Detection and Modeling of Boundary Layer Height

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

Detection and localization of GLUTs in spermatozoa from different domestic species

Sperm cells need hexoses as a substrate for their function, for both the maintenance of membrane homeostasis and the movement of the tail. These cells have a peculiar metabolism that has not yet been fully understood, but it is clear that they obtain energy from hexoses through glycolisis and/or oxidative phosphorylation. Spermatozoa are in contact with different external environments, beginning from the testicular and epididymal fluid, passing to the seminal plasma and finally to the female genital tract fluids; in addition, with the spread of reproductive biotechnologies, sperm cells are diluted and stored in various media, containing different energetic substrates. To utilize these energetic sources, sperm cells, as other eukaryotic cells, have a well-constructed protein system, that is mainly represented by the GLUT family proteins. These transporters have a membrane-spanning α-helix structure and work as an enzymatic pump that permit a fast gradient dependent passage of sugar molecules through the lipidic bilayer of sperm membrane. Many GLUTs have been studied in man, bull and rat spermatozoa; the presence of some GLUTs has been also demonstrated in boar and dog spermatozoa. The aims of the present study were - to determine the presence of GLUTs 1, 2, 3, 4 and 5 in boar, horse, dog and donkey spermatozoa and to describe their localization; - to study eventual changes in GLUTs location after capacitation and acrosome reaction in boar, stallion and dog spermatozoa; - to determine possible changes in GLUTs localization after capacitation induced by insulin and IGF stimulation in boar spermatozoa; - to evaluate changes in GLUTs localization after flow-cytometric sex sorting in boar sperm cells. GLUTs 1, 2, 3 and 5 presence and localization have been demonstrated in boar, stallion, dog and donkey spermatozoa by western blotting and immunofluorescence analysis; a relocation in GLUTs after capacitation has been observed only in dog sperm cells, while no changes have been observed in the other species examined. As for boar, the stimulation of the capacitation with insulin and IGF didn’t cause any change in GLUTs localization, as well as for the flow cytometric sorting procedure. In conclusion, this study confirms the presence of GLUTs 1, 2 ,3 and 5 in boar, dog, stallion and donkey spermatozoa, while GLUT 4 seems to be absent, as a confirmation of other studies. Only in dog sperm cells capacitating conditions induce a change in GLUTs distribution, even if the physiological role of these changes should be deepened.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Detection and molecular characterization of viruses infecting Actinidia spp.

Kiwifruit (genus Actinidia) is an important horticultural crop grown in the temperate regions. The four world’s largest producers are China, Italy, New Zealand and Chile. More than 50 species are recognized in the genus but the principal species in cultivation are A. deliciosa and A. chinensis. In Italy, as well as in many other countries, the kiwifruit crop has been considered to be relatively disease free and then no certification system for this species has been developed to regulate importation of propagation plant material in the European Union. During the last years a number of fungal and bacterial diseases have been recorded such as Botrytis cinerea and Pseudomonas syringae pv. actinidiae. Since 2003, several viruses and virus-like diseases have been identified and more recent studies demonstrated that Actinidia spp can be infected by a wide range of viral agents. In collaboration with the University of Auckland we have been detected thirteen different viral species on kiwifruit plants. During the three years of my PhD I worked on the characterization of Cucumber mosaic virus (CMV) and Pelargonium zonate spot virus (PZSV). The determination of causal agents has been based on host range, symptom expression in the test plant species and morphological properties of the virus particles using transmission electron microscopy (TEM) and using specific oligonucleotide primers in reverse transcription-polymerase chain reaction (RT-PCR). Both viruses induced several symptoms on kiwifruit plants. Moreover with new technologies such as high-throughput sequencing we detected additional viruses, a new member of the family Closteroviridae and a new member of the family Totiviridae. Taking together all results of my studies it is clear that, in order to minimize the risk of serious viral disease in kiwifruit, it is vital to use virus-free propagation material in order to prevent the spread of these viruses.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

