Positive biocompatibility of nanocrystalline glass-like carbon thin films

The interest in carbon nanomaterials with high transparency and electrical conductivity has grown within the last decade in view of a wide variety of applications, including biocompatible sensors, diagnostic devices and bioelectronic implants. The aim of this work is to test the biocompatibility of particular nanometer-thin nanocrystalline glass-like carbon films (NGLC), a disordered structure of graphene flakes joined by carbon matrix (Romero et al., 2016). We used a cell line (SN4741) from substantia nigra dopaminergic cells derived from transgenic mouse embryo cells (Son et al., 1999). Some cells were cultured on top of NGLC films (5, 20 and 80 nm) and other with NGLC nanoflakes (approx. 5-10 mm2) in increasing concentrations: 1, 5, 10, 20 and 50 μg/ml, during 24 h, 3 days and 7 days. Cells growing in normal conditions were defined under culture with DMEM supplemented with 10% FCS, Glucose (0,6%), penicillin-streptomycin (50U/ml) and L-glutamine (2mM) at 5%CO2 humidified atmosphere. Nanoflakes were resuspended in DMEM at the stock concentration (2 g/l). The experiments were conducted in 96 well plates (Corning) using 2500 cells per well. For MTT analysis, the manufacturer recommendations were followed (Roche, MTT kit assay): a positive control with a 10% Triton X-100 treatments (15 minutes) and a negative control without neither Triton X-100 nor NGLC. As apoptosis/necrosis assay we used LIVE/DEAD® Viability/Cytotoxicity Assay Kit (Invitrogen). In a separate experiment, cells were cultured on top of the NGLC films for 7 days. Primary antibodies: anti-synaptophysin (SYP, clone SY38, Chemicon) and goat anti-GIRK2 (G-protein-regulated inward-rectifier potassium channel 2 protein) (Abcom) following protocol for immunofluorescence. WB for proteins detection performed with a polyclonal anti-rabbit proliferating cell nuclear antigen (PCNA). Results demonstrated the biocompatibility with different concentration of NGLC varying the degree of survival from a low concentration (1 mg/ml) in the first 24 h to high concentrations (20-50 g/ml) after 7 days as it is corroborated by the PCNA analysis. Cells cultured on top of the film showed after 7 days axonal-like alignment and edge orientation as well as net-like images. Neuronal functionality was demonstrated to a certain extent through the analysis of coexistence between SYP and GIRK2. In conclusion, this nanomaterial could offer a powerful platform for biomedical applications such as neural tissue engineering

HIGH VOLTAGE ELECTROPHORETIC DEPOSITION FOR ELECTROCHEMICAL ENERGY STORAGE AND OTHER APPLICATIONS

High voltage electrophoretic deposition (HVEPD) has been developed as a novel technique to obtain vertically aligned forests of one-dimensional nanomaterials for efficient energy storage. The ability to control and manipulate nanomaterials is critical for their effective usage in a variety of applications. Oriented structures of one-dimensional nanomaterials provide a unique opportunity to take full advantage of their excellent mechanical and electrochemical properties. However, it is still a significant challenge to obtain such oriented structures with great process flexibility, ease of processing under mild conditions and the capability to scale up, especially in context of efficient device fabrication and system packaging. This work presents HVEPD as a simple, versatile and generic technique to obtain vertically aligned forests of different one-dimensional nanomaterials on flexible, transparent and scalable substrates. Improvements on material chemistry and reduction of contact resistance have enabled the fabrication of high power supercapacitor electrodes using the HVEPD method. The investigations have also paved the way for further enhancements of performance by employing hybrid material systems and AC/DC pulsed deposition. Multi-walled carbon nanotubes (MWCNTs) were used as the starting material to demonstrate the HVEPD technique. A comprehensive study of the key parameters was conducted to better understand the working mechanism of the HVEPD process. It has been confirmed that HVEPD was enabled by three key factors: high deposition voltage for alignment, low dispersion concentration to avoid aggregation and simultaneous formation of holding layer by electrodeposition for reinforcement of nanoforests. A set of suitable parameters were found to obtain vertically aligned forests of MWCNTs. Compared with their randomly oriented counterparts, the aligned MWCNT forests showed better electrochemical performance, lower electrical resistance and a capability to achieve superhydrophpbicity, indicating their potential in a broad range of applications. The versatile and generic nature of the HVEPD process has been demonstrated by achieving deposition on flexible and transparent substrates, as well as aligned forests of manganese dioxide (MnO2) nanorods. A continuous roll-printing HVEPD approach was then developed to obtain aligned MWCNT forest with low contact resistance on large, flexible substrates. Such large-scale electrodes showed no deterioration in electrochemical performance and paved the way for practical device fabrication. The effect of a holding layer on the contact resistance between aligned MWCNT forests and the substrate was studied to improve electrochemical performance of such electrodes. It was found that a suitable precursor salt like nickel chloride could be used to achieve a conductive holding layer which helped to significantly reduce the contact resistance. This in turn enhanced the electrochemical performance of the electrodes. High-power scalable redox capacitors were then prepared using HVEPD. Very high power/energy densities and excellent cyclability have been achieved by synergistically combining hydrothermally synthesized, highly crystalline α-MnO2 nanorods, vertically aligned forests and reduced contact resistance. To further improve the performance, hybrid electrodes have been prepared in the form of vertically aligned forest of MWCNTs with branches of α-MnO2 nanorods on them. Large- scale electrodes with such hybrid structures were manufactured using continuous HVEPD and characterized, showing further improved power and energy densities. The alignment quality and density of MWCNT forests were also improved by using an AC/DC pulsed deposition technique. In this case, AC voltage was first used to align the MWCNTs, followed by immediate DC voltage to deposit the aligned MWCNTs along with the conductive holding layer. Decoupling of alignment from deposition was proven to result in better alignment quality and higher electrochemical performance.

