by several examples.


2019 ◽  
Vol 11 (9) ◽  
pp. 1123 ◽  
Author(s):  
Jérémie Sublime ◽  
Ekaterina Kalinicheva

Post-disaster damage mapping is an essential task following tragic events such as hurricanes, earthquakes, and tsunamis. It is also a time-consuming and risky task that still often requires the sending of experts on the ground to meticulously map and assess the damages. Presently, the increasing number of remote-sensing satellites taking pictures of Earth on a regular basis with programs such as Sentinel, ASTER, or Landsat makes it easy to acquire almost in real time images from areas struck by a disaster before and after it hits. While the manual study of such images is also a tedious task, progress in artificial intelligence and in particular deep-learning techniques makes it possible to analyze such images to quickly detect areas that have been flooded or destroyed. From there, it is possible to evaluate both the extent and the severity of the damages. In this paper, we present a state-of-the-art deep-learning approach for change detection applied to satellite images taken before and after the Tohoku tsunami of 2011. We compare our approach with other machine-learning methods and show that our approach is superior to existing techniques due to its unsupervised nature, good performance, and relative speed of analysis.


2018 ◽  
Vol 3 (9) ◽  
Author(s):  
Anastasia Rousaki ◽  
Luc Moens ◽  
Peter Vandenabeele

Abstract Archaeometry is the research area on the edge between humanities and natural sciences: it uses and optimises methods from chemistry, spectroscopy, physics, biology, etc. to help answering research questions from humanities. In general, these objects are investigated for several reasons. Besides the fundamental interest to know about the materials that were used in the past, the study of artefacts can support their preservation, either by helping to select optimal storage or display conditions, either by investigating decay pathways and suggesting solutions. Other reasons for art analysis include provenance studies, dating the artefact or identifying forgeries. Since several years, Raman spectroscopy is increasingly applied for the investigation of objects of art or archaeology. The technique is well-appreciated for the limited (or even absent) sample preparation, the relative straightforward interpretation of the spectra (by fingerprinting - comparing them against a database of reference pigments) and its speed of analysis. Moreover, the small spectral footprint – allowing to record a molecular spectrum of particles down to 1 µm, the typical size of pigment grains – is certainly a positive property of the technique. Raman spectroscopy can be considered as rather versatile, as inorganic as well as organic materials can be studied, and as the technique can gather information on crystalline as well as on non-crystalline phases. As a consequence, Raman spectroscopy can be used to study antique objects and twentieth-century synthetic (organic) materials – illustrating the wide range of applications. Finally, the technique is as non-destructive, provided the laser power is kept sufficiently low not to damage the artwork. In literature, the terms “non-invasive” and “non-destructive” are used, where the first term means that no sampling is involved, and the latter term indicates that no sample is taken or that during analysis the sample is not consumed (destroyed) and remains available for further analysis.


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