Light energy management in peach: utilization, photoprotection , photodamage and recovery. Maximizing light absorption in orchard is not always the best solution

The relation between the intercepted light and orchard productivity was considered linear, although this dependence seems to be more subordinate to planting system rather than light intensity. At whole plant level not always the increase of irradiance determines productivity improvement. One of the reasons can be the plant intrinsic un-efficiency in using energy. Generally in full light only the 5 – 10% of the total incoming energy is allocated to net photosynthesis. Therefore preserving or improving this efficiency becomes pivotal for scientist and fruit growers. Even tough a conspicuous energy amount is reflected or transmitted, plants can not avoid to absorb photons in excess. The chlorophyll over-excitation promotes the reactive species production increasing the photoinhibition risks. The dangerous consequences of photoinhibition forced plants to evolve a complex and multilevel machine able to dissipate the energy excess quenching heat (Non Photochemical Quenching), moving electrons (water-water cycle , cyclic transport around PSI, glutathione-ascorbate cycle and photorespiration) and scavenging the generated reactive species. The price plants must pay for this equipment is the use of CO2 and reducing power with a consequent decrease of the photosynthetic efficiency, both because some photons are not used for carboxylation and an effective CO2 and reducing power loss occurs. Net photosynthesis increases with light until the saturation point, additional PPFD doesn’t improve carboxylation but it rises the efficiency of the alternative pathways in energy dissipation but also ROS production and photoinhibition risks. The wide photo-protective apparatus, although is not able to cope with the excessive incoming energy, therefore photodamage occurs. Each event increasing the photon pressure and/or decreasing the efficiency of the described photo-protective mechanisms (i.e. thermal stress, water and nutritional deficiency) can emphasize the photoinhibition. Likely in nature a small amount of not damaged photosystems is found because of the effective, efficient and energy consuming recovery system. Since the damaged PSII is quickly repaired with energy expense, it would be interesting to investigate how much PSII recovery costs to plant productivity. This PhD. dissertation purposes to improve the knowledge about the several strategies accomplished for managing the incoming energy and the light excess implication on photo-damage in peach. The thesis is organized in three scientific units. In the first section a new rapid, non-intrusive, whole tissue and universal technique for functional PSII determination was implemented and validated on different kinds of plants as C3 and C4 species, woody and herbaceous plants, wild type and Chlorophyll b-less mutant and monocot and dicot plants. In the second unit, using a “singular” experimental orchard named “Asymmetric orchard”, the relation between light environment and photosynthetic performance, water use and photoinhibition was investigated in peach at whole plant level, furthermore the effect of photon pressure variation on energy management was considered on single leaf. In the third section the quenching analysis method suggested by Kornyeyev and Hendrickson (2007) was validate on peach. Afterwards it was applied in the field where the influence of moderate light and water reduction on peach photosynthetic performances, water requirements, energy management and photoinhibition was studied. Using solar energy as fuel for life plant is intrinsically suicidal since the high constant photodamage risk. This dissertation would try to highlight the complex relation existing between plant, in particular peach, and light analysing the principal strategies plants developed to manage the incoming light for deriving the maximal benefits as possible minimizing the risks. In the first instance the new method proposed for functional PSII determination based on P700 redox kinetics seems to be a valid, non intrusive, universal and field-applicable technique, even because it is able to measure in deep the whole leaf tissue rather than the first leaf layers as fluorescence. Fluorescence Fv/Fm parameter gives a good estimate of functional PSII but only when data obtained by ad-axial and ab-axial leaf surface are averaged. In addition to this method the energy quenching analysis proposed by Kornyeyev and Hendrickson (2007), combined with the photosynthesis model proposed by von Caemmerer (2000) is a forceful tool to analyse and study, even in the field, the relation between plant and environmental factors such as water, temperature but first of all light. “Asymmetric” training system is a good way to study light energy, photosynthetic performance and water use relations in the field. At whole plant level net carboxylation increases with PPFD reaching a saturating point. Light excess rather than improve photosynthesis may emphasize water and thermal stress leading to stomatal limitation. Furthermore too much light does not promote net carboxylation improvement but PSII damage, in fact in the most light exposed plants about 50-60% of the total PSII is inactivated. At single leaf level, net carboxylation increases till saturation point (1000 – 1200 μmolm-2s-1) and light excess is dissipated by non photochemical quenching and non net carboxylative transports. The latter follows a quite similar pattern of Pn/PPFD curve reaching the saturation point at almost the same photon flux density. At middle-low irradiance NPQ seems to be lumen pH limited because the incoming photon pressure is not enough to generate the optimum lumen pH for violaxanthin de-epoxidase (VDE) full activation. Peach leaves try to cope with the light excess increasing the non net carboxylative transports. While PPFD rises the xanthophyll cycle is more and more activated and the rate of non net carboxylative transports is reduced. Some of these alternative transports, such as the water-water cycle, the cyclic transport around the PSI and the glutathione-ascorbate cycle are able to generate additional H+ in lumen in order to support the VDE activation when light can be limiting. Moreover the alternative transports seems to be involved as an important dissipative way when high temperature and sub-optimal conductance emphasize the photoinhibition risks. In peach, a moderate water and light reduction does not determine net carboxylation decrease but, diminishing the incoming light and the environmental evapo-transpiration request, stomatal conductance decreases, improving water use efficiency. Therefore lowering light intensity till not limiting levels, water could be saved not compromising net photosynthesis. The quenching analysis is able to partition absorbed energy in the several utilization, photoprotection and photo-oxidation pathways. When recovery is permitted only few PSII remained un-repaired, although more net PSII damage is recorded in plants placed in full light. Even in this experiment, in over saturating light the main dissipation pathway is the non photochemical quenching; at middle-low irradiance it seems to be pH limited and other transports, such as photorespiration and alternative transports, are used to support photoprotection and to contribute for creating the optimal trans-thylakoidal ΔpH for violaxanthin de-epoxidase. These alternative pathways become the main quenching mechanisms at very low light environment. Another aspect pointed out by this study is the role of NPQ as dissipative pathway when conductance becomes severely limiting. The evidence that in nature a small amount of damaged PSII is seen indicates the presence of an effective and efficient recovery mechanism that masks the real photodamage occurring during the day. At single leaf level, when repair is not allowed leaves in full light are two fold more photoinhibited than the shaded ones. Therefore light in excess of the photosynthetic optima does not promote net carboxylation but increases water loss and PSII damage. The more is photoinhibition the more must be the photosystems to be repaired and consequently the energy and dry matter to allocate in this essential activity. Since above the saturation point net photosynthesis is constant while photoinhibition increases it would be interesting to investigate how photodamage costs in terms of tree productivity. An other aspect of pivotal importance to be further widened is the combined influence of light and other environmental parameters, like water status, temperature and nutrition on peach light, water and phtosyntate management.