Calculation of mutual information for nonlinear communication channel at large signal-to-noise ratio

Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications - the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.

Geometrical Methods in Multivariate Risk Management: Algorithms and Applications

This thesis builds a framework for evaluating downside risk from multivariate data via a special class of risk measures (RM). The peculiarity of the analysis lies in getting rid of strong data distributional assumptions and in orientation towards the most critical data in risk management: those with asymmetries and heavy tails. At the same time, under typical assumptions, such as the ellipticity of the data probability distribution, the conformity with classical methods is shown. The constructed class of RM is a multivariate generalization of the coherent distortion RM, which possess valuable properties for a risk manager. The design of the framework is twofold. The first part contains new computational geometry methods for the high-dimensional data. The developed algorithms demonstrate computability of geometrical concepts used for constructing the RM. These concepts bring visuality and simplify interpretation of the RM. The second part develops models for applying the framework to actual problems. The spectrum of applications varies from robust portfolio selection up to broader spheres, such as stochastic conic optimization with risk constraints or supervised machine learning.

Layered Information Modeling and a Knowledge Organization Paradigm: Inherent Classification and the Design of Interoperable Systems

In knowledge technology work, as expressed by the scope of this conference, there are a number of communities, each uncovering new methods, theories, and practices. The Library and Information Science (LIS) community is one such community. This community, through tradition and innovation, theories and practice, organizes knowledge and develops knowledge technologies formed by iterative research hewn to the values of equal access and discovery for all. The Information Modeling community is another contributor to knowledge technologies. It concerns itself with the construction of symbolic models that capture the meaning of information and organize it in ways that are computer-based, but human understandable. A recent paper that examines certain assumptions in information modeling builds a bridge between these two communities, offering a forum for a discussion on common aims from a common perspective. In a June 2000 article, Parsons and Wand separate classes from instances in information modeling in order to free instances from what they call the “tyranny” of classes. They attribute a number of problems in information modeling to inherent classification – or the disregard for the fact that instances can be conceptualized independent of any class assignment. By faceting instances from classes, Parsons and Wand strike a sonorous chord with classification theory as understood in LIS. In the practice community and in the publications of LIS, faceted classification has shifted the paradigm of knowledge organization theory in the twentieth century. Here, with the proposal of inherent classification and the resulting layered information modeling, a clear line joins both the LIS classification theory community and the information modeling community. Both communities have their eyes turned toward networked resource discovery, and with this conceptual conjunction a new paradigmatic conversation can take place. Parsons and Wand propose that the layered information model can facilitate schema integration, schema evolution, and interoperability. These three spheres in information modeling have their own connotation, but are not distant from the aims of classification research in LIS. In this new conceptual conjunction, established by Parsons and Ward, information modeling through the layered information model, can expand the horizons of classification theory beyond LIS, promoting a cross-fertilization of ideas on the interoperability of subject access tools like classification schemes, thesauri, taxonomies, and ontologies. This paper examines the common ground between the layered information model and faceted classification, establishing a vocabulary and outlining some common principles. It then turns to the issue of schema and the horizons of conventional classification and the differences between Information Modeling and Library and Information Science. Finally, a framework is proposed that deploys an interpretation of the layered information modeling approach in a knowledge technologies context. In order to design subject access systems that will integrate, evolve and interoperate in a networked environment, knowledge organization specialists must consider a semantic class independence like Parsons and Wand propose for information modeling.

