Towards Distributed Model Transformations with LinTra

Performance and scalability of model transformations are becoming prominent topics in Model-Driven Engineering. In previous works we introduced LinTra, a platform for executing model transformations in parallel. LinTra is based on the Linda model of a coordination language and is intended to be used as a middleware where high-level model transformation languages are compiled. In this paper we present the initial results of our analyses on the scalability of out-place model-to-model transformation executions in LinTra when the models and the processing elements are distributed over a set of machines.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

Cancers of unknown primary site (CUPs) as a model of metastatic process.

Cancers of unknown primary site (CUPs) are a rare group of metastatic tumours, with a frequency of 3-5%, with an overall survival of 6-10 month. The identification of tumour primary site is usually reached by a combination of diagnostic investigations and immunohistochemical testing of the tumour tissue. In CUP patients, these investigations are inconclusive. Since international guidelines for treatment are based on primary site indication, CUP treatment requires a blind approach. As a consequence, CUPs are usually empiric treated with poorly effective. In this study, we applied a set of microRNAs using EvaGreen-based Droplet Digital PCR in a retrospective and prospective collection of formalin-fixed paraffin-embedded tissue samples. We assessed miRNA expression of 155 samples including primary tumours (N=94), metastases of known origin (N=10) and metastases of unknown origin (N=50). Then, we applied the shrunken centroids predictive algorithm to obtain the CUP’s site(s)-of-origin. The molecular test was successfully applied to all CUP samples and provided a site-of-origin identification for all samples, potentially within a one-week time frame from sample inclusion. In the second part of the study we derived two CUP cell lines, and corresponding patient-derived xenografts (PDXs). CUP cell lines and PDXs underwent histological, molecular, and genomic characterization confirming the features of the original tumour. Tissues-of-origin prediction was obtained from the tumour microRNA expression profile and confirmed by single cell RNA sequencing. Genomic testing analysis identified FGFR2 amplification in both models. Drug-screening assays were performed to test the activity of FGFR2-targeting drug and the combination treatment with the MEK inhibitor trametinib, which proved to be synergic and exceptionally active, both in vitro and in vivo. In conclusion, our study demonstrated that miRNA expression profiling could be employed as diagnostic test. Then we successfully derived two CUP models from patients, used for therapy tests, bringing personalized therapy closer to CUP patients.

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.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Changes In Motor Behavior During Pregnancy In Rats: The Basis For A Possible Animal Model Of Restless Legs Syndrome.

Pregnant women have a 2-3 fold higher probability of developing restless legs syndrome (RLS - sleep-related movement disorders) than general population. This study aims to evaluate the behavior and locomotion of rats during pregnancy in order to verify if part of these animals exhibit some RLS-like features. We used 14 female 80-day-old Wistar rats that weighed between 200 and 250 g. The rats were distributed into control (CTRL) and pregnant (PN) groups. After a baseline evaluation of their behavior and locomotor activity in an open-field environment, the PN group was inducted into pregnancy, and their behavior and locomotor activity were evaluated on days 3, 10 and 19 of pregnancy and in the post-lactation period in parallel with the CTRL group. The serum iron and transferrin levels in the CTRL and PN groups were analyzed in blood collected after euthanasia by decapitation. There were no significant differences in the total ambulation, grooming events, fecal boli or urine pools between the CTRL and PN groups. However, the PN group exhibited fewer rearing events, increased grooming time and reduced immobilization time than the CTRL group (ANOVA, p<0.05). These results suggest that pregnant rats show behavioral and locomotor alterations similar to those observed in animal models of RLS, demonstrating to be a possible animal model of this sleep disorder.

Prostatic Angiogenic Responses In Late Life: Antiangiogenic Therapy Influences And Relation With The Glandular Microenvironment In The Transgenic Adenocarcinoma Of Mouse Prostate (tramp) Model.

Aging is considered one of the main predisposing factors for the development of prostate malignancies. Angiogenesis is fundamental for tumor growth and its inhibition represents a promising therapeutic approach in cancer treatment. Thus, we sought to determine angiogenic responses and the effects of antiangiogenic therapy in the mouse prostate during late life, comparing these findings with the prostatic microenvironment in the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) model. Male mice (52 week-old FVB) were submitted to treatments with SU5416 (6 mg/kg; i.p.) and/or TNP-470 (15 mg/kg; s.c.). Finasteride was administered (20 mg/kg; s.c.), alone or in association to both inhibitors. The dorsolateral prostate was collected for VEGF, HIF-1α, FGF-2 and endostatin immunohistochemical and Western Blotting analyses and for microvessel density (MVD) count. Senescence led to increased MVD and VEGF, HIF-1α and FGF-2 protein levels in the prostatic microenvironment, similarly to what was observed in TRAMP mice prostate. The angiogenic process was impaired in all the treated groups, demonstrating significantly decreased MVD. Antiangiogenic and/or finasteride treatments resulted in decreased VEGF and HIF-1α levels, especially following TNP-470 administration, either alone or associated to SU5416. The combination of these agents resulted in increased endostatin levels, regardless of the presence of finasteride. Prostatic angiogenesis stimulation during senescence favored the development of neoplastic lesions, considering the pro-angiogenic microenvironment as a common aspect also observed during cancer progression in TRAMP mice. The combined antiangiogenic therapy was more efficient, leading to enhanced imbalance towards angiogenic inhibition in the organ. Finally, finasteride administration might secondarily upregulate the expression of pro-angiogenic factors, pointing to the harmful effects of this therapy. Prostate 75: 484-499, 2015. © 2014 Wiley Periodicals, Inc.

