1,721,125 research outputs found
Applying Model-Based System Engineering to the Verification of Space Systems
No full textThe life cycle of a complex system is a process involving a large amount of elements to be defined, designed, verified, produced and interfaced, and completed through the interaction of several people with different background, experience and field of interest.
Model-based system engineering is an emerging approach that aims to help the improvement of such processes, making all the data relevant to the product stored in semantically structured models that describe it in all its characteristics and point of views.
The future development of system engineering may be envisaged as gradually abandoning the document-based in favor of the model-based approach.
While the application of model-based methodologies to the design of complex systems is on its way, through a relevant number of initiatives, lesser effort has been spent up to now concerning the verification of the system specification. The aim of this work is therefore to define a methodology to apply the principles of model-based system engineering to the verification process, to demonstrate feasibility and advantages and to identify the need of improvement in this sense coming from the past experience.
The space industry is an ideal domain for such activity, as it covers some of the most complex built systems, both in terms of design and industrial perspectives; therefore the work here presented is focused on the European space standards and principles, but it is worth noting that the approach is easily generalized to other industrial domains
Behavioral and neurochemical effects of Palmitoylethanolamide in a murine model of Alzheimer’s Disease
Full text linkAbstract
La malattia di Alzheimer è la forma più comune di demenza degenerativa progressivamente invalidante con esordio prevalentemente in età presenile.
Si stima che circa il 60-70% dei casi di demenza sia dovuta a Alzheimer disease (AD). AD è una patologia multifattoriale caratterizzata sia da placche senili extracellulari, costituite dall’accumulo della proteina amiloide, sia da grovigli neurofibrillari intracellulari, composti da filamenti Tau patologici (NFTs).
Inoltre nell’Alzheimer vi è anche perdita neuronale soprattutto a livello delle aree cerebrali che sottendono i processi di apprendimento e memoria, come per esempio la corteccia frontale e l’ippocampo.
L’eziologia dell’AD sembra essere legata a vari meccanismi che non sono stati ancora completamente chiariti. Allo stato attuale, non esistono terapie in uso clinico in grado di influenzare efficacemente il decorso della malattia.
Alla luce della complessità della patologia e ovvio pensare che i nuovi farmaci, per essere ritenuti farmacologicamente promettenti, dovrebbero agire contemporaneamente sui vari meccanismi patogenetici coinvolti nell’AD.
A tal proposito, l'obiettivo di questo progetto di ricerca è stato quello di verificare se la Palmitoiletanolamide (PEA) è in grado di modulare i sintomi presenti nella malattia di Alzheimer.
Per gli obiettivi del progetto, è stato utilizzato un modello transgenico murino della patologia di Alzheimer ed il rispettivo gruppo controllo, non transgenico (NonTg).
I topi transgenici, creati nei laboratori del prof. La Ferla (University of California, Irvine, USA) hanno tre geni umani mutanti (APPswe, PS1M146V, e tauP301L), per questo indicati come 3×Tg-AD, e sono considerati tra i modelli animali di malattia di Alzheimer che meglio simulano la patologia riscontrata nell’uomo.
Infatti, i 3×Tg-AD sono in grado di sviluppare le placche amiloidi e NTF in maniera tempo dipendente, nelle regioni target del cervello, simulando così la progressione della malattia riscontrata negli esseri umani.
Nel nostro protocollo sperimentale, topi a 3 mesi (che presentavano i primi segni di alterazioni neuropatologiche) e 9 mesi (che presentavano evidenti segni di alterazioni neuropatologiche) di vita sono stati trattati con Palmitoiletanolamide (PEA) per 90 giorni e, alla fine del trattamento cronico, i topi sono stati sottoposti a diversi test comportamentali per valutare un eventuale effetto sui deficit cognitivi e non cognitivi riscontrati nel modello transgenico preso in esame.
Alla fine dei test comportamentali gli animali sono stati sacrificati per determinare, mediante analisi di biologia molecolare, l'effetto del trattamento sulle alterazioni istopatologiche tipiche della AD.
I risultati dello studio hanno dimostrato che la PEA è in grado di migliorare le funzioni cognitive e non cognitive nei topi 3×Tg-AD a 6 mesi di vita, mentre sui topi a 12 mesi di vita ha mostrato un miglioramento significativo solo sulla memoria a breve termine.
Circa gli effetti della PEA sulla patologia Aβ e tau nei topi 3xTg-AD, lo studio ha dimostrato che la PEA riduce in modo significativo i livelli di APP nella corteccia di topi 3×Tg-AD a 6 mesi e, cosa ancor più interessante, diminuisce anche i livelli di Aβ*56, un oligomero di Aβ.
Inoltre, il trattamento cronico con PEA ha indotto una significativa riduzione della fosforilazione di tau nei residui di fosforilazione 202/205.
Questi risultati suggeriscono, pertanto, che il miglioramento delle funzioni cognitive e non cognitive potrebbe essere ascritto alle variazioni sui livelli complessivi di Aβ e di tau indotti dal trattamento cronico con PEA. Inoltre, non abbiamo trovato cambiamenti significativi nei topi 3×Tg-AD per quanto riguarda i marcatori neuroinfiammatori presi in considerazione, come, ad esempio, COX-2 o marcatori di attivazione astrocitari e/o microgliali.
