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Measuring magnetic fields in the inner corona, the interface between the solar chromosphere and outer corona, is of paramount importance if we aim to understand the energetic transformations taking place there, and because it is at the origin of processes that lead to coronal heating, solar wind acceleration, and of most of the phenomena relevant to space weather. However, these measurements are more difficult than mere imaging because polarimetry requires differential photometry. The coronal magnetograph mission (CMAG) has been designed to map the vector magnetic field, line-of-sight velocities, and plane-of-the-sky velocities of the inner corona with unprecedented spatial and temporal resolutions from space. This will be achieved through full vector spectropolarimetric observations using a coronal magnetograph as the sole instrument on board a spacecraft, combined with an external occulter installed on another spacecraft. The two spacecraft will maintain a formation flight distance of 430 m for coronagraphic observations, which requires a 2.5 m occulter disk radius. The mission will be preferentially located at the Lagrangian L5 point, offering a significant advantage for solar physics and space weather research. Existing ground-based instruments face limitations such as atmospheric turbulence, solar scattered light, and long integration times when performing coronal magnetic field measurements. CMAG overcomes these limitations by performing spectropolarimetric measurements from space with an external occulter and high-image stability maintained over time. It achieves the necessary sensitivity and offers a spatial resolution of 2.5″ and a temporal resolution of approximately one minute, in its nominal mode, covering the range from 1.02 solar radii to 2.5 radii. CMAG relies on proven European technologies and can be adapted to enhance any other solar mission, offering potential significant advancements in coronal physics and space weather modeling and monitoring.

A large part of the Web, today, consists of online platforms that allow their users to generate digital content. They include online social networks, multimedia-sharing websites, blogging platforms, and online discussion boards, to name a few examples. Users of those platforms generate content in the form of digital items (e.g. documents, images, or videos), inspect content generated by others, and, finally, interact with each other (e.g. by commenting on each other's generated items). For the social process of information exchange they enable, such platforms are customarily referred to as `social media'. Activity on social media is largely spontaneous and uncoordinated, but it is not random; users choose the discussions they engage in and who they interact with, and their choices and actions reflect what they find important. In this thesis, we define and quantify notions of importance for items, users, and social connections between users, and, based on those definitions, propose efficient algorithms to detect important instances of social media activity. Our description of the algorithms is accompanied with experimental studies that showcase their performance on real datasets in terms of efficiency and effectiveness.

