Development of metabotropic glutamate receptors from trigeminal nuclei to barrel cortex in postnatal mouse

Expression patterns of group I (mGluR1α and mGluR5)and group II (mGluR2/3) metabotropic glutamate receptor subtypes were examined immunocytochemically in the trigeminal system of mice during the first 3 weeks of postnatal development, when somatotopic whisker representations are sequentially established from brainstem through thalamus to cerebral cortex. Immunostaining for all three epitopes formed whisker-related patterns in the trigeminal nuclei from postnatal day (P) 0, in the ventral posterior thalamic nucleus from P2, and in the posteromedial barrel subfield of somatosensory cortex (SI) from P4. The appearance of whisker-related patterns was preceded by increased levels of immunostaining of the neuropil, which subsequently declined from the trigeminal nuclei upward. In SI, mGluR1α-positive neurons were observed in all cortical layers from P2. mGluR5 was localized in neurons, glial cells, and neuropil from P2. mGluR2/3 immunostaining was distributed only in the neuropil at all ages. The three receptor subtypes showed moderate to high expression in deep layer V throughout development. Transient expression peaked in the hollows of layer IV barrels from P4 to P9, and then fell off as expression increased in supragranular layers from P14 to P21. The deep aspect of the cortical subplate (layer VIb) showed dense mGluR5 and less dense mGluR1α immunostaining throughout development. Up-regulation of expression of group I and II mGluRs is correlated with the growth and refinement of connectivity and the establishment of somatotopic patterns in the three main relay stations of the trigeminal system. This finding suggests roles for mGluRs in the early processing of sensory information and in developmental plasticity.

Essays in Economic Geography and Long-Term Development

This dissertation has two main themes: first, the economic impact of tourism on cities and, secondly, the determinants of European long-run development, with a focus on the pre-Industrial era. The common thread is the attempt to develop economic geography models that incorporate spatial frictions and are liable to be given empirical content. Chapter 1, written in conjunction with G. Alfredo Minerva, provides an empirical analysis of the relationship between tourism and economic activity across Italian municipalities, and lays down the basic elements of an urban theory of tourism in an a-spatial setting. Chapter 2 extends these ideas to a quantitative urban framework to study the economic impact and the welfare consequences of tourism into the city of Venice. The model is given empirical content thanks to a large collection of data at the Census tract level for the Municipality of Venice, and then used to perform counterfactual policty analysis. In chapter 3, with Matteo Santacesaria, we consider a setting where agents are continuously distributed over a two-dimensional heterogeneous geography, and are allowed to do business at a finite set of markets. We study the equilibrium partition of the economic space into a collection of mutually-exclusive market areas, and provide condition for this equilibrium partition to exist and to be unique. Finally, chapter 4 "The rise of (urban) Europe: a Quantitative-Spatial analysis", co-authored with Matteo Cervellati and Alex Lehner, sets up a quantitative economic geography model to understand the roots of the Industrial Revolution, in an attempt to match the evolution of the European urban network, and the corresponding city-size distribution, over the period A.D. 1000-1850. It highlights the importance of agricultural trade across cities for the emergence of large manufacturing hubs.

A distributed middleware for IT/OT convergence in modern industrial environments

The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition. The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support. We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers.

Serverless middlewares to integrate heterogeneous and distributed services in cloud continuum environments

The application of modern ICT technologies is radically changing many fields pushing toward more open and dynamic value chains fostering the cooperation and integration of many connected partners, sensors, and devices. As a valuable example, the emerging Smart Tourism field derived from the application of ICT to Tourism so to create richer and more integrated experiences, making them more accessible and sustainable. From a technological viewpoint, a recurring challenge in these decentralized environments is the integration of heterogeneous services and data spanning multiple administrative domains, each possibly applying different security/privacy policies, device and process control mechanisms, service access, and provisioning schemes, etc. The distribution and heterogeneity of those sources exacerbate the complexity in the development of integrating solutions with consequent high effort and costs for partners seeking them. Taking a step towards addressing these issues, we propose APERTO, a decentralized and distributed architecture that aims at facilitating the blending of data and services. At its core, APERTO relies on APERTO FaaS, a Serverless platform allowing fast prototyping of the business logic, lowering the barrier of entry and development costs to newcomers, (zero) fine-grained scaling of resources servicing end-users, and reduced management overhead. APERTO FaaS infrastructure is based on asynchronous and transparent communications between the components of the architecture, allowing the development of optimized solutions that exploit the peculiarities of distributed and heterogeneous environments. In particular, APERTO addresses the provisioning of scalable and cost-efficient mechanisms targeting: i) function composition allowing the definition of complex workloads from simple, ready-to-use functions, enabling smarter management of complex tasks and improved multiplexing capabilities; ii) the creation of end-to-end differentiated QoS slices minimizing interfaces among application/service running on a shared infrastructure; i) an abstraction providing uniform and optimized access to heterogeneous data sources, iv) a decentralized approach for the verification of access rights to resources.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.

