L'animazione giapponese come nuova frontiera dello streaming on demand

L’obiettivo di questo lavoro è prendere in analisi in che modo l’animazione seriale giapponese così come i film d’animazione siano pian piano diventati elementi imprescindibili dell’offerta di una piattaforma di streaming, e di come in futuro lo saranno sempre di più andando a convergere con altre esperienze mediali come i videogiochi. Animazione quindi come una nuova frontiera nella quale le piattaforme on demand dovranno giocarsela per il proprio spazio vitale ma anche per acquisire nuovi utenti.

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Minimal computation structures for visual information applications based on printed electronics

In the early nineties, Mark Weiser wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. According to Weiser, computers require too much attention from the user, drawing his focus from the tasks at hand. Instead of being the centre of attention, computers should be so natural that they would vanish into the human environment. Computers become not only truly pervasive but also effectively invisible and unobtrusive to the user. This requires not only for smaller, cheaper and low power consumption computers, but also for equally convenient display solutions that can be harmoniously integrated into our surroundings. With the advent of Printed Electronics, new ways to link the physical and the digital worlds became available. By combining common printing techniques such as inkjet printing with electro-optical functional inks, it is starting to be possible not only to mass-produce extremely thin, flexible and cost effective electronic circuits but also to introduce electronic functionalities into products where it was previously unavailable. Indeed, Printed Electronics is enabling the creation of novel sensing and display elements for interactive devices, free of form factor. At the same time, the rise in the availability and affordability of digital fabrication technologies, namely of 3D printers, to the average consumer is fostering a new industrial (digital) revolution and the democratisation of innovation. Nowadays, end-users are already able to custom design and manufacture on demand their own physical products, according to their own needs. In the future, they will be able to fabricate interactive digital devices with user-specific form and functionality from the comfort of their homes. This thesis explores how task-specific, low computation, interactive devices capable of presenting dynamic visual information can be created using Printed Electronics technologies, whilst following an approach based on the ideals behind Personal Fabrication. Focus is given on the use of printed electrochromic displays as a medium for delivering dynamic digital information. According to the architecture of the displays, several approaches are highlighted and categorised. Furthermore, a pictorial computation model based on extended cellular automata principles is used to programme dynamic simulation models into matrix-based electrochromic displays. Envisaged applications include the modelling of physical, chemical, biological, and environmental phenomena.

Multi-level SLA-driven resource management on Cloud Providers

Nowadays, service providers in the Cloud offer complex services ready to be used as it was a commodity like water or electricity to their customers with any other extra effort for them. However, providing these services implies a high management effort which requires a lot of human interaction. Furthermore, an efficient resource management mechanism considering only provider's resources is, though necessary, not enough, because the provider's profit is limited by the amount of resources it owns. Dynamically outsourcing resources to other providers in response to demand variation avoids this problem and makes the provider to get more profit. A key technology for achieving these goals is virtualization which facilitates provider's management and provides on-demand virtual environments, which are isolated and consolidated in order to achieve a better utilization of the provider's resources. Nevertheless, dealing with some virtualization capabilities implies an effort for the user in order to take benefit from them. In order to avoid this problem, we are contributing the research community with a virtualized environment manager which aims to provide virtual machines that fulfils with the user requirements. Another challenge is sharing resources among different federated Cloud providers while exploiting the features of virtualization in a new approach for facilitating providers' management. This project aims for reducing provider's costs and at the same time fulfilling the quality of service agreed with the customers while maximizing the provider's revenue. It considers resource management at several layers, namely locally to each node in the provider, among different nodes in the provider, and among different federated providers. This latter layer supports the novel capabilities of outsourcing when the local resources are not enough to fulfil the users demand, and offering resources to other providers when the local resources are underused.

