The Impacts of Airport Centrality in the EU Network and Inter- Airport Competition on Airport Efficiency

In this paper we study the relationship between airport efficiency and two factors: an airport’s centrality in the EU network, and the intensity of competition from alternative airports in the same catchment area. We apply a two-stage econometric model based on the Simar & Wilson (2007) bootstrap procedure to a balanced sample of 57 European airports. We also design and compute our own measures of airport centrality and competition. The results show that efficiency is positively related to centrality in the European network, as measured by a weighted sum of minimal paths passing through the airport in question. The intensity of competition between airports also has a positive effect on efficiency. Our analysis suggests that air transportation policies should focus on increasing competition within important catchment areas (e.g., by investing in infrastructure facilitating access to alternative airports) and enhancing the connectivity of the EU network (e.g., by subsidizing new point-to-point connections between airports with capacity to spare).air transportation, efficiency, network centrality, inter – airports competition.

DEALING WITH NEXT-GENERATION MALWARE

Malicious programs are a serious problem that threatens the security of billions of Internet users. Today's malware authors are motivated by the easy financial gain they can obtain by selling on the underground market the information stolen from the infected hosts. To maximize their profit, miscreants continuously improve their creations to make them more and more resilient against anti-malware solutions. This increasing sophistication in malicious code led to next-generation malware, a new class of threats that exploit the limitations of state-of-the-art anti-malware products to bypass security protections and eventually evade detection. Unfortunately, current anti-malware technologies are inadequate to face next-generation malware. For this reason, in this dissertation we propose novel techniques to address the shortcomings of defensive technologies and to enhance current state-of-the-art security solutions. Dynamic behavior-based analysis is a very promising approach to automatically understand the behaviors a malicious program may exhibit at run-time. However, behavior-based solutions still present several limitations. First of all, these techniques may give incomplete results because the execution environments in which they are applied are synthetic and do not faithfully resemble the environments of end-users, the intended targets of the malicious activities. To overcome this problem, we present a new framework for improving behavior-based analysis of suspicious programs, that allows an end-user to delegate security labs the execution and the analysis of a program and to force the program to behave as if it were executed directly in the environment of the former. Our evaluation demonstrated that the proposed framework allows security labs to improve the completeness of the analysis, by analyzing a piece of malware on behalf of multiple end-users simultaneously, while performing a fine-grained analysis of the behavior of the program with no computational cost for the end-users. Another drawback of state-of-the-art defensive solutions is non-transparency: malicious programs are often able to determine that their execution is being monitored, and thus they can tamper with the analysis to avoid detection, or simply behave innocuously to mislead the anti-malware tool. At this aim, we propose a generic framework to perform complex dynamic system-level analyses of deployed production systems. By leveraging hardware support for virtualization available nowadays on all commodity machines, our framework is completely transparent to the system under analysis and it guarantees isolation of the analysis tools running on top of it. The internals of the kernel of the running system need not to be modified and the whole platform runs unaware of the framework. Once the framework has been installed, even kernel-level malware cannot detect it or affect its execution. This is accomplished by installing a minimalistic virtual machine monitor and migrating the system, as it runs, into a virtual machine. To demonstrate the potentials of our framework we developed an interactive kernel debugger, named HyperDbg. As HyperDbg can be used to monitor any critical system component, it is suitable to analyze even malicious programs that include kernel-level modules. Despite all the progress anti-malware technologies can make, perfect malware detection remains an undecidable problem. When it is not possible to prevent a malicious threat from infecting a system, post-infection remediation remains the only viable possibility. However, if the machine has already been compromised, the execution of the remediation tool could be tampered by the malware that is running on the system. To address this problem we present Conqueror, a software-based attestation scheme for tamper-proof code execution on untrusted legacy systems. Besides providing load-time attestation of a piece of code, Conqueror also ensures run-time integrity. Conqueror constitutes a valid alternative to trusted computing platforms, for systems lacking specialized hardware for attestation. We implemented a prototype, specific for the Intel x86 architecture, and evaluated the proposed scheme. Our evaluation showed that, compared to competitors, Conqueror is resistant to both static and dynamic attacks. We believe Conqueror and our transparent dynamic analysis framework constitute important building blocks for creating new security applications. To demonstrate this claim, we leverage the aforementioned solutions to realize HyperSleuth, an infrastructure to securely perform live forensic analysis of potentially compromised production systems. HyperSleuth provides a trusted execution environment that guarantees an attacker controlling the system cannot interfere with the analysis and cannot tamper with the results. The framework can be installed as the system runs, without a reboot and without loosing any volatile data. Moreover, the analysis can be periodically and safely interrupted to resume normal execution of the system. On top of HyperSleuth we implemented three forensic analysis tools: a lazy physical memory dumper, a lie detector, and a system call tracer. The experimental evaluation we conducted demonstrated that even time consuming analyses, such as the dump of the content of the physical memory, can be securely performed without interrupting the services offered by the system