Development of oil spill detection techniques for satellite optical sensors and their application to monitor oil spill discharge in Mediterranean sea

Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

Nanotechnology control of self organized biomolecules and biomaterials for medical research

Nanotechnology entails the manufacturing and manipulation of matter at length scales ranging from single atoms to micron-sized objects. The ability to address properties on the biologically-relevant nanometer scale has made nanotechnology attractive for Nanomedicine. This is perceived as a great opportunity in healthcare especially in diagnostics, therapeutics and more in general to develop personalized medicine. Nanomedicine has the potential to enable early detection and prevention, and to improve diagnosis, mass screening, treatment and follow-up of many diseases. From the biological standpoint, nanomaterials match the typical size of naturally occurring functional units or components of living organisms and, for this reason, enable more effective interaction with biological systems. Nanomaterials have the potential to influence the functionality and cell fate in the regeneration of organs and tissues. To this aim, nanotechnology provides an arsenal of techniques for intervening, fabricate, and modulate the environment where cells live and function. Unconventional micro- and nano-fabrication techniques allow patterning biomolecules and biocompatible materials down to the level of a few nanometer feature size. Patterning is not simply a deterministic placement of a material; in a more extended acception it allows a controlled fabrication of structures and gradients of different nature. Gradients are emerging as one of the key factors guiding cell adhesion, proliferation, migration and even differentiation in the case of stem cells. The main goal of this thesis has been to devise a nanotechnology-based strategy and tools to spatially and temporally control biologically-relevant phenomena in-vitro which are important in some fields of medical research.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system

Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.