Efficacy and Safety of Canakinumab Vs Triamcinolone Acetonide in Patients with Gouty Arthritis Unable to Use Nonsteroidal Anti-Inflammatory Drugs and Colchicine, and On Stable Urate Lowering Therapy (ULT) or Unable to Use ULT

Background/Purpose: The primary treatment goals for gouty arthritis (GA) are rapid relief of pain and inflammation during acute attacks, and long-term hyperuricemia management. A post-hoc analysis of 2 pivotal trials was performed to assess efficacy and safety of canakinumab (CAN), a fully human monoclonal anti-IL-1_ antibody, vs triamcinolone acetonide (TA) in GA patients unable to use NSAIDs and colchicine, and who were on stable urate lowering therapy (ULT) or unable to use ULT. Methods: In these 12-week, randomized, multicenter, double-blind, double-dummy, active-controlled studies (_-RELIEVED and _-RELIEVED II), patients had to have frequent attacks (_3 attacks in previous year) meeting preliminary GA ACR 1977 criteria, and were unresponsive, intolerant, or contraindicated to NSAIDs and/or colchicine, and if on ULT, ULT was stable. Patients were randomized during an acute attack to single dose CAN 150 mg s.c. or TA 40 mg i.m. and were redosed "on demand" for each new attack. Patients completing the core studies were enrolled into blinded 12-week extension studies to further investigate on-demand use of CAN vs TA for new attacks. The subpopulation selected for this post-hoc analysis was (a) unable to use NSAIDs and colchicine due to contraindication, intolerance or lack of efficacy for these drugs, and (b) currently on ULT, or contraindication or previous failure of ULT, as determined by investigators. Subpopulation comprised 101 patients (51 CAN; 50 TA) out of 454 total. Results: Several co-morbidities, including hypertension (56%), obesity (56%), diabetes (18%), and ischemic heart disease (13%) were reported in 90% of this subpopulation. Pain intensity (VAS 100 mm scale) was comparable between CAN and TA treatment groups at baseline (least-square [LS] mean 74.6 and 74.4 mm, respectively). A significantly lower pain score was reported with CAN vs TA at 72 hours post dose (1st co-primary endpoint on baseline flare; LS mean, 23.5 vs 33.6 mm; difference _10.2 mm; 95% CI, _19.9, _0.4; P_0.0208 [1-sided]). CAN significantly reduced risk for their first new attacks by 61% vs TA (HR 0.39; 95% CI, 0.17-0.91, P_0.0151 [1-sided]) for the first 12 weeks (2nd co-primary endpoint), and by 61% vs TA (HR 0.39; 95% CI, 0.19-0.79, P_0.0047 [1-sided]) over 24 weeks. Serum urate levels increased for CAN vs TA with mean change from baseline reaching a maximum of _0.7 _ 2.0 vs _0.1 _ 1.8 mg/dL at 8 weeks, and _0.3 _ 2.0 vs _0.2 _ 1.4 mg/dL at end of study (all had GA attack at baseline). Adverse Events (AEs) were reported in 33 (66%) CAN and 24 (47.1%) TA patients. Infections and infestations were the most common AEs, reported in 10 (20%) and 5 (10%) patients treated with CAN and TA respectively. Incidence of SAEs was comparable between CAN (gastritis, gastroenteritis, chronic renal failure) and TA (aortic valve incompetence, cardiomyopathy, aortic stenosis, diarrohea, nausea, vomiting, bicuspid aortic valve) groups (2 [4.0%] vs 2 [3.9%]). Conclusion: CAN provided superior pain relief and reduced risk of new attack in highly-comorbid GA patients unable to use NSAIDs and colchicine, and who were currently on stable ULT or unable to use ULT. The safety profile in this post-hoc subpopulation was consistent with the overall _-RELIEVED and _-RELIEVED II population.

Nonactivated versus thrombin-activated platelets on wound healing and fibroblast-to-myofibroblast differentiation in vivo and in vitro.

Background: Platelet preparations for tissue healing are usually preactivated before application to deliver concentrated growth factors. In this study, the authors investigated the differences between nonactivated and thrombin-activated platelets in wound healing.Methods: The healing effects (i.e., wound closure, myofibroblast formation, and angiogenesis) of nonactivated and thrombin-activated platelets were compared in experimental wounds in diabetic (db/db) animals. In vitro, fibroblast phenotype and function were tested in response to platelets and activated platelets. No treatment served as a negative control.Results: Wounds treated with platelets reached 90 percent closure after 15 days, faster than activated platelets (26 days), and with higher levels of myofibroblasts and angiogenesis. In vitro, platelets enhanced cell migration and induced twofold higher myofibroblast differentiation and contraction compared with activated platelets.Conclusions: Platelets stimulate wound healing more efficiently compared with activated platelets by enhancing fibroblast differentiation and contractile function. Similar levels of growth factors may induce different biological effects when delivered "on demand" rather than in an initial bolus. (Plast. Reconstr. Surg. 129: 46e, 2012.)