Tailoring parameter distributions to specific germplasm : impact on crop model-based ideotyping

Crop models are increasingly used to identify promising ideotypes for given environmental and management conditions. However, uncertainty must be properly managed to maximize the in vivo realizability of ideotypes. We focused on the impact of adopting germplasm-specific distributions while exploring potential combinations of traits. A field experiment was conducted on 43 Italian rice varieties representative of the Italian rice germplasm, where the following traits were measured: light extinction coefficient, radiation use efficiency, specific leaf area at emergence and tillering. Data were used to derive germplasm-specific distributions, which were used to re-run a previous modelling experiment aimed at identifying optimal combinations of plant trait values. The analysis, performed using the rice model WARM and sensitivity analysis techniques, was conducted under current conditions and climate change scenarios. Results revealed that the adoption of germplasm-specific distributions may markedly affect ideotyping, especially for the identification of most promising traits. A re-ranking of some of the most relevant parameters was observed (radiation use efficiency shifted from 4th to 1st), without clear relationships between changes in rankings and differences in distributions for single traits. Ideotype profiles (i.e., values of the ideotype traits) were instead more consistent, although differences in trait values were found

Analysis and modeling of processes involved with salt tolerance and rice

Salinity is a worldwide problem for rice (Oryza sativa L.) cultivation, and a number of breeding programs targeting increased salt tolerance are ongoing. A new trait-based mathematical model for salt stress on rice was recently proposed, characterized by a high level of detail in the description of physiological mechanisms dealing with crop response to salinity. In this study, dedicated growth chamber experiments were performed where three rice cultivars with different degrees of tolerance were grown under different salinity levels. The aim was to improve the understanding of physiological mechanisms like Na+ uptake and sequestration in structural tissues, and to validate the model using new datasets where temporal dynamics in plant response to salt stress were analyzed. Model evaluation demonstrated strong agreement between measured and simulated dry weights of plant organs (e.g., R2 = 0.88-0.97 for aboveground biomass), [Na+] in plant tissues (R2 = 0.73-0.88), and green leaf area index (R2 = 0.71-0.99). These results demonstrate the reliability of the model and support its adoption within studies aimed at analyzing or predicting the response of different cultivars to temporal dynamics of Na+ concentration in soil and water

Standardization of the HbA2 assay

Background A project for the standardization of HbA2 was launched by the IFCC back in 2004. Materials and methods In this work we report on the state-of-the-art of the project on standardization of HbA2. Data obtained from various EQAS studies, and from previous experimental evaluations, are presented. Results We have proven that biases between various commercial methods are still currently significant. We have also shown that calibration by commutable control materials may halve the inter-method variability. Conclusions The foundation of the reference system for HbA2, together with a brief preliminary presentation of the proposed primary reference measurement procedure based on ID-MS are outlined

Trait-based model development to support breeding programs : A case study for salt tolerance and rice