A Distributed Support based on Kubeflow to Ease MLOps of Federated Learning Algorithms

The main objective of my thesis work is to exploit the Google native and open-source platform Kubeflow, specifically using Kubeflow pipelines, to execute a Federated Learning scalable ML process in a 5G-like and simplified test architecture hosting a Kubernetes cluster and apply the largely adopted FedAVG algorithm and FedProx its optimization empowered by the ML platform ‘s abilities to ease the development and production cycle of this specific FL process. FL algorithms are more are and more promising and adopted both in Cloud application development and 5G communication enhancement through data coming from the monitoring of the underlying telco infrastructure and execution of training and data aggregation at edge nodes to optimize the global model of the algorithm ( that could be used for example for resource provisioning to reach an agreed QoS for the underlying network slice) and after a study and a research over the available papers and scientific articles related to FL with the help of the CTTC that suggests me to study and use Kubeflow to bear the algorithm we found out that this approach for the whole FL cycle deployment was not documented and may be interesting to investigate more in depth. This study may lead to prove the efficiency of the Kubeflow platform itself for this need of development of new FL algorithms that will support new Applications and especially test the FedAVG algorithm performances in a simulated client to cloud communication using a MNIST dataset for FL as benchmark.

Development and testing of a virtual energy meter using the Labview Environment

The quantity of electric energy utilized by a home, a business, or an electrically powered device is measured by an electricity meter, also known as an electric meter, electrical meter, or energy meter. Electric meters located at customers' locations are used by electric providers for billing. They are usually calibrated in billing units, with the kilowatt hour being the most popular (kWh). Typically, they are read once each billing cycle. When energy savings are sought during specific times, some meters may monitor demand, or the highest amount of electricity used during a specific time. Additionally, some meters feature relays for load shedding in response to responses during periods of peak load. The amount of electrical energy consumed by users is measured by a Watt-hour meter, also known as an energy meter. To charge the electricity usage by loads like lights, fans, and other appliances, utilities put these gadgets everywhere, including in households, businesses, and organizations. Watts are a fundamental power unit. A kilowatt is equal to one thousand watts. One kilowatt is regarded as one unit of energy used if used for one hour. These meters calculate the product of the instantaneous voltage and current readings and provide instantaneous power. This power is distributed over a period and is used during that time. Depending on the supply used by home or commercial installations, these may be single or three phase meters. These can be linked directly between line and load for minor service measurements, such as home consumers. However, step-down current transformers must be installed for greater loads to handle their higher current demands.

[the Use Of Fish On Buccal Smear To Investigate Mosaicism With A 45,x Cell Line: Study On Healthy Men And Patients With Disorders Of Sex Development].

To verify whether fluorescence in situ hybridization (FISH) of cells from the buccal epithelium could be employed to detect cryptomosaicism with a 45,X lineage in 46,XY patients. Samples of nineteen 46,XY healthy young men and five patients with disorders of sex development (DSD), four 45,X/46,XY and one 46,XY were used. FISH analysis with X and Y specific probes on interphase nuclei from blood lymphocytes and buccal epithelium were analyzed to investigate the proportion of nuclei containing only the signal of the X chromosome. The frequency of nuclei containing only the X signal in the two tissues of healthy men did not differ (p = 0.69). In all patients with DSD this frequency was significantly higher, and there was no difference between the two tissues (p = 0.38), either. Investigation of mosaicism with a 45,X cell line in patients with 46,XY DSD or sterility can be done by FISH directly using cells from the buccal epithelium.

The Influence Of The Environment On The Development Of Thyroid Tumors: A New Appraisal.

Most epidemiological studies concerning differentiated thyroid cancers (DTC) indicate an increasing incidence over the last two decades. This increase might be partially explained by the better access to health services worldwide, but clinicopathological analyses do not fully support this hypothesis, indicating that there are carcinogenetic factors behind this noticeable increasing incidence. Although we have undoubtedly understood the biology and molecular pathways underlying thyroid carcinogenesis in a better way, we have made very little progresses in identifying a risk profile for DTC, and our knowledge of risk factors is very similar to what we knew 30-40 years ago. In addition to ionizing radiation exposure, the most documented and established risk factor for DTC, we also investigated the role of other factors, including eating habits, tobacco smoking, living in a volcanic area, xenobiotics, and viruses, which could be involved in thyroid carcinogenesis, thus, contributing to the increase in DTC incidence rates observed.

Development And Shelf-life Determination Of Pasteurized, Microfiltered, Lactose Hydrolyzed Skim Milk.

The segment of the world population showing permanent or temporary lactose intolerance is quite significant. Because milk is a widely consumed food with an high nutritional value, technological alternatives have been sought to overcome this dilemma. Microfiltration combined with pasteurization can not only extend the shelf life of milk but can also maintain the sensory, functional, and nutritional properties of the product. This studied developed a pasteurized, microfiltered, lactose hydrolyzed (delactosed) skim milk (PMLHSM). Hydrolysis was performed using β-galactosidase at a concentration of 0.4mL/L and incubation for approximately 21h at 10±1°C. During these procedures, the degree of hydrolysis obtained (>90%) was accompanied by evaluation of freezing point depression, and the remaining quantity of lactose was confirmed by HPLC. Milk was processed using a microfiltration pilot unit equipped with uniform transmembrane pressure (UTP) ceramic membranes with a mean pore size of 1.4 μm and UTP of 60 kPa. The product was submitted to physicochemical, microbiological, and sensory evaluations, and its shelf life was estimated. Microfiltration reduced the aerobic mesophilic count by more than 4 log cycles. We were able to produce high-quality PMLHSM with a shelf life of 21 to 27d when stored at 5±1°C in terms of sensory analysis and proteolysis index and a shelf life of 50d in regard to total aerobic mesophile count and titratable acidity.