Enhanced Glucose-induced Intracellular Signaling Promotes Insulin Hypersecretion: Pancreatic Beta-cell Functional Adaptations In A Model Of Genetic Obesity And Prediabetes.

Obesity is associated with insulin resistance and is known to be a risk factor for type-2 diabetes. In obese individuals, pancreatic beta-cells try to compensate for the increased insulin demand in order to maintain euglycemia. Most studies have reported that this adaptation is due to morphological changes. However, the involvement of beta-cell functional adaptations in this process needs to be clarified. For this purpose, we evaluated different key steps in the glucose-stimulated insulin secretion (GSIS) in intact islets from female ob/ob obese mice and lean controls. Obese mice showed increased body weight, insulin resistance, hyperinsulinemia, glucose intolerance and fed hyperglycemia. Islets from ob/ob mice exhibited increased glucose-induced mitochondrial activity, reflected by enhanced NAD(P)H production and mitochondrial membrane potential hyperpolarization. Perforated patch-clamp examination of beta-cells within intact islets revealed several alterations in the electrical activity such as increased firing frequency and higher sensitivity to low glucose concentrations. A higher intracellular Ca(2+) mobilization in response to glucose was also found in ob/ob islets. Additionally, they displayed a change in the oscillatory pattern and Ca(2+) signals at low glucose levels. Capacitance experiments in intact islets revealed increased exocytosis in individual ob/ob beta-cells. All these up-regulated processes led to increased GSIS. In contrast, we found a lack of beta-cell Ca(2+) signal coupling, which could be a manifestation of early defects that lead to beta-cell malfunction in the progression to diabetes. These findings indicate that beta-cell functional adaptations are an important process in the compensatory response to obesity.

In vitro Microfluidic Model For The Study Of Vaso-occlusive Processes.

Vaso-occlusion, responsible for much of the morbidity of sickle-cell disease, is a complex multicellular process, apparently triggered by leukocyte adhesion to the vessel wall. The microcirculation represents a major site of leukocyte-endothelial interactions and vaso-occlusive processes. We have developed a biochip with subdividing interconnecting microchannels that decrease in size (40 μm to 10 μm in width), for use in conjunction with a precise microfluidic device, to mimic cell flow and adhesion through channels of sizes that approach those of the microcirculation. The biochips were utilized to observe the dynamics of the passage of neutrophils and red blood cells, isolated from healthy and sickle-cell anemia (SCA) individuals, through laminin or endothelial adhesion molecule-coated microchannels at physiologically relevant rates of flow and shear stress. Obstruction of E-selectin/intercellular adhesion molecule 1-coated biochip microchannels by SCA neutrophils was significantly greater than that observed for healthy neutrophils, particularly in the microchannels of 40-15 μm in width. Whereas SCA red blood cells alone did not significantly adhere to, or obstruct, microchannels, mixed suspensions of SCA neutrophils and red blood cells significantly adhered to and obstructed laminin-coated channels. Results from this in vitro microfluidic model support a primary role for leukocytes in the initiation of SCA occlusive processes in the microcirculation. This assay represents an easy-to-use and reproducible in vitro technique for understanding molecular mechanisms and cellular interactions occurring in subdividing microchannels of widths approaching those observed in the microvasculature. The assay could hold potential for testing drugs developed to inhibit occlusive mechanisms such as those observed in SCA and thrombotic diseases.

Behaviour of oligodendrocytes and Schwann cells in an experimental model of toxic demyelination of the central nervous system

Oligodendrocytes and Schwann cells are engaged in myelin production, maintenance and repairing respectively in the central nervous system (CNS) and the peripheral nervous system (PNS). Whereas oligodendrocytes act only within the CNS, Schwann cells are able to invade the CNS in order to make new myelin sheaths around demyelinated axons. Both cells have some limitations in their activities, i.e. oligodendrocytes are post-mitotic cells and Schwann cells only get into the CNS in the absence of astrocytes. Ethidium bromide (EB) is a gliotoxic chemical that when injected locally within the CNS, induce demyelination. In the EB model of demyelination, glial cells are destroyed early after intoxication and Schwann cells are free to approach the naked central axons. In normal Wistar rats, regeneration of lost myelin sheaths can be achieved as early as thirteen days after intoxication; in Wistar rats immunosuppressed with cyclophosphamide the process is delayed and in rats administered cyclosporine it may be accelerated. Aiming the enlightening of those complex processes, all events concerning the myelinating cells in an experimental model are herein presented and discussed.

