An Overview of Approaches and Challenges for Retrieving Marine Inherent Optical Properties from Ocean Color Remote Sensing

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches

Development of monitoring and control systems for biotechnological processes

The field of biotechnology represents an important research area that has gained increasing success in recent times. Characterized by the involvement of biological organisms in manufacturing processes, its areas of application are broad and include the pharmaceuticals, agri-food, energy, and even waste treatment. The implication of living microorganisms represents the common element in all bioprocesses. Cell cultivations is undoubtedly the key step that requires maintaining environmental conditions in precise and defined ranges, having a significant impact on the process yield and thus on the desired product quality. The apparatus in which this process occurs is the bioreactor. Unfortunately, monitoring and controlling these processes can be a challenging task because of the complexity of the cell growth phenomenon and the limited number of variables can be monitored in real-time. The thesis presented here focuses on the monitoring and control of biotechnological processes, more specifically in the production of bioethanol by fermentation of sugars using yeasts. The study conducted addresses several issues related to the monitoring and control of the bioreactor, in which the fermentation takes place. First, the topic concerning the lack of proper sensors capable of providing online measurements of key variables (biomass, substrate, product) is investigated. For this purpose, nonlinear estimation techniques are analyzed to reconstruct unmeasurable states. In particular, the geometric observer approach is applied to select the best estimation structure and then a comparison with the extended Kalman filter is reported. Both estimators proposed demonstrate good estimation capabilities as input model parameters vary. Guaranteeing the achievement of the desired ethanol composition is the main goal of bioreactor control. To this end, different control strategies, evaluated for three different scenarios, are analzyed. The results show that the MIMO system, together with an estimator for ethanol composition, ensure the compliance with product quality. After analyzing these difficulties through numeric simulations, this research work shifts to testing a specific biotechnological process such as manufacturing bioethanol from brewery’s spent grain (BSG) as renewable waste biomass. Both acid pre-treatment, which is necessary to release sugars, and fermentation are optimized. Results show that a glucose yield of 18.12 per 100 g of dried biomass is obtained when the pre-treatment step is performed under optimized conditions (0.37 M H2SO4, 10% S-L ratio). Regarding the fermentation, T=25°C, pH=4.5, and inoculum volume equal to 12.25% v/v are selected as the best condition, at which an ethanol yield of 82.67% evaluated with respect to theoretical one is obtained. As a final step, the use of Raman spectroscopy combined with chemometric techniques such as Partial Least Square (PLS) analysis is evaluated to develop an online sensor for fermentation process monitoring. The results show that the biomass type involved significantly affects the acquired spectra, making them noisy and difficult to interpret. This represents a nontrivial limitation of the applied methodology, for which more experimental data and more robust statistical techniques could be helpful

An Overview of Approaches and Challenges for Retrieving Marine Inherent Optical Properties from Ocean Color Remote Sensing

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectancesthat can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namelythe ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a watermass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and itsdissolved and particulate constituents. Because of their dependence on the concentration and composition ofmarine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This informationis critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbonproduction and export, phytoplankton dynamics, and responses to climatic disturbances. Given their im-portance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products intothe community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., theglobal, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mis-sion), we present a synopsis of the current state of the art in the retrieval of these core optical properties.Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separatedbased their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated witheach approach are provided, as well as common performance metrics used to evaluate them. We discuss currentknowledge gaps and make recommendations for future investment for upcoming missions whose instrumentcharacteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

"The Physics of Evolving Matter: Memory, Learning and Evolution" The Geilo School 2022, March 21-31, Geilo, Norway

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Exploration of carbon nanotube composites and piezoelectric materials for implantable devices