Recovery of gold(0) nanoparticles from aqueous solutions using effluents from a bioremediation process

The use of biological processes with the aim of the recovery of gold from low-concentration solutions derived from leaching of secondary sources is gaining increasing importance owing to the scarcity of the primary resources and the economic and environmental advantages usually presented by these methods. Thus, the addition in batch and continuous processes of different solutions containing biogenic sulphide, which was generated by the activity of sulphate-reducing bacteria (SRB), to gold(III) solutions was investigated for that purpose. In the batch experiments, AuS nanoparticles with sizes of between 6 and 14 nm were obtained (corresponding to 100% removal of Au(III) from solution) if the biogenic sulphide was generated in a typical nutrient medium for SRB, whereas Au(0) nanoparticles with sizes of below 8 nm were obtained (corresponding to 62% removal of Au(III)) if effluent from a SRB bioremediation process for treating acid mine drainage (AMD) was used instead. These results stimulated the development of a continuous process of addition, in which two sulphide-rich effluents, which resulted from a SRB bioremediation process for treating two types of AMD (from a uranium mine and a polysulphide mine), were tested. In both cases, Au(0) nanoparticles with sizes of between 6 and 15 nm were mainly obtained, and the percentage removal of Au(III) from solution ranged from 76% to 100%. The processes described allow the simultaneous treatment of AMD and recovery of metallic gold nanoparticles, which are a product with a wide range of applications (e.g., in medicine, optical devices and catalysis) and high economic value. The synthesis process described in this work can be considered as novel, because it is the first time, to our knowledge, that the use of effluent from a SRB bioremediation process has been reported for the recovery of gold(III) as gold(0) nanoparticles.

“A long-term mortality analysis of subsidized firms in rural areas: an empirical study in the Portuguese Alentejo region”

Studies have demonstrated that public policies to support private firms’ investment have the ability to promote entrepreneurship, but the sustainability of subsidized firms has not often been analysed. This paper aims to examine this dimension specifically through evaluating the mortality of subsidized firms in the long-term. The analysis focuses on a case study of the LEADER+ Programme in the Alentejo region of Portugal. With this purpose, the paper examines the activity status (active or not active) of 154 private, rural, for-profit firms in Alentejo that had received a subsidy to support investment between 2002 and 2008 under the LEADER+ Programme. The methodology is based on binary choice models in order to study the probability of these firms still being active. The explanatory variables used are the following: (1) the characteristics of entrepreneurs and managers’ strategic decisions, (2) firm profile and characteristics, (3) regional economic environment. Data assessment showed that the cumulative mortality rate of firms on 31st December 2013 is over 20 %. Interpretation of the regression model revealed that he probability of firms’ survival increases with higher investment, firm age and regional business concentration, whereas the number of applications made by firms has a negative impact on their survival. So it seems that for subsidized firms the amount of investment is as important as its frequency.

Studying the alignment of 5-cyanobiphenyl on a polydimethylsiloxane surface through Molecular Dynamics simulations

For 40 years, at the University of Bologna, a group of researchers coordinated by professor Claudio Zannoni has been studying liquid crystals by employing computational techniques. They have developed effective models of these interesting, and still far from being completely understood, systems. They were able to reproduce with simulations important features of some liquid crystal molecules, such as transition temperature. Then they focused their attention on the interactions that these molecules have with different kinds of surface, and how these interactions affect the alignment of liquid crystals. The group studied the behaviour of liquid crystals in contact with different kinds of surfaces, from silica, either amorphous and crystalline, to organic self assembled monolayers (SAMs) and even some common polymers, such as polymethylmethacrylate (PMMA) and polystyrene (PS). Anyway, a library of typical surfaces is still far from being complete, and a lot of work must be done to investigate the cases which have not been analyzed yet. A hole that must be filled is represented by polydimethylsiloxane (PDMS), a polymer on which the interest of industry has enormously grown up in the last years, thanks to its peculiar features, allowing it to be employed in many fields of applications. It has been observed experimentally that PDMS causes 4-cyano-4’-pentylbiphenyl (well known as 5CB), one of the most common liquid crystal molecules, to align homeotropically (i.e. perpendicular) with respect to a surface made of this polymer. Even though some hypothesis have been presented to rationalize the effect, a clear explanation of this phenomenon has not been given yet. This dissertation shows the work I did during my internship in the group of professor Zannoni. The challenge that I had to tackle was to investigate, via Molecular Dynamics (MD) simulations, the reasons of 5CB homeotropic alignment on a PDMS surface, as the group had previously done for other surfaces.