Effects of the condylar process fracture on facial symmetry in rats submitted to protein undernutrition

PURPOSE: To investigate the facial symmetry of rats submitted to experimental mandibular condyle fracture and with protein undernutrition (8% of protein) by means of cephalometric measurements. METHODS: Forty-five adult Wistar rats were distributed in three groups: fracture group, submitted to condylar fracture with no changes in diet; undernourished fracture group, submitted to hypoproteic diet and condylar fracture; undernourished group, kept until the end of experiment, without condylar fracture. Displaced fractures of the right condyle were induced under general anesthesia. The specimens were submitted to axial radiographic incidence, and cephalometric mensurations were made using a computer system. The values obtained were subjected to statistical analyses among the groups and between the sides in each group. RESULTS: There was significative decrease of the values of serum proteins and albumin in the undernourished fracture group. There was deviation of the median line of the mandible relative to the median line of the maxilla, significative to undernutrition fracture group, as well as asymmetry of the maxilla and mandible, in special in the final period of experiment. CONCLUSION: The mandibular condyle fracture in rats with proteic undernutrition induced an asymmetry of the mandible, also leading to consequences in the maxilla.

Influence of specimens' design and manufacturing process on microtensile bond strength to enamel: laboratory and FEA comparison

This study evaluated the effect of specimens' design and manufacturing process on microtensile bond strength, internal stress distributions (Finite Element Analysis - FEA) and specimens' integrity by means of Scanning Electron Microscopy (SEM) and Laser Scanning Confocal Microscopy (LCM). Excite was applied to flat enamel surface and a resin composite build-ups were made incrementally with 1-mm increments of Tetric Ceram. Teeth were cut using a diamond disc or a diamond wire, obtaining 0.8 mm² stick-shaped specimens, or were shaped with a Micro Specimen Former, obtaining dumbbell-shaped specimens (n = 10). Samples were randomly selected for SEM and LCM analysis. Remaining samples underwent microtensile test, and results were analyzed with ANOVA and Tukey test. FEA dumbbell-shaped model resulted in a more homogeneous stress distribution. Nonetheless, they failed under lower bond strengths (21.83 ± 5.44 MPa)c than stick-shaped specimens (sectioned with wire: 42.93 ± 4.77 MPaª; sectioned with disc: 36.62 ± 3.63 MPa b), due to geometric irregularities related to manufacturing process, as noted in microscopic analyzes. It could be concluded that stick-shaped, nontrimmed specimens, sectioned with diamond wire, are preferred for enamel specimens as they can be prepared in a less destructive, easier, and more precise way.

Effect of nitric oxide inhibitor and donor substances on the infammatory process caused by endodontic irrigants

Nitric oxide (NO) has been considered a key molecule in infammation. OBJECTIVE: The aim of this study was to evaluate the effect of treatment with L-NAME and sodium nitroprussiate, substances that inhibit and release NO, respectively, on tissue tolerance to endodontic irrigants. MATERIAL AND METHODS: The vital dye exudation method was used in a rat subcutaneous tissue model. Injections of 2% Evans blue were administered intravenously into the dorsal penial vein of 14 male rats (200-300 g). The NO inhibitor and donor substances were injected into the subcutaneous tissue in the dorsal region, forming two groups of animals: G1 was inoculated with L-NAME and G2 with sodium nitroprussiate. Both groups received injections of the test endodontic irrigants: acetic acid, 15% citric acid, 17% EDTA-T and saline (control). After 30 min, analysis of the extravasated dye was performed by light absorption spectrophotometry (620 nm). RESULTS: There was statistically signifcant difference (p<0.05) between groups 1 and 2 for all irrigants. L-NAME produced a less intense infammatory reaction and nitroprussiate intensifed this process. CONCLUSIONS: Independently of the administration of NO inhibitors and donors, EDTA-T produced the highest irritating potential in vital tissue among the tested irrigating solutions.

Reaction-diffusion stochastic lattice model for a predator-prey system

We have the purpose of analyzing the effect of explicit diffusion processes in a predator-prey stochastic lattice model. More precisely we wish to investigate the possible effects due to diffusion upon the thresholds of coexistence of species, i. e., the possible changes in the transition between the active state and the absorbing state devoid of predators. To accomplish this task we have performed time dependent simulations and dynamic mean-field approximations. Our results indicate that the diffusive process can enhance the species coexistence.

The UV/H2O2 - photodegradation of poly(ethyleneglycol) and model compounds

The general mechanism for the photodegradation of polyethyleneglycol (PEG) by H2O2/UV was determined studying the photooxidation of small model molecules, like low molecular weight ethyleneglycols (tetra-, tri-, di-, and ethyleneglycol). After 30 min of irradiation the average molar mass (Mw) of the degradated PEG, analysed by GPC, fall to half of its initial value, with a concomitant increase in polydispersitivity and number of average chain scission (S), characterizing a random chain scission process yielding oligomers and smaller size ethyleneglycols. HPLC analysis of the photodegradation of the model ethyleneglycols proved that the oxidation mechanism involved consecutive reactions, where the larger ethyleneglycols gave rise, successively, to smaller ones. The photodegradation of ethyleneglycol lead to the formation of low molecular weight carboxylic acids, like glycolic, oxalic and formic acids.