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Determinants of demand for antenatal care in Colombia

Even though antenatal care is universally regarded as important, determinants of demand for antenatal care have not been widely studied. Evidence concerning which and how socioeconomic conditions influence whether a pregnant woman attends or not at least one antenatal consultation or how these factors affect the absences to antenatal consultations is very limited. In order to generate this evidence, a two-stage analysis was performed with data from the Demographic and Health Survey carried out by Profamilia in Colombia during 2005. The first stage was run as a logit model showing the marginal effects on the probability of attending the first visit and an ordinary least squares model was performed for the second stage. It was found that mothers living in the pacific region as well as young mothers seem to have a lower probability of attending the first visit but these factors are not related to the number of absences to antenatal consultation once the first visit has been achieved. The effect of health insurance was surprising because of the differing effects that the health insurers showed. Some familiar and personal conditions such as willingness to have the last children and number of previous children, demonstrated to be important in the determination of demand. The effect of mother’s educational attainment was proved as important whereas the father’s educational achievement was not. This paper provides some elements for policy making in order to increase the demand inducement of antenatal care, as well as stimulating research on demand for specific issues on health.

Free-range village chickens on the Accra plains, Ghana: Their contribution to households

A cross-sectional survey investigating the contribution of free-range village chickens to household economies was carried out in four administrative districts within 60km of Accra. Answers were provided by 101 men and 99 women. Nearly all respondents claimed to keep chickens for meat, with a far smaller percentage claiming to keep them for egg production. Over 80% of respondents kept chickens to supplement their incomes. The proportion of the flock eaten varied between administrative areas (p=0.009 and p=0.027), although this was possibly a consequence of differences in consumption patterns between occupation of the respondent, land area cultivated and flock size. The proportion of chickens sold varied as a result of differences in flock size (p=0.013), the proportion sold increasing with number of birds in the flock. Respondents generally agreed that chickens could be sold without difficulty. A majority of chicken sales were from the farm gate, directly to consumers or traders. Sales were on demand or when the owner needed money. Money from the sale was kept by the owner of the chicken and the money was spent on personal needs. The proportion of the flock sold varied between administrative areas (p=0.025) and occupation of the respondent (p=0.040). Respondents describing animal production as their main occupation tended to have greater reliance on chicken sales for their income. Consideration is given to estimating the offtake from the flock and the financial contribution to the household.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Ant larval demand reduces aphid colony growth rates in an ant-aphid interaction

Ants often form mutualistic interactions with aphids, soliciting honeydew in return for protective services. Under certain circumstances, however, ants will prey upon aphids. In addition, in the presence of ants aphids may increase the quantity or quality of honeydew produced, which is costly. Through these mechanisms, ant attendance can reduce aphid colony growth rates. However, it is unknown whether demand from within the ant colony can affect the ant-aphid interaction. In a factorial experiment, we tested whether the presence of larvae in Lasius niger ant colonies affected the growth rate of Aphis fabae colonies. Other explanatory variables tested were the origin of ant colonies (two separate colonies were used) and previous diet (sugar only or sugar and protein). We found that the presence of larvae in the ant colony significantly reduced the growth rate of aphid colonies. Previous diet and colony origin did not affect aphid colony growth rates. Our results suggest that ant colonies balance the flow of two separate resources from aphid colonies- renewable sugars or a protein-rich meal, depending on demand from ant larvae within the nest. Aphid payoffs from the ant-aphid interaction may change on a seasonal basis, as the demand from larvae within the ant colony waxes and wanes.

