10081 research outputs found
Sort by
Data-driven and data-oriented methods for materials science and technologies
Get PDFThe discovery of new materials and their functions has always been a fundamental component of technological progress. Nowadays, the quest for new materials is stronger than ever: sustainability, medicine, robotics and electronics are all key assets which depend on the ability to create specifically tailored materials.
However, designing materials with desired properties is a difficult task, and the complexity of the discipline makes it difficult to identify general criteria. While scientists developed a set of best practices (often based on experience and expertise), this is still a trial-and-error process.
This becomes even more complex when dealing with advanced functional materials. Their properties depend on structural and morphological features, which in turn depend on fabrication procedures and environment, and subtle alterations leads to dramatically different results.
Because of this, materials modeling and design is one of the most prolific research fields. Many techniques and instruments are continuously developed to enable new possibilities, both in the experimental and computational realms. Scientists strive to enforce cutting-edge technologies in order to make progress. However, the field is strongly affected by unorganized file management, proliferation of custom data formats and storage procedures, both in experimental and computational research. Results are difficult to find, interpret and re-use, and a huge amount of time is spent interpreting and re-organizing data. This also strongly limit the application of data-driven and machine learning techniques.
This work introduces possible solutions to the problems described above. Specifically, it talks about developing features for specific classes of advanced materials and use them to train machine learning models and accelerate computational predictions for molecular compounds; developing method for organizing non homogeneous materials data; automate the process of using devices simulations to train machine learning models; dealing with scattered experimental data and use them to discover new patterns
Integrating structural variant calling, annotation and prioritization into whole genome analysis workflows: a practical application in the molecular diagnosis of neurodevelopmental disorders
Get PDFBackground: WGS is increasingly used as a first-line diagnostic test for patients with rare genetic diseases such as neurodevelopmental disorders (NDD). Clinical applications require a robust infrastructure to support processing, storage and analysis of WGS data. The identification and interpretation of SVs from WGS data also needs to be improved. Finally, there is a need for a prioritization system that enables downstream clinical analysis and facilitates data interpretation. Here, we present the results of a clinical application of WGS in a cohort of patients with NDD.
Methods: We developed highly portable workflows for processing WGS data, including alignment, quality control, and variant calling of SNVs and SVs. A benchmark analysis of state-of-the-art SV detection tools was performed to select the most accurate combination for SV calling. A gene-based prioritization system was also implemented to support variant interpretation.
Results: Using a benchmark analysis, we selected the most accurate combination of tools to improve SV detection from WGS data and build a dedicated pipeline. Our workflows were used to process WGS data from 77 NDD patient-parent families. The prioritization system supported downstream analysis and enabled molecular diagnosis in 32% of patients, 25% of which were SVs and suggested a potential diagnosis in 20% of patients, requiring further investigation to achieve diagnostic certainty.
Conclusion: Our data suggest that the integration of SNVs and SVs is a main factor that increases diagnostic yield by WGS and show that the adoption of a dedicated pipeline improves the process of variant detection and interpretation
Paper Nature: the Epistolary of Ulisse Aldrovandi (1522-1605)
Get PDFQuesto lavoro intende offrire una prima panoramica generale del carteggio di Ulisse Aldrovandi (1522-1605), contenuto prevalentemente presso il Fondo Aldrovandi della Biblioteca Universitaria di Bologna. Lo studioso di storia naturale bolognese aveva infatti scambiato oltre 2.100 lettere con corrispondenti provenienti da zone anche geograficamente remote. Del totale complessivo di queste lettere, solo poche sono state pubblicate, mentre una percentuale significativa di lettere rimane ancora oggi inedita. La presente ricerca non ha tuttavia come obiettivo l’edizione delle lettere, ma uno studio analitico delle funzioni e delle caratteristiche preminenti di questa corrispondenza esaminata nella sua totalità.This work intends to offer an initial general overview of the correspondence of Ulisse Aldrovandi (1522-1605), mainly contained in the Fondo Aldrovandi of the University Library of Bologna. The Bolognese natural history scholar had in fact exchanged over 2,100 letters with correspondents from even geographically remote areas. Of the overall total of these letters, only a few have been published, while a significant percentage of letters remain unpublished to this day. However, the aim of the present research is not the edition of the letters, but an analytical study of the pre-eminent functions and characteristics of this correspondence examined in its entirety
Agroecological management of insect pests on sugarbeets and lettuce cultivated in organic farming
Get PDFTwo-year field trials were conducted in northern Italy with the aim of developing a trapcrop-based agroecological approach for the control of flea beetles (Chaetocnema tibialis (Illiger), Phyllotreta spp. (Chevrolat) (Coleoptera: Chrysomelidae)) and Lygus rugulipennis Poppius (Hemiptera: Miridae), key pests of sugar beet and lettuce, respectively.