Synthesis of constrained peptidomimetics for therapeutic, diagnostic and theranostic applications

This thesis work deals, principally, with the development of different chemical protocols ranging from environmental sustainability peptide synthesis to asymmetric synthesis of modified tryptophans to a series of straightforward procedures for constraining peptide backbones without the need for a pre-formed scaffold. Much efforts have been dedicated to the structural analysis in a biomimetic environment, fundamental for predicting the in vivo conformation of compounds, as well as for giving a rationale to the experimentally determined bioactivity. The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, titration experiments, molecular dynamics, etc.), FT-IR and ECD spectroscopy. As a practical application, 3D rigid scaffolds have been employed for the synthesis of biological active compounds based on peptidomimetic and retro-mimetic structures. These mimics have been investigated for their potential as antiflammatory agents and actually the results obtained are very promising. Moreover, the synthesis of Amo ring permitted the development of an alternative high effective synthetic pathway for obtaining Linezolid antibiotic. The final section is, instead, dedicated to the construction of a new biosensor based on zeolite L SAMs functionalized with the integrin ligand c[RGDfK], that has showed high efficiency for the selective detection of tumor cells. Such kind of sensor could, in fact, enable the convenient, non-invasive detection and diagnosis of cancer in early stages, from a few drops of a patient's blood or other biological fluids. In conclusion, the researches described herein demonstrate that the peptidomimetic approach to 3D definite structures, allows unambiguous investigation of the structure-activity relationships, giving an access to a wide range bioactive compounds of pharmaceutical interest to use not only as potential drugs but also for diagnostic and theranostic applications.

Development of thermochemiluminescence-based sensitive probes: synthesis, optimization, and characterization of c2- and c7-substituted acridine-containing 1,2-dioxetanes

After initial efforts in the late 1980s, the interest in thermochemiluminescence (TCL) as an effective detection technique has gradually faded due to some drawbacks, such as the high temperatures required to trigger the light emission and the relatively low intensities, which determined a poor sensitivity. Recent advances made with the adoption of variably functionalized 1,2-dioxetanes as innovative luminophores, have proved to be a promising approach for the development of reagentless and ultrasensitive detection methods exploitable in biosensors by using TCL compounds as labels, as either single molecules or included in modified nanoparticles. In this PhD Thesis, a novel class of N-substituted acridine-containing 1,2-dioxetanes was designed, synthesized, and characterized as universal TCL probes endowed with optimal emission-triggering temperatures and higher detectability particularly useful in bioanalytical assays. The different decorations introduced by the insertion of both electron donating (EDGs) and electron withdrawing groups (EWGs) at the 2- and 7-positions of acridine fluorophore was found to profoundly affect the photophysical properties and the activation parameters of the final 1,2-dioxetane products. Challenges in the synthesis of 1,2-dioxetanes were tackled with the recourse to continuous flow photochemistry to achieve the target parent compound in high yields, short reaction time, and easy scalability. Computational studies were also carried out to predict the olefins reactivity in the crucial photooxygenation reaction as well as the final products stability. The preliminary application of TCL prototype molecule has been performed in HaCaT cell lines showing the ability of these molecules to be detected in real biological samples and cell-based assays. Finally, attempts on the characterization of 1,2-dioxetanes in different environments (solid state, optical glue and nanosystems) and the development of bioconjugated TCL probes will be also presented and discussed.