Alpha, Omega end group functionalization of RAFT polymers based on pentafluorophenyl esters and methane thiosulfonates

While polymers with different functional groups along the backbone have intensively been investigated, there is still a challenge in orthogonal functionalization of the end groups. Such well-defined systems are interesting for the preparation of multiblock (co) polymers or polymer networks, for bio-conjugation or as model systems for examining the end group separation of isolated polymer chains. rnHere, Reversible Addition Fragmentation Chain Transfer (RAFT) polymerization was employed as method to investigate improved techniques for an a, w end group functionalization. RAFT produces polymers terminated in an R group and a dithioester-Z group, where R and Z stem from a suitable chain transfer agent (CTA). rnFor alpha end group functionalization, a CTA with an activated pentafluorophenyl (PFP) ester R group was designed and used for the polymerization of various methacrylate monomers, N-isopropylacrylamide and styrene yielding polymers with a PFP ester as a end group. This allowed the introduction of inert propyl amides, of light responsive diazo compounds, of the dyes NBD, Texas Red, or Oregon Green, of the hormone thyroxin and allowed the formation of multiblocks or peptide conjugates. rnFor w end group functionalization, problems of other techniques were overcome through an aminolysis of the dithioester in the presence of a functional methane thiosulfonate (MTS), yielding functional disulfides. These disulfides were stable under ambient conditions and could be cleaved on demand. Using MTS chemistry, terminal methyl disulfides (enabling self-assembly on planar gold surfaces and ligand substitution on gold and semiconductor nanoparticles), butynyl disulfide end groups (allowing the “clicking” of the polymers onto azide functionalized surfaces and the selective removal through reduction), the bio-target biotin, and the fluorescent dye Texas Red were introduced into polymers. rnThe alpha PFP amidation could be performed under mild conditions, without substantial loss of DTE. This way, a step-wise synthesis produced polymers with two functional end groups in very high yields. rnAs examples, polymers with an anchor group for both gold nanoparticles (AuNP) and CdSe / ZnS semi-conductor nanoparticles (QD) and with a fluorescent dye end group were synthesized. They allowed a NP decoration and enabled an energy transfer from QD to dye or from dye to AuNP. Water-soluble polymers were prepared with two different bio-target end groups, each capable of selectively recognizing and binding a certain protein. The immobilization of protein-polymer-protein layers on planar gold surfaces was monitored by surface plasmon resonance.Introducing two different fluorescent dye end groups enabled an energy transfer between the end groups of isolated polymer chains and created the possibility to monitor the behavior of single polymer chains during a chain collapse. rnThe versatility of the synthetic technique is very promising for applications beyond this work.

Elastic computing on Cloud resources for the CMS experiment

Nowadays, data handling and data analysis in High Energy Physics requires a vast amount of computational power and storage. In particular, the world-wide LHC Com- puting Grid (LCG), an infrastructure and pool of services developed and deployed by a ample community of physicists and computer scientists, has demonstrated to be a game changer in the efficiency of data analyses during Run-I at the LHC, playing a crucial role in the Higgs boson discovery. Recently, the Cloud computing paradigm is emerging and reaching a considerable adoption level by many different scientific organizations and not only. Cloud allows to access and utilize not-owned large computing resources shared among many scientific communities. Considering the challenging requirements of LHC physics in Run-II and beyond, the LHC computing community is interested in exploring Clouds and see whether they can provide a complementary approach - or even a valid alternative - to the existing technological solutions based on Grid. In the LHC community, several experiments have been adopting Cloud approaches, and in particular the experience of the CMS experiment is of relevance to this thesis. The LHC Run-II has just started, and Cloud-based solutions are already in production for CMS. However, other approaches of Cloud usage are being thought of and are at the prototype level, as the work done in this thesis. This effort is of paramount importance to be able to equip CMS with the capability to elastically and flexibly access and utilize the computing resources needed to face the challenges of Run-III and Run-IV. The main purpose of this thesis is to present forefront Cloud approaches that allow the CMS experiment to extend to on-demand resources dynamically allocated as needed. Moreover, a direct access to Cloud resources is presented as suitable use case to face up with the CMS experiment needs. Chapter 1 presents an overview of High Energy Physics at the LHC and of the CMS experience in Run-I, as well as preparation for Run-II. Chapter 2 describes the current CMS Computing Model, and Chapter 3 provides Cloud approaches pursued and used within the CMS Collaboration. Chapter 4 and Chapter 5 discuss the original and forefront work done in this thesis to develop and test working prototypes of elastic extensions of CMS computing resources on Clouds, and HEP Computing “as a Service”. The impact of such work on a benchmark CMS physics use-cases is also demonstrated.