Certamente ulteriori studi saranno necessari per determinare i meccanismi molecolari alla base degli effetti della PEA.
In conclusione, i nostri dati indicano che il trattamento cronico con PEA potrebbe essere efficace nelle fasi precoci della patologia, ovvero quando l’accumulo di Aβ è nelle sue fasi iniziali ed i danni nel sistema nervoso centrale sono ancora lievi.
Abstract in English
Alzheimer’s disease (AD) is the most common form of dementia affecting elderly people. AD is a multifaceted pathology characterized by accumulation of extracellular neuritic plaques, intracellular neurofibrillary tangles (NFTs) and neuronal loss mainly in the cortex and hippocampus. AD etiology appears to be linked to a multitude of mechanisms that have not been yet completely elucidated. At present, no therapies in clinical use are able to effectively impact the disease course. Therefore, new drugs able to simultaneously ameliorate the numerous pathogenic mechanism involved in AD are therapeutically promising.To this regard, the aim of this research project was to investigate whether the Palmitoylethanolamide (PEA), an endogenous fatty acid amide, might modulate the symptoms of the AD.
To this aim, the triple transgenic mouse model of AD (3xTg-AD) and wild type littermate (NonTg) have been used. The 3×Tg-AD mice harbor three mutant human genes (APPswe, PS1M146V, and tauP301L) and are one of the most thoroughly characterized model of AD. The 3×Tg-AD mice develop amyloid plaques and NTF pathology in a hierarchical manner in AD-relevant brain regions, and closely mimic the disease progression in humans.
The mice at 3-months and 9-months of age have been treated with PEA for 90 days and, at the end of treatment, they were subjected to different behavioral tests in order to investigate their mood and learning/memory domains. At the end of behavioral tests the animals were sacrified to determine, by biochemical analyses, the effect of treatment on neuropathological and neuroinflammatory hallmarks.
Interestingly PEA is able to improve cognitive and non-cognitive functions in 3×Tg-AD at 6 months of age, while has only effect on short-term memory in transgenic mice at 12 months of age.
The present work provides also an extensive investigation of the effect of PEA treatment on the onset and progression of Aβ and tau pathology in 3×Tg-AD
mice. We showed that PEA significantly reduces the levels of full-length APP in cortex of 6-month-old 3×Tg-AD mice and, more interestingly, it decreases also the levels of Aβ*56, an Aβ oligomer. Similarly, PEA treatment is able to reduce steady-state levels of full-length APP also in 3×Tg-AD mice at 12 months of age, suggesting that it could modulate APP processing in these animals.
Interestingly, PEA treatment is also associated with a significant reduction in tau phosphorylation at residues 202/205. These results suggest that cognitive improvement is probably due to changes in overall Aβ levels and tau pathology or to a mixture of both hallmarks.
Furthermore, we did not find significant changes in almost all neuroinflammatory markers taken into account, such as COX-2 or in microglial/astrocytic activation markers.
Although further studies are needed to determine the molecular mechanisms underlying the beneficial effects of PEA against AD neuropathology, our data indicate that the compound may be effective in early AD or when Aβ is accumulating and initiating damage in the central nervous system
Glutamate and mitochondria: two prominent players in the oxidative stress-induced neurodegeneration
Full text linkThe aetiology of major neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) is still unknown, but increasing evidences suggest that glutamate and mitochondria are two prominent players in the oxidative stress (OS) process that underlie these illnesses. Although AD and PD have distinct pathological and clinical features, OS is a common mechanism contributing to neuronal damage. Glutamate is an important neurotransmitter in neurons and glial cells and is strongly dependent on calcium homeostasis and on mitochondrial function. In the present work we focused on glutamate- induced calcium signaling and its relation to the mitochondrial dysfunction with cell death processes. In addition, we have discussed how alterations in this pathway may lead or aggravate the neurodegenerative diseases. Finally, this review aims to stimulate further studies on this issue and thereby engage a new perspective regarding the design of possible therapeutic agents or the identification of biomarkers
Parametric Methods for Fault Analysis Applied to a Servomechanism Affected by Multiple Failures
No full textIn order to detect incipient failures due to a progressive wear of a primary flight command electro hydraulic actuator (EHA), prognostics could employ several approaches; the choice of the best ones is driven by the efficacy shown in failure detection, since not all the algorithms might be useful for the proposed purpose. In other words, some of them could be suitable only for certain applications while they could not give useful results for others. Developing a fault detection algorithm able to identify the precursors of the above mentioned EHA failure and its degradation pattern is thus beneficial for anticipating the incoming failure and alerting the maintenance crew so as to properly schedule the servomechanism replacement. The research presented in the paper was focused to develop a prognostic technique, able to identify symptoms alerting that an EHA component is degrading and will eventually exhibit an anomalous behavior; in particular, six different types of progressive failures are considered (dry friction acting of servovalve spool or mechanical actuator, radial clearance between spool and sleeve, shape of the corners of the spool lands, torque sensitivity of the first stage torque motor, contamination of the first stage filter). To this purpose, an innovative model based fault detection technique, based upon "failure maps", has been developed merging together the information achieved by FFT analysis and proper "failure precursors" (calculated comparing the actual EHA responses with the expected ones). To assess the robustness of the proposed technique, an appropriate simulation test environment was developed. The results showed an adequate robustness and confidence was gained in the ability to early identify an eventual EHA malfunctioning with low risk of false alarms or missed failure