Eco-physiological models are increasingly used to analyze G 7 E 7 M interactions to support breeding programs via the design of ideotypes for specific contexts. However, available crop models are only partly suitable for this purpose, since they often lack clear relationships between parameters and traits breeders are working on. Taking salt stress tolerance and rice as a case study, we propose a paradigm shift towards the building of ideotyping-specific models explicitly around traits involved in breeding programs. Salt tolerance is a complex trait relying on different physiological processes that can be alternatively selected to improve the overall crop tolerance. We developed a new model explicitly accounting for these traits and we evaluated its performance using data from growth chamber experiments (e.g., R2 ranged from 0.74 to 0.94 for the biomass of different plant organs). Using the model, we were able to show how an increase in the overall tolerance can derive from completely different physiological mechanisms according to soil/water salinity dynamics. The study demonstrated that a trait-based approach can increase the usefulness of mathematical models for supporting breeding programs

The Impacts of Airport Centrality in the EU Network and Inter- Airport Competition on Airport Efficiency

In this paper we study the relationship between airport efficiency and two factors: an airport’s centrality in the EU network, and the intensity of competition from alternative airports in the same catchment area. We apply a two-stage econometric model based on the Simar & Wilson (2007) bootstrap procedure to a balanced sample of 57 European airports. We also design and compute our own measures of airport centrality and competition. The results show that efficiency is positively related to centrality in the European network, as measured by a weighted sum of minimal paths passing through the airport in question. The intensity of competition between airports also has a positive effect on efficiency. Our analysis suggests that air transportation policies should focus on increasing competition within important catchment areas (e.g., by investing in infrastructure facilitating access to alternative airports) and enhancing the connectivity of the EU network (e.g., by subsidizing new point-to-point connections between airports with capacity to spare)

Anemia a cellule falciformi e sindromi correlate: aggiornamenti e prospettive

The presence of hemoglobin S (HbS) in blood is responsible for sickle cell disease when its concentration, for the presence of two copies of HbS gene or one copy of HbS plus another \u3b2-globin variant (such as hemoglobin C or \u3b2-thalassemia), is markedly increased. In this report, we reviewed some recent epidemiological data on the disease prevalence, we discussed pre-analytical as well analytical aspects, relevant to the correct measurement of HbS in blood, and we summarized some important aspects for the management of the sickling crises and for the current and future therapy of this disease

Inhibition of the Nicotinic Acetylcholine Receptors by Cobra Venom α-Neurotoxins: Is There a Perspective in Lung Cancer Treatment?

Nicotine exerts its oncogenic effects through the binding to nicotinic acetylcholine receptors (nAChRs) and the activation of downstream pathways that block apoptosis and promote neo-angiogenesis. The nAChRs of the α7 subtype are present on a wide variety of cancer cells and their inhibition by cobra venom neurotoxins has been proposed in several articles and reviews as a potential innovative lung cancer therapy. However, since part of the published results was recently retracted, we believe that the antitumoral activity of cobra venom neurotoxins needs to be independently re-evaluated

The Impacts of Airport Centrality in the EU Network and Inter- Airport Competition on Airport Efficiency

In this paper we study the relationship between airport efficiency and two factors: an airport’s centrality in the EU network, and the intensity of competition from alternative airports in the same catchment area. We apply a two-stage econometric model based on the Simar & Wilson (2007) bootstrap procedure to a balanced sample of 57 European airports. We also design and compute our own measures of airport centrality and competition. The results show that efficiency is positively related to centrality in the European network, as measured by a weighted sum of minimal paths passing through the airport in question. The intensity of competition between airports also has a positive effect on efficiency. Our analysis suggests that air transportation policies should focus on increasing competition within important catchment areas (e.g., by investing in infrastructure facilitating access to alternative airports) and enhancing the connectivity of the EU network (e.g., by subsidizing new point-to-point connections between airports with capacity to spare)