This thesis describes an exploration of carbon nanotube (CNT) nanocomposites for application in implantable medical devices. The focus here is on materials and structures of interest as components of devices incorporating electrodes. Electrodes for implantable devices are commonly required to interface between an electrical system, where the charge carriers are electrons presented through a metal, and human tissue, where the charge carriers are ions as well as electrons not in a metal. These interfaces are found to be prone to issues such as fibrosis and rejection. The properties of carbon nanomaterials, piezoelectric peptides/polymers and their composites suggest them as promising candidate materials that could resolve these issues. The superior conductivity, mechanical properties and chemical stability of carbon nanotubes have been explored in recent years for potential application in biomedical sensors and devices. This work has explored piezoelectric materials, carbon nanotubes, polymers and nanocomposites of these as potential components of implantable devices. Diphenylalanine is a chiral, amphiphilic dipeptide molecule which has the ability to self-assemble into piezoelectric microtubules. The self-assembly process of diphenylalanine microtubules has been explored and its properties have been compared to the properties of poly[vinylidenefluoride-co-trifluoroethylene] (P[VDF-TrFE]) electrospun nanofibres. Later parts of this work considered the deposition of electrodes by printing. The development of CNT-polymer nanocomposites as printable inks for the fabrication of electrodes was explored. The structure and properties of the piezoelectric nano/ micro-materials, CNT-peptide complex and conductive CNT-polymer printable inks were characterised by a range of microscopic and spectroscopic techniques. The viability of neural cells on the developed functional materials and electrodes were tested by metabolic activity measurements and immunochemical staining microscopy. A CNT-polymer ink demonstrated good conductivity and dimensional stability when printed by 3D printer. Good biocompatibility of all the functional materials developed have been demonstrated in vitro, showing promise for further development of soft electrodes and applications in nanostructure piezoelectric sensors and implantable devices

Raman spectroscopic techniques for meat analysis: A review

Raman spectroscopy (vibrational spectroscopy) proved to be an effective analytical approach in the field of geology, semiconductors, materials and polymers. Over the past decade, Raman spectroscopy has attracted the attention of researchers as a non-destructive, highly sensitive, fast and eco-friendly method and has demonstrated the unique capabilities of food analysis. The use of Raman spectroscopic methods (RSMs) to assess the quality of meat and finished products is rapidly expanding. From the analysis of one sample, you can get a large amount of information about the structure of proteins, the composition of fatty acids, organoleptic parameters, autolysis and spoilage indicators, authentication of raw materials, technological properties. An important advantage of the method is the comparability of the results obtained with the data of traditional analytical methods. Traditional methods of determining the quality of meat are often time-consuming, expensive and lead to irreversible damage to a sample. It is difficult to use them in production conditions directly on the meat processing lines. Technological advances have made it possible to develop portable Raman spectroscopes to use directly in production. The article presents the basic principles of Raman spectroscopy, system  atizes the results of the use of RSMs for the analysis of meat quality from different types of slaughter animals and provides tools for analyzing the data of the obtained spectra. Raman spectra have many dependent variables, so chemometric assays are used to work with them. Literature analysis has shown that currently there is no unified database of meat spectra in the world, standardized protocols for conducting research and processing the obtained results. In Russia, the use of RSMs is a new,Raman spectroscopy (vibrational spectroscopy) proved to be an effective analytical approach in the field of geology, semiconductors, materials and polymers. Over the past decade, Raman spectroscopy has attracted the attention of researchers as a non-destructive, highly sensitive, fast and eco-friendly method and has demonstrated the unique capabilities of food analysis. The use of Raman spectroscopic methods (RSMs) to assess the quality of meat and finished products is rapidly expanding. From the analysis of one sample, you can get a large amount of information about the structure of proteins, the composition of fatty acids, organoleptic parameters, autolysis and spoilage indicators, authentication of raw materials, technological properties. An important advantage of the method is the comparability of the results obtained with the data of traditional analytical methods. Traditional methods of determining the quality of meat are often time-consuming, expensive and lead to irreversible damage to a sample. It is difficult to use them in production conditions directly on the meat processing lines. Technological advances have made it possible to develop portable Raman spectroscopes to use directly in production. The article presents the basic principles of Raman spectroscopy, system  atizes the results of the use of RSMs for the analysis of meat quality from different types of slaughter animals and provides tools for analyzing the data of the obtained spectra. Raman spectra have many dependent variables, so chemometric assays are used to work with them. Literature analysis has shown that currently there is no unified database of meat spectra in the world, standardized protocols for conducting research and processing the obtained results. In Russia, the use of RSMs is a new, promising and relevant area of research in the field of meat quality