Study of the second hyperpolarizability of poly(3-alkylthiophenes) using the third-harmonic scattering technique

During the past years, the considerable need in the domain of communications for more potent photonic devices has focused the research activities into the nonlinear optical (NLO) materials which can be used for modern optical switches. In this regard, a lot of research activities are focused on the organic materials and conjugated polymers which offer more advantages compared to the inorganic ones. On this matter, poly(3-alkylthiophene) (P3AT), an organic conjugated polymer, can be investigated as potential optical material with in particular the focus on the NLO properties such as the first- and second-hyperpolarizability, β and γ respectively. The activities carried out at the Laboratory of Polymer Synthesis of the KU Leuven, during the master's thesis work, focused on the study of conjugated polymers in order to evaluate their NLO properties for the future purpose of applications in optical systems. In particular, three series of polythiophenes functionalized with an alkyl side chain in the 3-position were synthesized: poly(3-hexylthiophene) (P3HT), poly[3-(2-ethylhexyl)thiophene] (P3EHT) and random copolymer of the two regio-isomers of P3HT. They were made in order to study the influence of molar mass, branching and regio-irregularity on the γ-value. The Kumada catalyst transfer condensative polymerization (KCTCP) and the Pd(RuPhos)-protocol were used for the polymerizations in order to have control over the molar mass of the growing chain and consequently to obtain well-defined and reproducible materials. The P3AT derivatives obtained were characterized by gel permeation chromatography (GPC), spectroscopic techniques (1H-NMR, UV-Vis) and the γ-value was investigated using the third-harmonic scattering (THS) technique. In particular, the THS technique is useful to investigate the optical behavior of the series of polymers in solution.

Development and characterization of innovative graphene-based composites

Over the last decade, graphene and related materials (GRM) have drawn significant interest and resources for their development into the next generation of composite materials. This is because these nanoparticles have the ability to operate as reinforcing additives capable of imparting considerable mechanical property increases while also embedding multi-functional advantages on the host matrix. Because graphene and 2D materials are still in their early stages, the relative maturity of different types of composite systems varies. As a result, certain nanocomposite systems are currently commercially accessible, while others are not yet sufficiently developed to enter the market. A substantial emphasis has been placed on developing thermoplastic and thermosetting materials that combine a variety of mechanical and functional qualities. These include higher strength and stiffness, increased thermal and electrical conductivity, improved barrier properties, fire retardancy, and others, with the ultimate goal of providing multifunctionality to already employed composites. The work presented in this thesis investigates the use and benefits that GRM could bring to composites for a variety of applications, with the goal of realizing multifunctional components with improved properties that leads to lightweight and, as a result, energy and cost savings and pollution reduction in the environment. In particular, we worked on the following topics: • Benchmarking of commercial GRM-based master batches; • GRM-coatings for water uptake reduction; • GRM as thermo-electrical anti-icing /de-icing system; • GRM for Out of Oven curing of composites.

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented.

Strategies to hijack MTs dysfunction in neurodegenerative tauopathies: Design and synthesis of novel CNS-disease-modifying tools