De Novo Assembly And Transcriptome Analysis Of The Rubber Tree (hevea Brasiliensis) And Snp Markers Development For Rubber Biosynthesis Pathways.

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Development And Characterization Of Microsatellite Loci For Ocotea Species (lauraceae) Threatened With Extinction.

The Atlantic rainforest species Ocotea catharinensis, Ocotea odorifera, and Ocotea porosa have been extensively harvested in the past for timber and oil extraction and are currently listed as threatened due to overexploitation. To investigate the genetic diversity and population structure of these species, we developed 8 polymorphic microsatellite markers for O. odorifera from an enriched microsatellite library by using 2 dinucleotide repeats. The microsatellite markers were tested for cross-amplification in O. catharinensis and O. porosa. The average number of alleles per locus was 10.2, considering all loci over 2 populations of O. odorifera. Observed and expected heterozygosities for O. odorifera ranged from 0.39 to 0.93 and 0.41 to 0.92 across populations, respectively. Cross-amplification of all loci was successfully observed in O. catharinensis and O. porosa except 1 locus that was found to lack polymorphism in O. porosa. Combined probabilities of identity in the studied Ocotea species were very low ranging from 1.0 x 10-24 to 7.7 x 10-24. The probability of exclusion over all loci estimated for O. odorifera indicated a 99.9% chance of correctly excluding a random nonparent individual. The microsatellite markers described in this study have high information content and will be useful for further investigations on genetic diversity within these species and for subsequent conservation purposes.

Development And Characterization Of Microsatellite Loci For Tabebuia Cassinoides (bignoniaceae).

Tabebuia cassinoides (Lam.) DC., popularly known as caxeta, is a tree species that belongs to the plant family Bignoniaceae. This species is endemic to the Brazilian Atlantic Forest and is widely exploited commercially. To date, little is known about its genetic structure, preventing the establishment of adequate management plans for this taxon. The objective of this study was to construct a microsatellite-enriched genomic library for T. cassinoides to select polymorphic loci, and standardize polymerase chain reaction amplification conditions. Of the 15 loci examined, 5 were polymorphic. The number of alleles per locus ranged from 2 to 8, with a mean of 4.4. The microsatellite loci described here represent the basis for detailed population genetic studies of this species, which will greatly contribute for the development of better conservation strategies for this taxon.

Development And Characterization Of 32 Microsatellite Loci In Genipa Americana (rubiaceae).

• Microsatellite primers were developed for the tree species Genipa americana (Rubiaceae) for further population genetic studies. • We identified 144 clones containing 65 repeat motifs from a genomic library enriched for (CT)8 and (GT)8 motifs. Primer pairs were developed for 32 microsatellite loci and validated in 40 individuals of two natural G. americana populations. Seventeen loci were polymorphic, revealing from three to seven alleles per locus. The observed and expected heterozygosities ranged from 0.24 to 1.00 and from 0.22 to 0.78, respectively. • The 17 primers identified as polymorphic loci are suitable to study the genetic diversity and structure, mating system, and gene flow in G. americana.

Leaf-, Panel- And Latex-expressed Sequenced Tags From The Rubber Tree (hevea Brasiliensis) Under Cold-stressed And Suboptimal Growing Conditions: The Development Of Gene-targeted Functional Markers For Stress Response.

Hevea brasiliensis is a native species of the Amazon Basin of South America and the primary source of natural rubber worldwide. Due to the occurrence of South American Leaf Blight disease in this area, rubber plantations have been extended to suboptimal regions. Rubber tree breeding is time-consuming and expensive, but molecular markers can serve as a tool for early evaluation, thus reducing time and costs. In this work, we constructed six different cDNA libraries with the aim of developing gene-targeted molecular markers for the rubber tree. A total of 8,263 reads were assembled, generating 5,025 unigenes that were analyzed; 912 expressed sequence tags (ESTs) represented new transcripts, and two sequences were highly up-regulated by cold stress. These unigenes were scanned for microsatellite (SSR) regions and single nucleotide polymorphisms (SNPs). In total, 169 novel EST-SSR markers were developed; 138 loci were polymorphic in the rubber tree, and 98 % presented transferability to six other Hevea species. Locus duplication was observed in H. brasiliensis and other species. Additionally, 43 SNP markers in 13 sequences that showed similarity to proteins involved in stress response, latex biosynthesis and developmental processes were characterized. cDNA libraries are a rich source of SSR and SNP markers and enable the identification of new transcripts. The new markers developed here will be a valuable resource for linkage mapping, QTL identification and other studies in the rubber tree and can also be used to evaluate the genetic variability of other Hevea species, which are valuable assets in rubber tree breeding.