Dynamic control of laser driven proton beams by exploiting self-generated, ultrashort electromagnetic pulses

As part of the ultrafast charge dynamics initiated by high intensity laser irradiations of solid targets,high amplitude EM pulses propagate away from the interaction point and are transported along anystalks and wires attached to the target. The propagation of these high amplitude pulses along a thinwire connected to a laser irradiated target was diagnosed via the proton radiography technique,measuring a pulse duration of 20 ps and a pulse velocity close to the speed of light. The strongelectric field associated with the EM pulse can be exploited for controlling dynamically the protonbeams produced from a laser-driven source. Chromatic divergence control of broadband laser drivenprotons (upto 75% reduction in divergence of >5 MeV protons) was obtained by winding the supportingwire around the proton beam axis to create a helical coil structure. In addition to providingfocussing and energy selection, the technique has the potential to post-accelerate the transiting protonsby the longitudinal component of the curved electric field lines produced by the helical coil lens.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Dynalog: an automated dynamic analysis framework for characterizing android applications

Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

Automated Software Debugging Using Hybrid Static/Dynamic Analysis

With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.

A distributed, compact routing protocol for the Internet

The Internet has grown in size at rapid rates since BGP records began, and continues to do so. This has raised concerns about the scalability of the current BGP routing system, as the routing state at each router in a shortest-path routing protocol will grow at a supra-linearly rate as the network grows. The concerns are that the memory capacity of routers will not be able to keep up with demands, and that the growth of the Internet will become ever more cramped as more and more of the world seeks the benefits of being connected. Compact routing schemes, where the routing state grows only sub-linearly relative to the growth of the network, could solve this problem and ensure that router memory would not be a bottleneck to Internet growth. These schemes trade away shortest-path routing for scalable memory state, by allowing some paths to have a certain amount of bounded “stretch”. The most promising such scheme is Cowen Routing, which can provide scalable, compact routing state for Internet routing, while still providing shortest-path routing to nearly all other nodes, with only slightly stretched paths to a very small subset of the network. Currently, there is no fully distributed form of Cowen Routing that would be practical for the Internet. This dissertation describes a fully distributed and compact protocol for Cowen routing, using the k-core graph decomposition. Previous compact routing work showed the k-core graph decomposition is useful for Cowen Routing on the Internet, but no distributed form existed. This dissertation gives a distributed k-core algorithm optimised to be efficient on dynamic graphs, along with with proofs of its correctness. The performance and efficiency of this distributed k-core algorithm is evaluated on large, Internet AS graphs, with excellent results. This dissertation then goes on to describe a fully distributed and compact Cowen Routing protocol. This protocol being comprised of a landmark selection process for Cowen Routing using the k-core algorithm, with mechanisms to ensure compact state at all times, including at bootstrap; a local cluster routing process, with mechanisms for policy application and control of cluster sizes, ensuring again that state can remain compact at all times; and a landmark routing process is described with a prioritisation mechanism for announcements that ensures compact state at all times.

Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

In recent years, there has been an enormous growth of location-aware devices, such as GPS embedded cell phones, mobile sensors and radio-frequency identification tags. The age of combining sensing, processing and communication in one device, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Wireless Sensor Network (mWSN) applications. As computing, sensing and communication become more ubiquitous, trajectory privacy becomes a critical piece of information and an important factor for commercial success. While on the move, sensor nodes continuously transmit data streams of sensed values and spatiotemporal information, known as ``trajectory information". If adversaries can intercept this information, they can monitor the trajectory path and capture the location of the source node. This research stems from the recognition that the wide applicability of mWSNs will remain elusive unless a trajectory privacy preservation mechanism is developed. The outcome seeks to lay a firm foundation in the field of trajectory privacy preservation in mWSNs against external and internal trajectory privacy attacks. First, to prevent external attacks, we particularly investigated a context-based trajectory privacy-aware routing protocol to prevent the eavesdropping attack. Traditional shortest-path oriented routing algorithms give adversaries the possibility to locate the target node in a certain area. We designed the novel privacy-aware routing phase and utilized the trajectory dissimilarity between mobile nodes to mislead adversaries about the location where the message started its journey. Second, to detect internal attacks, we developed a software-based attestation solution to detect compromised nodes. We created the dynamic attestation node chain among neighboring nodes to examine the memory checksum of suspicious nodes. The computation time for memory traversal had been improved compared to the previous work. Finally, we revisited the trust issue in trajectory privacy preservation mechanism designs. We used Bayesian game theory to model and analyze cooperative, selfish and malicious nodes' behaviors in trajectory privacy preservation activities.

Evolution and challenges of dynamic global vegetation models for some aspects of plant physiology and elevated atmospheric CO2.