Neuronal microtubules assembly and dynamics are regulated by several proteins including (MT)-associated protein tau, whose aberrant hyperphosphorylation promotes its dissociation from MTs and its abnormal deposition into neurofibrillary tangles, a common neurotoxic hallmarks of neurodegenerative tauopathies. To date, no disease-modifying drugs have been approved to combat CNS tau-related diseases. The multifactorial etiology of these conditions represents one of the major limits in the discovery of effective therapeutic options. In addition, tau protein functions are orchestrated by diverse post-translational modifications among which phosphorylation mediated by PKs plays a leading role. In this context, conventional single-target therapies are often inadequate in restoring perturbed networks and fraught with adverse side-effects. This thesis reports two distinct approaches to hijack MT defects in neurons. The first is focused on the rational design and synthesis of first-in-class triple inhibitors of GSK-3β, FYN, and DYRK1A, three close-related PKs, which act as master regulators of aberrant tau hyperphosphorylation. A merged multi-target pharmacophore strategy was applied to simultaneously modulate all three targets and achieve a disease-modifying effect. Optimization of ARN25068 by a computationally and crystallographic driven SAR exploration, allowed to rationalize the key structural modifications to maintain a balanced potency against all three targets and develop a new generation of quite well-balanced analogs exhibiting improved physicochemical properties, a good in vitro ADME profile, and promising cell-based anti-tau phosphorylation activity. In Part II, MT-stabilizing compounds have been developed to compensate MT defects in tau-related pathologies. Intensive chemical effort has been devoted to scaling up BL-0884, identified as a promising MT-normalizing TPD, which exhibited favorable ADME-PK, including brain penetration, oral bioavailability, and brain pharmacodynamic activity. A suitable functionalization of the exposed hydroxyl moiety of BL-0884 was carried out to generate corresponding esters and amides possessing a wide range of applications as prodrugs and active targeting for cancer chemotherapy.

Cross-sensors analysis of multispectral Earth observation data for environmental monitoring

Time Series Analysis of multispectral satellite data offers an innovative way to extract valuable information of our changing planet. This is now a real option for scientists thanks to data availability as well as innovative cloud-computing platforms, such as Google Earth Engine. The integration of different missions would mitigate known issues in multispectral time series construction, such as gaps due to clouds or other atmospheric effects. With this purpose, harmonization among Landsat-like missions is possible through statistical analysis. This research offers an overview of the different instruments from Landsat and Sentinel missions (TM, ETM, OLI, OLI-2 and MSI sensors) and products levels (Collection-2 Level-1 and Surface Reflectance for Landsat and Level-1C and Level-2A for Sentinel-2). Moreover, a cross-sensors comparison was performed to assess the interoperability of the sensors on-board Landsat and Sentinel-2 constellations, having in mind a possible combined use for time series analysis. Firstly, more than 20,000 pairs of images almost simultaneously acquired all over Europe were selected over a period of several years. The study performed a cross-comparison analysis on these data, and provided an assessment of the calibration coefficients that can be used to minimize differences in the combined use. Four of the most popular vegetation indexes were selected for the study: NDVI, EVI, SAVI and NDMI. As a result, it is possible to reconstruct a longer and denser harmonized time series since 1984, useful for vegetation monitoring purposes. Secondly, the spectral characteristics of the recent Landsat-9 mission were assessed for a combined use with Landsat-8 and Sentinel-2. A cross-sensor analysis of common bands of more than 3,000 almost simultaneous acquisitions verified a high consistency between datasets. The most relevant discrepancy has been observed in the blue and SWIRS bands, often used in vegetation and water related studies. This analysis was supported with spectroradiometer ground measurements.

Advanced representation of the ocean/sea ice dynamics at high latitudes

Sea ice is a fundamental element of global climate system, with numerous impacts on the polar environment. The ongoing drastic changes in the Earth’s sea ice cover highlight the necessity of monitoring the polar regions and systematically evaluating the quality of different numerical products. The main objective of this thesis is to improve our knowledge of the representation of Arctic and Antarctic sea ice using comprehensive global ocean reanalyses and coupled climate models. The dissertation will explore (i) the Antarctic marginal ice zone (MIZ) and pack ice area in the ensemble mean of four global ocean reanalyses called GREP; (ii) historical representation of the Arctic and Antarctic sea ice state in HighResMIP models; (iii) the future evolution of Arctic sea ice in HighResMIP models. Global ocean reanalyses and GREP are found to adequately capture interannual and seasonal variability in both pack ice and MIZ areas at hemispheric and regional scales. The advantage of the ensemble-mean approach is proved as GREP smooths the strengths and weaknesses of single systems and provides the most consistent and reliable estimates. This work is intended to encourage the use of GREP in a wide range of applications. The analysis of sea ice representation in the coupled climate models shows no systematic impact of the increased horizontal resolution. We argue that a few minor improvements in sea ice representation with the enhanced horizontal resolution are presumably not worth the major effort of costly computations. The thesis highlights the critical importance to distinguish the MIZ from consolidated pack ice both for investigating changes in sea ice distribution and evaluating the product’s performance. Considering that the MIZ is predicted to dominate the Arctic sea ice cover, the model physics parameterizations and sea ice rheology might require modifications. The results of the work can be useful for modelling community.