849 resultados para ACRL Assessment and Action Project
Resumo:
Aspergillus phoenicis is an interesting heat tolerant fungus that can synthesize enzymes with several applications in the food industry due to its great hydrolytic potential. In this work, the fungus produced high enzymatic levels when cultivated on inexpensive culture media consisting of flakes from different origins such as cassava flour, wheat fibre, crushed soybean, agro-industrial wastes, starch, glucose or maltose. Several enzymatic systems were produced from these carbon sources, but amylase was the most evident, followed by pectinase and xylanase. Traces of CMCases, avicelase, lipase, β-xylosidase, β-glucosidase and α-glucosidase activities were also detected. Amylases were produced on rye flakes, starch, oat flakes, corn flakes, cassava flour and wheat fibre. Significant amylolytic levels were produced in the culture medium with glucose or when this sugar was exhausted, suggesting an enzyme in the constitutive form. Cassava flour, rye, oats, barley and corn flakes were also used as substrates in the hydrolytic reactions, aiming to verify the liberation potential of reducing sugars. Corn flakes induced greater liberation of reducing sugars as compared to the others. Thin layer chromatography of the reaction end products showed that the hydrolysis of cassava flour liberated maltooligosaccharides, but cassava flour and corn, rye, oats and barley flakes were hydrolyzed to glucose. These results suggested the presence of glucoamylase and α-amylase as part of the enzymatic pool of A. phoencis.
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[EN] This paper describes VPL, a Virtual Programming Lab module for Moodle, developed at the University of Las Palmas of Gran Canaria (ULPGC) and released for free uses under GNU/GPL license. For the students, it is a simple development environment with auto evaluation capabilities. For the instructors, it is a students' work management system, with features to facilitate the preparation of assignments, manage the submissions, check for plagiarism, and do assessments with the aid of powerful and flexible assessment tools based on program testing, all of that being independent of the programming language used for the assignments and taken into account critical security issues.
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The high energy consumption caused by the building sector and the continuous growth and ageing of the existing housing stock show the importance of housing renovation to improve the quality of the environment. This research compares the environmental performance of flat roof systems (insulation, roofing membrane and covering layer) using Life Cycle Assessment (LCA). The aim is to give indications on how to improve the environmental performance of housing. This research uses a reference building located in the Netherlands and considers environmental impacts related to materials, energy consumption for heating and maintenance activities. It indicates impact scores for each material taking into account interconnections between the layers and between the different parts of the life cycle. It compares the environmental and economic performances of PV panels and of different materials and thermal resistance values for the insulation. These comparisons show that PV panels are convenient from an environmental and economic point of view. The same is true for the insulation layer, especially for materials as PIR (polyisocyanurate) and EPS (expanded polystyrene). It shows that energy consumption for heating causes a larger share of impact scores than production of the materials and maintenance activities. The insulation also causes larger impact scores comparing to roofing membrane and covering layer. The results show which materials are preferable for flat roof renovation and what causes the largest shares of impact. This gives indication to the roofers and to other stakeholders about how to reduce the environmental impact of the existing housing stock.
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Sudden cardiac death due to ventricular arrhythmia is one of the leading causes of mortality in the world. In the last decades, it has proven that anti-arrhythmic drugs, which prolong the refractory period by means of prolongation of the cardiac action potential duration (APD), play a good role in preventing of relevant human arrhythmias. However, it has long been observed that the “class III antiarrhythmic effect” diminish at faster heart rates and that this phenomenon represent a big weakness, since it is the precise situation when arrhythmias are most prone to occur. It is well known that mathematical modeling is a useful tool for investigating cardiac cell behavior. In the last 60 years, a multitude of cardiac models has been created; from the pioneering work of Hodgkin and Huxley (1952), who first described the ionic currents of the squid giant axon quantitatively, mathematical modeling has made great strides. The O’Hara model, that I employed in this research work, is one of the modern computational models of ventricular myocyte, a new generation began in 1991 with ventricular cell model by Noble et al. Successful of these models is that you can generate novel predictions, suggest experiments and provide a quantitative understanding of underlying mechanism. Obviously, the drawback is that they remain simple models, they don’t represent the real system. The overall goal of this research is to give an additional tool, through mathematical modeling, to understand the behavior of the main ionic currents involved during the action potential (AP), especially underlining the differences between slower and faster heart rates. In particular to evaluate the rate-dependence role on the action potential duration, to implement a new method for interpreting ionic currents behavior after a perturbation effect and to verify the validity of the work proposed by Antonio Zaza using an injected current as a perturbing effect.