Dynamic global vegetation models (DGVMs) simulate surface processes such as the transfer of energy, water, CO2, and momentum between the terrestrial surface and the atmosphere, biogeochemical cycles, carbon assimilation by vegetation, phenology, and land use change in scenarios of varying atmospheric CO2 concentrations. DGVMs increase the complexity and the Earth system representation when they are coupled with atmospheric global circulation models (AGCMs) or climate models. However, plant physiological processes are still a major source of uncertainty in DGVMs. The maximum velocity of carboxylation (Vcmax), for example, has a direct impact over productivity in the models. This parameter is often underestimated or imprecisely defined for the various plant functional types (PFTs) and ecosystems. Vcmax is directly related to photosynthesis acclimation (loss of response to elevated CO2), a widely known phenomenon that usually occurs when plants are subjected to elevated atmospheric CO2 and might affect productivity estimation in DGVMs. Despite this, current models have improved substantially, compared to earlier models which had a rudimentary and very simple representation of vegetation?atmosphere interactions. In this paper, we describe this evolution through generations of models and the main events that contributed to their improvements until the current state-of-the-art class of models. Also, we describe some main challenges for further improvements to DGVMs.

Dynamic Modeling and Seasonal Performance Evaluation of Air-to-Water Heat Pump Systems

In this Thesis a series of numerical models for the evaluation of the seasonal performance of reversible air-to-water heat pump systems coupled to residential and non-residential buildings are presented. The exploitation of the energy saving potential linked to the adoption of heat pumps is a hard task for designers due to the influence on their energy performance of several factors, like the external climate variability, the heat pump modulation capacity, the system control strategy and the hydronic loop configuration. The aim of this work is to study in detail all these aspects. In the first part of this Thesis a series of models which use a temperature class approach for the prediction of the seasonal performance of reversible air source heat pumps are shown. An innovative methodology for the calculation of the seasonal performance of an air-to-water heat pump has been proposed as an extension of the procedure reported by the European standard EN 14825. This methodology can be applied not only to air-to-water single-stage heat pumps (On-off HPs) but also to multi-stage (MSHPs) and inverter-driven units (IDHPs). In the second part, dynamic simulation has been used with the aim to optimize the control systems of the heat pump and of the HVAC plant. A series of dynamic models, developed by means of TRNSYS, are presented to study the behavior of On-off HPs, MSHPs and IDHPs. The main goal of these dynamic simulations is to show the influence of the heat pump control strategies and of the lay-out of the hydronic loop used to couple the heat pump to the emitters on the seasonal performance of the system. A particular focus is given to the modeling of the energy losses linked to on-off cycling.

Analisi e studio computazionale di solver per problemi di routing di interesse industriale

Il Routing rappresenta uno dei problemi più studiati nell’ambito della Ricerca Operativa in quanto offre molteplici possibilità di ottimizzazione da cui possono derivare altrettanti vantaggi per le aziende che decidono di gestirlo in maniera strutturata. Uno dei principali ambiti di applicazione del routing è la pianificazione operativa del trasporto merci a clienti sparsi in un determinato territorio. Ci sono aziende che devono organizzare la loro Logistica distributiva ogni giorno. Ormai è diventato evidente che la realizzazione di questo processo mediante modalità “standard”, senza l’utilizzo di appositi strumenti di ottimizzazione, non solo porta alla perdita di occasioni importanti in termini di vantaggi raggiungibili, ma è anche molto più dispendiosa a livello di tempo richiesto. Molte aziende si stanno quindi affidando a soluzioni SW che si vadano ad integrare con i loro processi decisionali. Questi sistemi hanno alla base delle componenti algoritmiche in grado di trovare la migliore soluzione possibile per la tipologia specifica di Routing da affrontare. Per questi motivi, lo sviluppo di algoritmi in grado di risolvere questo problema rappresenta una parte consistente della letteratura scientifica in ambito di ottimizzazione. In questo elaborato si andranno a definire le principali caratteristiche di un problema di Routing in forma base e nelle sue varianti principali. Si descriveranno le caratteristiche dei problemi di Routing incontrati da Optit S.r.l, un’azienda che opera nel settore dello sviluppo di soluzioni SW di ottimizzazione. Nel fare ciò, si cercherà di trovare sovrapposizione con quanto descritto in letteratura. Infine, si descriveranno alcuni solver Open-Source per risolvere problemi di Routing e si mostreranno i risultati da essi ottenuti su alcuni casi di interesse industriale.

Caffeine As An Indicator Of Estrogenic Activity In Source Water.

Caffeine has already been used as an indicator of anthropogenic impacts, especially the ones related to the disposal of sewage in water bodies. In this work, the presence of caffeine has been correlated with the estrogenic activity of water samples measured using the BLYES assay. After testing 96 surface water samples, it was concluded that caffeine can be used to prioritize samples to be tested for estrogenic activity in water quality programs evaluating emerging contaminants with endocrine disruptor activity.