Knowledge of the parameters of rational fertilization leads to increased production, improved product quality, reduced environmental impacts, reduced production costs and satisfaction of global food demand.In this master's thesis, two minerals, clinoptilolite and palygorskite, were used in two concentrations in soil, which in combination with chemical fertilizer aim to create slow-release fertilizers of nutrients. Slow-release fertilizers allow the release (release) of nutrients, seeking the controlled release of soil nutrients. In addition, they provide nutrients to plant roots for a prolonged period of time, thus reducing the possibility of water pollution by avoiding nutrient leakage.The materials used for the execution of this thesis are clinoptilolite (zeolite) from Thracean Zeolite®, palygorskite from GEOHELLAS, soil and liquid fertilizer from the ELGO DIMITRA Institute of Chania. In the initial stage, the minerals and soil were ground to a size below 63 μm, followed by mineralogical analysis by X-ray diffractometry (XRD) and chemical analysis by X-ray fluorescence spectrometry (XRF). In addition, for the minerals and soil, pH, conductivity, granulometric analysis by wet sieving and laser granulometry, as well as measurement of cation exchange capacity with the Kjedahl apparatus were carried out in the Geochemistry laboratory of the Technical University of Crete. The next stage of the experimental procedure included column experiments, in which five different samples were placed: soil, soil with 5 g of palygorskite, soil with 2.5 g of palygorskite, soil with 5 g of zeolite and soil with 2.5 g of zeolite, through which liquid fertilizer diluted with water from the network of the Prefecture of Chania was passed. This experimental procedure simulated fertilization and watering in lettuce cultivation and lasted 14 days. In the lettuce experiment, which lasted 19 days, five different samples were placed in pots: soil, soil with 123 g of palygorskite, soil with 246 g of palygorskite, soil with 123 g of zeolite and soil with 246 g of zeolite, through which diluted liquid fertilizer was passed. Photographic material was collected and surface images of the lettuces were taken, in order to calculate the increase in leaf area in each sample. After the completion of the experiments, the concentrations of potassium, magnesium, phosphorus, copper and zinc were determined by atomic absorption spectrometry-AAS (Perkin Elmer Analyst 100 spectrometer), absorption spectrophotometry (Jenway 7315 spectrometer) and inductively coupled plasma emission spectroscopy (ICP-MS) (Agilent 7500cx ICP-MS spectrometer), which belong to the Geochemistry and Hydrogeochemical Engineering and Soil Remediation laboratories of the Technical University of Crete, respectively.According to the results of the experimental procedure, the use of zeolite and palygorskite contributes to the retention and release of nutrients. The application of 246 and 123 g of palygorskite, as demonstrated by the column experiments and the lettuce experiments, releases significant amounts of magnesium from the palygorskite structure, which probably makes the addition of magnesium to the liquid fertilizer unnecessary. On the contrary, 246 and 123 g of zeolite retain quantities of magnesium, making it available to the lettuce roots. In addition, 246 g of zeolite retains more magnesium compared to 123 g. 246 g of zeolite retains a greater amount of potassium compared to the other tests in both the column experiments and the lettuce experiments. The increase in the concentration of the mineral in the soil, for zeolite and palygorskite, leads to an increase in potassium retention. In the column experiment, the minerals release amounts of copper and zinc, while zinc retention is observed in the last days only for the 246 g zeolite. According to the surface growth data, the 246 g zeolite, the 123 g zeolite and the 123 g palygorskite act as soil conditioners, while the 246 g palygorskite may inhibit growth. Enhancing the concentration of zeolite in lettuce cultivation makes sense, as it acts as a slow-release fertilizer, retaining significant amounts of nutrients, such as magnesium, potassium and phosphorus, for an extended period of time, making them available to the plant roots.

Power-law distributions have been studied as a significant characteristic of non-linear dissipative systems. Since discovering the power-law distribution of solar flares that was later extended to nano-flares and stellar flares, it has been widely accepted that different scales of flares share the same physical process. Here, we present the newly developed Semi-Automated Jet Identification Algorithm (SAJIA) and its application for detecting more than 1200 off-limb solar jets during Solar Cycle 24. Power-law distributions have been revealed between the intensity/energy and frequency of these events, with indices found to be analogous to those for flares and coronal mass ejections (CMEs). These jets are also found to be spatially and temporally modulated by the solar cycle forming a butterfly diagram in their latitudinal-temporal evolution, experiencing quasi-annual oscillations in their analysed properties, and very likely gathering in certain active longitudinal belts. Our results show that coronal jets display the same nonlinear behaviour as that observed in flares and CMEs, in solar and stellar atmospheres, strongly suggesting that they result from the same nonlinear statistics of scale-free processes as their counterparts in different scales of eruptive events. Although these jets, like flares and other large-scale dynamic phenomena, are found to be significantly modulated by the solar cycle, their corresponding power-law indices still remain similar.