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Proper hazard identification has become progressively more difficult to achieve, as witnessed by several major accidents that took place in Europe, such as the Ammonium Nitrate explosion at Toulouse (2001) and the vapour cloud explosion at Buncefield (2005), whose accident scenarios were not considered by their site safety case. Furthermore, the rapid renewal in the industrial technology has brought about the need to upgrade hazard identification methodologies. Accident scenarios of emerging technologies, which are not still properly identified, may remain unidentified until they take place for the first time. The consideration of atypical scenarios deviating from normal expectations of unwanted events or worst case reference scenarios is thus extremely challenging. A specific method named Dynamic Procedure for Atypical Scenarios Identification (DyPASI) was developed as a complementary tool to bow-tie identification techniques. The main aim of the methodology is to provide an easier but comprehensive hazard identification of the industrial process analysed, by systematizing information from early signals of risk related to past events, near misses and inherent studies. DyPASI was validated on the two examples of new and emerging technologies: Liquefied Natural Gas regasification and Carbon Capture and Storage. The study broadened the knowledge on the related emerging risks and, at the same time, demonstrated that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards. Moreover, in order to tackle underlying accident causes of atypical events, three methods for the development of early warning indicators were assessed: the Resilience-based Early Warning Indicator (REWI) method, the Dual Assurance method and the Emerging Risk Key Performance Indicator method. REWI was found to be the most complementary and effective of the three, demonstrating that its synergy with DyPASI would be an adequate strategy to improve hazard identification methodologies towards the capture of atypical accident scenarios.
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The aim of this thesis was to investigate the respective contribution of prior information and sensorimotor constraints to action understanding, and to estimate their consequences on the evolution of human social learning. Even though a huge amount of literature is dedicated to the study of action understanding and its role in social learning, these issues are still largely debated. Here, I critically describe two main perspectives. The first perspective interprets faithful social learning as an outcome of a fine-grained representation of others’ actions and intentions that requires sophisticated socio-cognitive skills. In contrast, the second perspective highlights the role of simpler decision heuristics, the recruitment of which is determined by individual and ecological constraints. The present thesis aims to show, through four experimental works, that these two contributions are not mutually exclusive. A first study investigates the role of the inferior frontal cortex (IFC), the anterior intraparietal area (AIP) and the primary somatosensory cortex (S1) in the recognition of other people’s actions, using a transcranial magnetic stimulation adaptation paradigm (TMSA). The second work studies whether, and how, higher-order and lower-order prior information (acquired from the probabilistic sampling of past events vs. derived from an estimation of biomechanical constraints of observed actions) interacts during the prediction of other people’s intentions. Using a single-pulse TMS procedure, the third study investigates whether the interaction between these two classes of priors modulates the motor system activity. The fourth study tests the extent to which behavioral and ecological constraints influence the emergence of faithful social learning strategies at a population level. The collected data contribute to elucidate how higher-order and lower-order prior expectations interact during action prediction, and clarify the neural mechanisms underlying such interaction. Finally, these works provide/open promising perspectives for a better understanding of social learning, with possible extensions to animal models.