Evaluation Of Fe Uptake And Translocation In Transgenic And Non-transgenic Soybean Plants Using Enriched Stable (57)fe As A Tracer.

A tracer experiment is carried out with transgenic T (variety M 7211 RR) and non-transgenic NT (variety MSOY 8200) soybean plants to evaluate if genetic modification can influence the uptake and translocation of Fe. A chelate of EDTA with enriched stable (57)Fe is applied to the plants cultivated in vermiculite plus substrate and the (57)Fe acts as a tracer. The exposure of plants to enriched (57)Fe causes the dilution of the natural previously existing Fe in the plant compartments and then the changed Fe isotopic ratio ((57)Fe/(56)Fe) is measured using a quadrupole-based inductively coupled plasma mass spectrometer equipped with a dynamic reaction cell (DRC). Mathematical calculations based on the isotope dilution methodology allow distinguishing the natural abundance Fe from the enriched Fe (incorporated during the experiment). The NT soybean plants acquire higher amounts of Fe from natural abundance (originally present in the soil) and from enriched Fe (coming from the (57)Fe-EDTA during the experiment) than T soybean ones, demonstrating that the NT soybean plants probably absorb higher amounts of Fe, independently of the source. The percentage of newly incorporated Fe (coming from the treatment) was approximately 2.0 and 1.1% for NT and T soybean plants, respectively. A higher fraction (90.1%) of enriched Fe is translocated to upper parts, and a slightly lower fraction (3.8%) is accumulated in the stems by NT plants than by T ones (85.1%; 5.1%). Moreover, in both plants, the Fe-EDTA facilitates the transport and translocation of Fe to the leaves. The genetic modification is probably responsible for differences observed between T and NT soybean plants.

Reference Values For High-density Lipoprotein Particle Size And Volume By Dynamic Light Scattering In A Brazilian Population Sample And Their Relationships With Metabolic Parameters.

Current data indicate that the size of high-density lipoprotein (HDL) may be considered an important marker for cardiovascular disease risk. We established reference values of mean HDL size and volume in an asymptomatic representative Brazilian population sample (n=590) and their associations with metabolic parameters by gender. Size and volume were determined in HDL isolated from plasma by polyethyleneglycol precipitation of apoB-containing lipoproteins and measured using the dynamic light scattering (DLS) technique. Although the gender and age distributions agreed with other studies, the mean HDL size reference value was slightly lower than in some other populations. Both HDL size and volume were influenced by gender and varied according to age. HDL size was associated with age and HDL-C (total population); non- white ethnicity and CETP inversely (females); HDL-C and PLTP mass (males). On the other hand, HDL volume was determined only by HDL-C (total population and in both genders) and by PLTP mass (males). The reference values for mean HDL size and volume using the DLS technique were established in an asymptomatic and representative Brazilian population sample, as well as their related metabolic factors. HDL-C was a major determinant of HDL size and volume, which were differently modulated in females and in males.

Interaction Between Fiscal And Monetary Policy In A Dynamic Nonlinear Model.

The objective of this study is to verify the dynamics between fiscal policy, measured by public debt, and monetary policy, measured by a reaction function of a central bank. Changes in monetary policies due to deviations from their targets always generate fiscal impacts. We examine two policy reaction functions: the first related to inflation targets and the second related to economic growth targets. We find that the condition for stable equilibrium is more restrictive in the first case than in the second. We then apply our simulation model to Brazil and United Kingdom and find that the equilibrium is unstable in the Brazilian case but stable in the UK case.

Key Participants Of The Tumor Microenvironment Of The Prostate: An Approach Of The Structural Dynamic Of Cellular Elements And Extracellular Matrix Components During Epithelial-stromal Transition.

Cancer is a multistep process that begins with the transformation of normal epithelial cells and continues with tumor growth, stromal invasion and metastasis. The remodeling of the peritumoral environment is decisive for the onset of tumor invasiveness. This event is dependent on epithelial-stromal interactions, degradation of extracellular matrix components and reorganization of fibrillar components. Our research group has studied in a new proposed rodent model the participation of cellular and molecular components in the prostate microenvironment that contributes to cancer progression. Our group adopted the gerbil Meriones unguiculatus as an alternative experimental model for prostate cancer study. This model has presented significant responses to hormonal treatments and to development of spontaneous and induced neoplasias. The data obtained indicate reorganization of type I collagen fibers and reticular fibers, synthesis of new components such as tenascin and proteoglycans, degradation of basement membrane components and elastic fibers and increased expression of metalloproteinases. Fibroblasts that border the region, apparently participate in the stromal reaction. The roles of each of these events, as well as some signaling molecules, participants of neoplastic progression and factors that promote genetic reprogramming during epithelial-stromal transition are also discussed.

Brincar : uma opção para a interação entre mãe ouvinte/filho surdo

Universidade Estadual de Campinas . Faculdade de Educação Física