The deployment of autonomous navigation systems on ships necessitates accurate motion prediction models tailored to individual vessels. Traditional physics-based models, while grounded in hydrodynamic principles, often fail to account for ship-specific behaviors under real-world conditions. Conversely, purely data-driven models offer specificity but lack interpretability and robustness in edge cases. This study proposes a data-driven physics-based model that integrates physics-based equations with data-driven parameter optimization, leveraging the strengths of both approaches to ensure interpretability and adaptability. The model incorporates physics-based components such as 3-DoF dynamics, rudder, and propeller forces, while parameters such as resistance curve and rudder coefficients are optimized using synthetic data. By embedding domain knowledge into the parameter optimization process, the fitted model maintains physical consistency. Validation of the approach is realized with two container ships by comparing, both qualitatively and quantitatively, predictions against ground-truth trajectories. The results demonstrate significant improvements, in predictive accuracy and reliability, of the data-driven physics-based models over baseline physics-based models tuned with traditional marine engineering practices. The fitted models capture ship-specific behaviors in diverse conditions with their predictions being, 51.6% (ship A) and 57.8% (ship B) more accurate, 72.36% (ship A) and 89.67% (ship B) more consistent.

The maritime industry aims towards a sustainable future, which requires significant improvements in operational efficiency. Current approaches focus on minimising fuel consumption and emissions through greater autonomy. Efficient and safe autonomous navigation requires high-fidelity ship motion models applicable to real-world conditions. Although physics-based ship motion models can predict ships' motion with sub-second resolution, their validation in real-world conditions is rarely found in the literature. This study presents a physics-based 3D dynamics motion model that is tailored to a container-ship, and compares its predictions against real-world voyages. The model integrates vessel motion over time and accounts for its hydrodynamic behavior under different environmental conditions. The model's predictions are evaluated against real vessel data both visually and using multiple distance measures. Both methodologies demonstrate that the model's predictions align closely with the real-world trajectories of the container-ship.

Several studies have documented periodic and quasi-periodic signals from the time series of dMe flare stars and other stellar sources. Such periodic signals, observed within quiescent phases (i.e., devoid of larger-scale microflare or flare activity), range in period from \\(1-1000\\) seconds and hence have been tentatively linked to ubiquitous \\(p\\)-mode oscillations generated in the convective layers of the star. As such, most interpretations for the observed periodicities have been framed in terms of magneto-hydrodynamic wave behavior. However, we propose that a series of continuous nanoflares, based upon a power-law distribution, can provide a similar periodic signal in the associated time series. Adapting previous statistical analyses of solar nanoflare signals, we find the first statistical evidence for stellar nanoflare signals embedded within the noise envelope of M-type stellar lightcurves. Employing data collected by the Next Generation Transit Survey (NGTS), we find evidence for stellar nanoflare activity demonstrating a flaring power-law index of \\(3.25 \\pm 0.20 \\), alongside a decay timescale of \\(200 \\pm 100\\) s. We also find that synthetic time series, consistent with the observations of dMe flare star lightcurves, are capable of producing quasi-periodic signals in the same frequency range as \\(p\\)-mode signals, despite being purely comprised of impulsive signatures. Phenomena traditionally considered a consequence of wave behaviour may be described by a number of high frequency but discrete nanoflare energy events. This new physical interpretation presents a novel diagnostic capability, by linking observed periodic signals to given nanoflare model conditions.

We perform NLTE inversions in a large set of umbral flashes, including the dark fibrils visible within them, and in the quiescent umbra by using the inversion code NICOLE on a set of full Stokes high-resolution Ca II 8542 A observations of a sunspot at disk center. We find that the dark structures have Stokes profiles that are distinct from those of the quiescent and flashed regions. They are best reproduced by atmospheres that are more similar to the flashed atmosphere in terms of velocities, even if with reduced amplitudes. We also find two sets of solutions that finely fit the flashed profiles: a set that is upflowing, featuring a transition region that is deeper than in the quiescent case and preceded by a slight dip in temperature, and a second solution with a hotter atmosphere in the chromosphere but featuring downflows close to the speed of sound at such heights. Such downflows may be related, or even dependent, on the presence of coronal loops, rooted in the umbra of sunspots, as is the case in the region analyzed. Similar loops have been recently observed to have supersonic downflows in the transition region and are consistent with the earlier \"sunspot plumes\" which were invariably found to display strong downflows in sunspots. Finally we find, on average, a magnetic field reduction in the flashed areas, suggesting that the shock pressure is moving field lines in the upper layers.