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The latter part of the 20th century was a period characterized by a fundamental demographic transition of western society. This substantial and structural demographic change proposes several challenges to contemporary society and fosters the emergence of new issues and challenges. Among these, none is more crucial than the comprehension of the mechanisms and the processes that lead people to positive aging. Rowe and Kahn’s model of successful aging highlights the interplay between social engagement with life, health, and functioning for a positive aging experience. Other systemic models of successful aging (Kahana et al., 1996; 2003; Stevernik et al., 2006) emphasize the role of internal and external resources for attaining positive aging. Among these, the proactive coping strategies are indicated as important active strategies for avoiding the depletion of resources, counterbalancing the declines and maintaining social and civic involvement. The study has analyzed the role of proactive coping strategies for two facets of positive aging, the experience of a high social well-being and the presence of personal projects in fundamental life domains. As expected, the proactive coping strategies, referred to as the active management of the environment, the accumulation of resources and the actualization of human potentials are confirmed as positive predictors of high level of social well-being and of many personal projects focused on family, culture, leisure time, civic and social participation. Perceived health status give a significant contribution only to the possession of many personal projects. Gender and level of school education give also a significant contribution to these two dimensions of positive aging, highlighting how positive aging is rooted not only in the possession of personal resources, but also in historical models of education and in positive longitudinal chains related to early development.
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The present work takes into account three posterior parietal areas, V6, V6A, and PEc, all operating on different subsets of signals (visual, somatic, motor). The work focuses on the study of their functional properties, to better understand their respective contribution in the neuronal circuits that make possible the interactions between subject and external environment. In the caudalmost pole of parietal lobe there is area V6. Functional data suggest that this area is related to the encoding of both objects motion and ego-motion. However, the sensitivity of V6 neurons to optic flow stimulations has been tested only in human fMRI experiments. Here we addressed this issue by applying on monkey the same experimental protocol used in human studies. The visual stimulation obtained with the Flow Fields stimulus was the most effective and powerful to activate area V6 in monkey, further strengthening this homology between the two primates. The neighboring areas, V6A and PEc, show different cytoarchitecture and connectivity profiles, but are both involved in the control of reaches. We studied the sensory responses present in these areas, and directly compared these.. We also studied the motor related discharges of PEc neurons during reaching movements in 3D space comparing also the direction and depth tuning of PEc cells with those of V6A. The results show that area PEc and V6A share several functional properties. Area PEc, unlike V6A, contains a richer and more complex somatosensory input, and a poorer, although complex visual one. Differences emerged also comparing the motor-related properties for reaches in depth: the incidence of depth modulations in PEc and the temporal pattern of modulation for depth and direction allow to delineate a trend among the two parietal visuomotor areas.
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During the PhD program in chemistry, curriculum in environmental chemistry, at the University of Bologna the sustainability of industry was investigated through the application of the LCA methodology. The efforts were focused on the chemical sector in order to investigate reactions dealing with the Green Chemistry and Green Engineering principles, evaluating their sustainability in comparison with traditional pathways by a life cycle perspective. The environmental benefits associated with a reduction in the synthesis steps and the use of renewable feedstock were assessed through a holistic approach selecting two case studies with high relevance from an industrial point of view: the synthesis of acrylonitrile and the production of acrolein. The current approach wants to represent a standardized application of LCA methodology to the chemical sector, which could be extended to several case studies, and also an improvement of the current databases, since the lack of data to fill the inventories of the chemical productions represent a huge limitation, difficult to overcome and that can affects negatively the results of the studies. Results emerged from the analyses confirms that the sustainability in the chemical sector should be evaluated from a cradle-to-gate approach, considering all the stages and flows involved in each pathways in order to avoid shifting the environmental burdens from a steps to another. Moreover, if possible, LCA should be supported by other tools able to investigate the other two dimensions of sustainability represented by the social and economic issues.
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This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback.
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Coastal flooding poses serious threats to coastal areas around the world, billions of dollars in damage to property and infrastructure, and threatens the lives of millions of people. Therefore, disaster management and risk assessment aims at detecting vulnerability and capacities in order to reduce coastal flood disaster risk. In particular, non-specialized researchers, emergency management personnel, and land use planners require an accurate, inexpensive method to determine and map risk associated with storm surge events and long-term sea level rise associated with climate change. This study contributes to the spatially evaluation and mapping of social-economic-environmental vulnerability and risk at sub-national scale through the development of appropriate tools and methods successfully embedded in a Web-GIS Decision Support System. A new set of raster-based models were studied and developed in order to be easily implemented in the Web-GIS framework with the purpose to quickly assess and map flood hazards characteristics, damage and vulnerability in a Multi-criteria approach. The Web-GIS DSS is developed recurring to open source software and programming language and its main peculiarity is to be available and usable by coastal managers and land use planners without requiring high scientific background in hydraulic engineering. The effectiveness of the system in the coastal risk assessment is evaluated trough its application to a real case study.