Flea beetle damage trials compared a trap cropping treatment, i.e., a sugar beet plot with a border of Sinapis alba (L.) and Brassica juncea (L.) with a control treatment, i.e., a sugar beet plot with bare soil as field border. Sugar beets grown near trap crops showed a significant decrease (≈40%) in flea beetle damage compared to control. Moreover, flea beetle damage varied with distance from the edge of the trap plants, being highest at 2 m from the edge, then decreasing at higher distances.
Regarding L. rugulipennis on lettuce two experiments were conducted. A semiochemical-assisted trap cropping trial was supported by another test evaluating the efficacy of pheromones and trap placement. In this trial, it was found that pheromone baited traps caught significantly more specimens of L. rugulipennis than unbaited traps. It was also found that traps placed at ground level produced larger catches than traps placed at the height of 70 cm. In the semiochemical-assisted trap cropping experiment, a treatment where lettuce was grown next to two Alfa-Alfa borders containing pheromone baited traps was compared with a control treatment, where lettuce was grown near bare soil. This experiment showed that the above-mentioned strategy managed to reduce L. rugulipennis damage to lettuce by ≈30%.
From these studies, it appears that trap crop-based strategy, alone or with baited traps, made it possible to reduce crop damage to economically acceptable levels and to minimize the need for insecticide treatments, showing that those strategy could be implemented in organic farming as a means of controlling insect pests
Unlocking ecological history using fish remains: Eco-evolutionary consequences of exploitation in the Atlantic bluefin tuna
Get PDFDuring recent decades, the health of ocean ecosystems and fish populations has been threatened by overexploitation, pollution, and anthropogenic-driven climate change. Due to a lack of long-term data, we have a poor understanding of when intensive exploitation began and what impact anthropogenic activities have had on the ecology and evolution of fishes. Such information is crucial to recover degraded and depleted marine ecosystems and fish populations, maximise their productivity in-line with historical levels, and predict their future dynamics. In this thesis, I evaluate anthropogenic impacts on the iconic Atlantic bluefin tuna (Thunnus thynnus; BFT), one of the longest and recently most intensely exploited marine fishes, with a tremendous cultural and economic importance. Using a long-time series of archaeological and archived faunal remains (bones) dating back to approximately two millennia ago, I apply morphological, isotopic, and genomic techniques to perform the first studies on long-term BFT size and growth, diet and habitat use, and demography and adaptation, and produce the first genome-wide data on this species. My findings suggest that exploitation had impacted BFT foraging behaviour by the ~16th century when coastal ecosystem degradation induced a pelagic shift in diet and habitat use. I reveal that BFT biomass began to decline much earlier than hitherto documented, by the 19th century, consistent with intensive tuna trap catches during this period and catch-at-size increasing. I find that BFT juvenile growth had increased by the early 1900s (and more dramatically by the 21st century) which may reflect an evolutionary response to size selective harvest–which I find putative genomic signatures of. Further, I observed that BFT foraging behaviours have been modified following overexploitation during the 20th century, which previously included a isotopically distinct, Black Sea niche. Finally, I show that despite biomass declining from centuries ago, BFT has retained genomic diversity
Strategies for lowering the environmental impact of different electrochemical energy storage system
Get PDFThe continuous growth of global population brings an exponential increase on energy consumption and greenhouse gas emission in the atmosphere contributing to the increase of the planet temperature. Therefore, it is mandatory to adopt renewable energy production systems like photovoltaic or wind power: unfortunately, the main limit of these technologies is the natural intermittence of the energy sources that limits their applicability. The key enabling technology for a widespread usage of clean power sources are electrochemical energy storage systems, most commonly known as batteries. Batteries will enable the storage of energy during overproduction period and the release during low production period stabilizing the power outcome, allowing the connection to the main grid and increasing the applicability of renewable energy sources. Despite the high number of benefits that the widespread use of batteries will bring, starting from the reduction of CO2 emitted in the atmosphere, it is necessary also to take care of the environmental impact of processes and materials used for the production of electrochemical storage systems. In addition, there are many different battery systems, with different chemistries and designs that require specific strategies. Nowadays, the most part of the materials and chemicals used for battery production are toxic for humans and the environment. For this reason, this Ph.D. thesis addresses the challenging scope of lowering the environmental impact of manufacturing processes of different electrochemical energy storage systems using natural derived or low carbon footprint materials while increasing the performances with respect to commercial devices. The activities carried out during my Ph.D. cover a high number of different electrochemical storage systems involving a wide range of electrochemical processes from capacitive to faradic. New materials, different production processes and new battery design, all in view of sustainability and low environmental impact, increased the innovative and challenging aspects of this work
A glassful of graphene: graphene-based materials for drinking water remediation
Get PDFModern world suffers from an intense water crisis. Emerging contaminants represent one of the most concerning elements of this issue. Substances, molecules, ions, and microorganisms take part in this vast and variegated class of pollutants, which main characteristic is to be highly resistant to traditional water purification technologies. An intense international research effort is being carried out in order to find new and innovative solutions to this problem, and graphene-based materials are one of the most promising options.