Spider silk as a blueprint for greener materials : a review

Spider silk exhibits remarkable properties, especially its well-known tensile performances. They rely on a complex nanostructured hierarchical organisation that studies progressively elucidate. Spider silk encompasses a vast range of fibres that exhibit diverse and captivating physical and biological characteristics. The full understanding of the relation between structure and properties may lead in the future to the design of a variety of high-performance, tailored materials and devices. Reknown for being produced in mild and benign conditions, this outstanding biological material constitutes one of the more representative example of biomimetism. In addition, silk’s structure is produced with limited means, i.e. low energy and relatively simple renewable constituents (silk proteins). Then, if successfully controlled and adequately transposed in biomaterials, some properties of natural silk could lead to innovative green materials that may contribute to reduce the ecological footprint of societies. In fact, striking recent advanced applications made with B. mori silk suggest that spider silk-based materials may lead to advanced resistant and functional materials, then becoming among the most promising subject of study in material science. However, several challenges have to be overcome, especially our ability to produce native-like silk, to control biomaterials’ structure and properties and to minimise their ecological footprint. This paper reviews the characteristics of spider silk that make it so attractive and that may (or may not) contribute to reduce ecological footprint of materials and the challenges in producing innovative spider silk-based materials. First, from a biomimetic perspective, the structure and models that explain the tensile resistance of natural silk are presented, followed by the state of knowledge regarding natural silk spinning process and synthetic production methods. Biocompatibility (biosafety and biofunctionality) as well as biodegradability issues are then addressed. Finally, examples of applications are reviewed. Features that may lead to the design of green materials are emphasised throughout

Atmospheric particulate matter characterization by Fourier transform infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks

Atmospheric particulate matter (PM) is a complex mixture of many different substances and requires a suite of instruments for chemical characterization. Fourier transform infrared (FT-IR) spectroscopy is a technique that can provide quantification of multiple species provided that accurate calibration models can be constructed to interpret the acquired spectra. In this capacity, FT-IR spectroscopy has enjoyed a long history in monitoring gas-phase constituents in the atmosphere and in stack emissions. However, application to PM poses a different set of challenges as the condensed-phase spectrum has broad, overlapping absorption peaks and contributions of scattering to the mid-infrared spectrum. Past approaches have used laboratory standards to build calibration models for prediction of inorganic substances or organic functional groups and predict their concentration in atmospheric PM mixtures by extrapolation. In this work, we review recent studies pursuing an alternate strategy, which is to build statistical calibration models for mid-IR spectra of PM using collocated ambient measurements. Focusing on calibrations with organic carbon (OC) and elemental carbon (EC) reported from thermal-optical reflectance (TOR), this synthesis serves to consolidate our knowledge for extending FT-IR spectroscopy to provide TOR-equivalent OC and EC measurements to new PM samples when TOR measurements are not available. We summarize methods for model specification, calibration sample selection, and model evaluation for these substances at several sites in two US national monitoring networks: seven sites in the Interagency Monitoring of Protected Visual Environments (IMPROVE) network for the year 2011 and 10 sites in the Chemical Speciation Network (CSN) for the year 2013. We then describe application of the model in an operational context for the IMPROVE network for samples collected in 2013 at six of the same sites as in 2011 and 11 additional sites. In addition to extending the evaluation to samples from a different year and different sites, we describe strategies for error anticipation due to precision and biases from the calibration model to assess model applicability for new spectra a priori. We conclude with a discussion regarding past work and future strategies for recalibration. In addition to targeting numerical accuracy, we encourage model interpretation to facilitate understanding of the underlying structural composition related to operationally defined quantities of TOR OC and EC from the vibrational modes in mid-IR deemed most informative for calibration. The paper is structured such that the life cycle of a statistical calibration model for FT-IR spectroscopy can be envisioned for any substance with IR-active vibrational modes, and more generally for instruments requiring ambient calibrations