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Il crescente utilizzo di sistemi di analisi high-throughput per lo studio dello stato fisiologico e metabolico del corpo, ha evidenziato che una corretta alimentazione e una buona forma fisica siano fattori chiave per la salute. L'aumento dell'età media della popolazione evidenzia l'importanza delle strategie di contrasto delle patologie legate all'invecchiamento. Una dieta sana è il primo mezzo di prevenzione per molte patologie, pertanto capire come il cibo influisce sul corpo umano è di fondamentale importanza. In questo lavoro di tesi abbiamo affrontato la caratterizzazione dei sistemi di imaging radiografico Dual-energy X-ray Absorptiometry (DXA). Dopo aver stabilito una metodologia adatta per l'elaborazione di dati DXA su un gruppo di soggetti sani non obesi, la PCA ha evidenziato alcune proprietà emergenti dall'interpretazione delle componenti principali in termini delle variabili di composizione corporea restituite dalla DXA. Le prime componenti sono associabili ad indici macroscopici di descrizione corporea (come BMI e WHR). Queste componenti sono sorprendentemente stabili al variare dello status dei soggetti in età, sesso e nazionalità. Dati di analisi metabolica, ottenuti tramite Magnetic Resonance Spectroscopy (MRS) su campioni di urina, sono disponibili per circa mille anziani (provenienti da cinque paesi europei) di età compresa tra i 65 ed i 79 anni, non affetti da patologie gravi. I dati di composizione corporea sono altresì presenti per questi soggetti. L'algoritmo di Non-negative Matrix Factorization (NMF) è stato utilizzato per esprimere gli spettri MRS come combinazione di fattori di base interpretabili come singoli metaboliti. I fattori trovati sono stabili, quindi spettri metabolici di soggetti sono composti dallo stesso pattern di metaboliti indipendentemente dalla nazionalità. Attraverso un'analisi a singolo cieco sono stati trovati alti valori di correlazione tra le variabili di composizione corporea e lo stato metabolico dei soggetti. Ciò suggerisce la possibilità di derivare la composizione corporea dei soggetti a partire dal loro stato metabolico.
Resumo:
Context and Objective: Main features of the autosomal dominant form of GH deficiency (IGHD II) include markedly reduced secretion of GH combined with low concentrations of IGF-I leading to short stature. Design, Setting, and Patients: A female patient presented with short stature (height -6.0 sd score) and a delayed bone age of 2 yr at the chronological age of 5 yr. Later, at the age of 9 yr, GHD was confirmed by standard GH provocation test, which revealed subnormal concentrations of GH and a very low IGF-I. Genetic analysis of the GH-1 gene revealed the presence of a heterozygous R178H mutation. Interventions and Results: AtT-20 cells coexpressing both wt-GH and GH-R178H showed a reduced GH secretion after forskolin stimulation compared with the cells expressing only wt-GH, supporting the diagnosis of IGHD II. Because reduced GH concentrations found in the circulation of our untreated patient could not totally explain her severe short stature, functional characterization of the GH-R178H performed by studies of GH receptor binding and activation of the Janus kinase-2/signal transducer and activator of transcription-5 pathway revealed a reduced binding affinity of GH-R178H for GH receptor and signaling compared with the wt-GH. Conclusion: This is the first report of a patient suffering from short stature caused by a GH-1 gene alteration affecting not only GH secretion (IGHD II) but also GH binding and signaling, highlighting the necessity of functional analysis of any GH variant, even in the alleged situation of IGHD II.