Graphene oxide (GO) is a nanostructured material where domains populated by oxygenated groups alternate with interconnected areas of sp2 hybridized carbon atoms, on the surface of a one-atom thick nanosheets. GO can adsorb a great number of molecules and ions on its surface, thanks to the variety of different interactions that it can express, such as hydrogen bonding, p-p stacking, and electrostatic and hydrophobic interaction. These characteristics, added to the high superficial area, make it an optimal material for the development of innovative materials for drinking water remediation.
The main concern in the use of GO in this field is to avoid secondary contaminations (i.e. GO itself must not become a pollutant). This issue can be faced through the immobilization of GO onto polymeric substrates, thus developing composite materials. The use of micro/ultrafiltration polymeric hollow fibers as substrates allows the design of adsorptive membranes, meaning devices that can perform filtration and adsorption simultaneously.
In this thesis, two strategies for the development of adsorptive membranes were investigated: a core-shell strategy, where hollow fibers are coated with GO, and a coextrusion strategy, where GO is embedded in the polymeric matrix of the fibers. The so-obtained devices were exploited for both fundamental studies (i.e. molecular and ionic behaviour in between GO nanosheets) and real applications (the coextruded material is now at TRL 9)
Study of materials and interphases for electrochemical energy storage from renewable sources
Get PDFBatteries should be refined depending on their application for a future in which the sustainable energy demand increases. On the one hand, it is fundamental to improve their safety, prevent failures, increase energy density, and reduce production costs. On the other hand, new battery materials and architecture are required to satisfy the growing demand.
This thesis explores different electrochemical energy storage systems and new methodologies to investigate complex and dynamic processes.
Lithium-ion batteries are described in all their cell components. In these systems, this thesis investigates negative electrodes. Both the development of new sustainable materials and new in situ electrode characterization methods were explored. One strategy to achieve high-energy systems is employing lithium metal anodes. In this framework, ammonium hexafluorophosphate is demonstrated to be a suitable additive for stabilizing the interphase and preventing uncontrolled dendritic deposition. Deposition/stripping cycles, electrochemical impedance spectroscopy, in situ optical microscopy, and operando confocal Raman spectroscopy have been used to study lithium metal-electrolyte interphase in the presence of the additive.
Redox Flow Batteries (RFBs) are proposed as a sustainable alternative for stationary applications. An all-copper aqueous RFB (CuRFB) has been studied in all its aspects. For the electrolyte optimization, spectro-electrochemical tests in diluted solution have been used to get information on the electrolyte’s electrochemical behaviour with different copper complexes distributions. In concentrated solutions, the effects of copper-to-ligand ratios, the concentration, and the counter-ion of the complexing agent were evaluated.
Electrode thermal treatment was optimized, finding a compromise between the electrochemical performance and the carbon footprint. On the membrane side, a new method for permeability studies was designed using scanning electrochemical microscopy (SECM). The Cu(II) permeability of several membranes was tested, obtaining direct visualization of Cu(II) concentration in space. Also, two spectrophotometric approaches were designed for SoC monitoring systems for negative and positive half-cells
Neurogeometry of reaching
Get PDFThe purpose of the thesis is to develop a model for the functional behaviour of neurons in the primary motor cortex (M1) responsible for arm reaching movements.
From Georgopoulos neurophysiological data, we provide a first bundle structure compatible with the hypercolumnar organization and with the position-direction selectivity of motor cortical cells. We then extend this model to encode the direction of arm movement which varies in time, as experimentally measured by Hatsopoulos by introducing the notion of movement fragments. We provide a sub-Riemannian model which describes the time-dependent directional selectivity of cells though integral curves of the geometric structure we set up. The sub-Riemannian distance we define allows to implement a grouping algorithm able to detect a set of hand motor trajectories. These paths, identified by using a kernel defined in terms of kinematic variables, are compatible with the motor primitives obtained from neurophysiological results by spectral analysis applied directly on cortical variables.
In a second part of the work, we propose geodesics in this space as an alternative model of models for arm movement trajectories. We define a special class of curves, called admissible, on which to study the geodesics problem: we provide a connectivity property in terms of admissible paths and the existence of normal length minimizers. Admissible geodesics are used as a model of reaching paths, finding a first validation through Flash and Hogan minimizing trajectories
Strategies to hijack MTs dysfunction in neurodegenerative tauopathies: Design and synthesis of novel CNS-disease-modifying tools
Get PDFNeuronal 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