A New Prognostic Method Based on Simulated Annealing Algorithm to Deal with the Effects of Dry Friction on Electromechanical Actuators
Full text linkIn prognostics it is possible to apply several approaches with the aim to detect incipient failures, caused by progressive wear, of electromechanical actuators (EMA) in primary flight commands. The anticipation of a failure has to be performed through a correct interpretation of the degradation pattern, so to trig an early alert for maintenance and to properly schedule the servomechanism replacement. This paper proposes a prognostic approach based on the simulated annealing optimization method, able to identify symptoms of degradation before the behavior of the actuator becomes anomalous; friction failures are considered as the case study. The approach is validated through an experimental test bench, resulting in an adequate robustness and a high degree of confidence in the ability to early identify faults, with a low amount of false alarms or not annunciated failure
Model-based definition of requirements to support system verification
Full text linkRequirements guide the engineering process from a technical and contractual point of view. Verification is the activity that manages the technical specification and provides the activities able to guarantee that the designed and manufactured system is able to fulfil requirements. While many of the engineering activities are increasingly based on models, especially for what concerns analysis by simulation, requirements are still text-based for the largest part. This paper proposes a methodology to manage the requirements as models, linking their distinguishing features to the relevant product objects, attributes, physical parameters and operational conditions. A case study is provided to assess the feasibility of the approach and to clarify the involved issues
Effects of Mechanical Backlash on Linear Electromechanical Actuators: A Fault Identification Method based on the Simulated Annealing Algorithm
No full textSeveral approaches can be employed in prognostics, to detect incipient failures of primary flight command electromechanical actuators (EMA), caused by progressive wear. The development of a prognostic algorithm capable of identifying the precursors of an electromechanical actuator failure is beneficial for the anticipation of the incoming faults: a correct interpretation of the fault degradation pattern can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. The research presented in this paper proposes a fault detection and identification technique, based on approaches derived from optimization methods, able to identify symptoms of EMA degradation before the actual exhibition of the anomalous behavior; in particular, the authors' work analyses the effects due to progressive backlashes acting on the mechanical transmission and evaluates the effectiveness of the proposed approach to correctly identify these faults. An experimental test bench was developed: results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual fault, minimizing the risk of false alarms or unrecognized failure
Effects of Dry Friction on Linear Electromechanical Actuators: A New Prognostic Method based on Simulated Annealing Algorithm
No full textSeveral approaches can be employed in prognostics, to detect incipient failures of primary flight command electromechanical actuators (EMA), caused by progressive wear. The development of a prognostic algorithm capable of identifying the precursors of an electromechanical actuator failure is beneficial for the anticipation of the incoming failure: a correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. The research presented in this paper proposes a prognostic technique, based on approaches derived from optimization methods, able to identify symptoms of an EMA degradation before the actual exhibition of the anomalous behavior; in this case friction failures are considered. An experimental test bench was developed: results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual fault, minimizing the risk of false alarms or not annunciated failure
Proposal of prognostic parametric method applied to an electrohydraulic servomechanism affected by multiple failures
No full textPrognostics could employ several approaches with the aim to detect incipient failures due to a progressive wear of a primary flight command electro hydraulic actuator (EHA); the efficacy shown in failure detection drives the choice of the best ones, since not all the algorithms might be useful for the intended purpose. This happens because some of them could be suitable only for specific applications while giving bad results for others. The development of a fault detection algorithm is thus beneficial for anticipating the incoming failure and alerting the maintenance crew so as to properly schedule the servomechanism replacement; such algorithm should be able to identify the precursors of the above mentioned EHA failure and its degradation pattern. This paper presents a research focused on the development of a prognostic methodology, able to identify symptoms alerting that an EHA component is degrading and will eventually exhibit an anomalous behavior; in detail, six different types of progressive failures have been considered (dry friction acting of servovalve spool or mechanical actuator, radial clearance between spool and sleeve, shape of the corners of the spool lands, torque sensitivity of the first stage torque motor, contamination of the first stage filter). To achieve such objectives, an innovative model based fault detection technique has been developed merging together the information achieved by FFT analysis and proper "failure precursors" (calculated comparing the actual EHA responses with the expected ones), relying upon a set of failure maps. The robustness of the proposed technique has been assessed through a simulation test environment, built on the purpose. Such simulation has demonstrated that the methodology has adequate robustness; also, the ability to early identify an eventual malfunctioning has been proved with low risk of missed failures or false positives
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