‘Podracing’: experimenting with mobile TV content consumption and delivery methods

Recently, mobile TV has been launched in several countries. While mobile TV integrates television contents into mobile phones, the most personal of communication devices, it becomes interesting to know how this feature will be used throughout the day and in varying contexts of everyday life. This paper presents empirical results on the use of mobile TV with different delivery mechanisms and both quantitative and qualitative results on how end-users prefer to use mobile TV contents in different situations. The data is based on ongoing empirical research in Finland in 2006 and 2007. The mobile TV services under study included both news and entertainment contents, and were tested in 3G, DVB-H and Wi-Fi networks using different delivery paradigms: broadcast, on-demand and download. To explore the use of different delivery methods and content consumption, we have developed a mobile TV service protoype, called Podracing. The analysis shows that users appreciated up-to-date information and information-rich media forms and contents especially for mobile news delivery. There was high demand for only the latest news on mobiles. The real-time property was considered important. Most of the users looked at the headlines or followed the news several times a day – much more often than the traditional TV and news prime times would allow.     

Multi-objective Swarm Intelligence schedulers for online scientific Clouds

Cloud Computing is a promising paradigm for parallel computing. However, as Cloud-based services become more dynamic, resource provisioning in Clouds becomes more challenging. The paradigm, with its promise of virtually infinite resources, seems to suit well in solving resource greedy scientific computing problems. In a Cloud, an appropriate number of Virtual Machines (VM) is created and allocated in physical resources for executing jobs. This work focuses on the Infrastructure as a Service (IaaS) model where custom VMs are launched in appropriate hosts available in a Cloud to execute scientific experiments coming from multiple users. Finding optimal solutions to allocate VMs to physical resources is an NP-complete problem, and therefore many heuristics have been developed. In this work, we describe and evaluate two Cloud schedulers based on Swarm Intelligence (SI) techniques, particularly Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). The main performance metrics to study are the number of serviced users by the Cloud and the total number of created VMs in online (non-batch) scheduling scenarios. We also perform a sensitivity analysis by varying the specific-parameter values of each algorithm to evaluate the impact on the performance of the two objective metrics. The intra-Cloud network traffic is also measured. Simulated experiments performed using CloudSim and job data from real scientific problems show that the use of SI-based techniques succeeds in balancing the studied metrics compared to Genetic Algorithms.     

A comparative organic geochemical study of oils seeps in Western Greece

Samples from three oil shows in Western Greece were studied following a suite of analytical geochemical procedures, aiming to reveal the origin of the organic matter and characterize its depositional environment. The authors’ findings were compared, and confirmed to a great extent, to geochemical results from previously published studies. Certain compositional differences exist between the three oil shows, reflecting different source rock and/or different facies. The influence of different analytical methodologies commonly used to separate compound groups (saturates, aromatics, resins, asphaltenes) on the obtained geochemical indices was also examined. The results demonstrate that bulk composition of maltenes, as well as most biomarker indices, are not affected significantly by the employed group-type separation procedures.     

The vicious cycle of vitamin a deficiency: A review

Vitamin A deficiency (VAD) is a serious and widespread public health problem and the leading cause of preventable blindness in young children. It is also associated with increased rates of death from severe infections, especially in developing countries. Over the past 35 years, researchers have examined the numerous activities of vitamin A in different tissues of the human body. VAD can lead to a series of ocular symptoms, anemia, and weak resistance to infection, which can increase the severity of infectious diseases and the risk of death. Cell development, vision, growth, and normal metabolism are among the vital processes that are insufficiently supported in the presence of VAD. VAD leads to impaired tissue function especially during the developmental periods of infancy, childhood, pregnancy, and lactation. We describe a multidirectional model of VAD that demonstrates how VAD can have progressive, negative effects on vital processes of the human body throughout the life cycle. This model starts with impaired intake and its link to decreased absorption and digestion and includes outcomes such as malnutrition, inflammation, and improper growth processes, including possible mechanisms. Together, these clinical and biochemical manifestations contribute to the vicious cycle of VAD.     

Issues related to the computer realization of a multidisciplinary and multiobjective optimization system

Issues and novel ideas to be considered when developing computer realizations of complex multidisciplinary and multiobjective optimization systems are introduced. The aim is to discuss computer realizations that make possible both computationally efficient multidisciplinary analysis and multiobjective optimization of real world problems. We introduce software tools that make typically very time-consuming simulation processes more effective and, thus, enable even interactive multiobjective optimization with a real decision maker. In this paper, we first define a multidisciplinary and multiobjective optimization system and after that present an implementation overview of such problems including basic components participating in the solution process. Furthermore, interfaces and data flows between the components are described. A couple of important features related to the implementation are discussed in detail, for example, the usage of automatic differentiation. Finally, the ideas presented are illustrated with an industrial multiobjective optimization problem, when we describe numerical experiments related to quality properties in paper making.     

Multiobjective process line optimization under uncertainty applied to papermaking

Multiobjective optimization methodology for the development of the papermaking process is considered. The aim is to find efficient and reliable solution procedures for the process line model consisting of sequential unit-process models; some of them based on physics, whereas others on experimental data. By the consequence of modeling procedures, nonphysical states or inherited from modeling data in statistical case, the unit-process models may suffer from undesired unreliability. To control the uncertainty resulting from the unit-process models, a new multiobjective optimization approach is introduced where both the papermaking targets as well as the uncertainty related unit-process models are simultaneously taken into account. We illustrate the solution process by numerical examples related to the quality of the produced paper.     

BET Inhibition Upregulates SIRT1 and Alleviates Inflammatory Responses

Control of histone acetylation is a part of the epigenetic mechanism that regulates gene expression and chromatin architecture. The members of the bromodomain and extra terminal domain (BET) protein family are a group of epigenetic readers that recognize histone acetylation, whereas histone deacetyl‐ ases such as sirtuin 1 (SIRT1) function as epigenetic erasers. We observed that BET inhibition by the specific inhibitor JQ1 upregulated SIRT1 expression and activated SIRT1. Moreover, we observed that BET inhibition functionally reversed the pro‐inflammatory effect of SIRT1 inhibition in a cellular lung disease model. SIRT1 activation is desirable in many age‐related, metabolic and inflammatory diseases; our results suggest that BET protein inhibition would be beneficial in treatment of those conditions. Most importantly, our findings demonstrate a novel mechanism of SIRT1 activation by inhibition of the BET proteins.     

Modulation of Aβ42 Aggregation Kinetics and Pathway by Low-Molecular-Weight Inhibitors

The aggregation of amyloid-β 42 (Aβ42) is directly related to the pathogenesis of Alzheimer's disease. Here, we have investigated the early stages of the aggregation process, during which most of the cytotoxic species are formed. Aβ42 aggregation kinetics, characterized by the quantification of Aβ42 monomer consumption, were tracked by real-time solution NMR spectroscopy (RT-NMR) allowing the impact that low-molecular-weight (LMW) inhibitors and modulators exert on the aggregation process to be analysed. Distinct differences in the Aβ42 kinetic profiles were apparent and were further investigated kinetically and structurally by using thioflavin T (ThT) and transmission electron microscopy (TEM), respectively. LMW inhibitors were shown to have a differential impact on early-state aggregation. Insight provided here could direct future therapeutic design based on kinetic profiling of the process of fibril formation.