Hewlett-Packard (Italy)

Specific immunotherapy is an efficient treatment for patients suffering from type I allergy. The mechanisms underlying successful immunotherapy are assumed to operate at the level of T helper cells, leading to a modulation of the immune response to allergens. During immunotherapy, increasing doses of allergens are given on a regular basis, and the beneficial effects for the patient depend on the concentration of allergen used. On the other hand, the risk of IgE-mediated anaphylactic side effects also increase with the amount of allergen applied per injection. Therefore, we have proposed the use of hypoallergenic (low IgE binding activity) forms of allergens for immunotherapy. We evaluated by site-directed mutagenesis the contributions of individual amino acid residues/positions for IgE binding to Bet v 1, the major allergen of birch pollen. We found that IgE binding to Bet v 1 depended on at least six amino acid residues/positions. Immunoblot analyses and inhibition experiments showed that the multiple-point Bet v 1 mutant exhibited extremely low reactivity with serum IgE from birch pollen-allergic patients. In vivo (skin prick) tests showed that the potency of the multiple-point mutant to induce typical urticarial type I reactions in pollen-allergic patients was significantly lower than for wild-type Bet v 1. Proliferation assays of allergen-specific T cell clones demonstrated that these six amino acid exchanges in the Bet v 1 sequence did not influence T cell recognition. Thus, the Bet v 1 six-point mutant displayed significantly reduced IgE binding activity, but conserved T cell activating capacity, which is necessary for immunomodulation. The approach described here may be generally applied to produce allergen variants to be used in a safe therapy form of immediate-type allergies.

Abstract The paper presents a parallel programming methodology that ensures easy programming, efficiency and portability of programs to different machines belonging to the class of the general‐purpose, distributed‐memory, MIMD architectures. The methodology is based on the definition of a new, high‐level, explicitly parallel language, called P 3 L, and of a set of static tools that automatically adapt the program features for each target architecture. P 3 L does not require programmers to specify process activations, the actual parallelism degree, scheduling, or interprocess communications, i.e. all those features that need to be adjusted to harness each specific target machine. Parallelism is, on the other hand, expressed in a structured and qualitative way, by hierarchical composition of a restricted set of language constructs, corresponding to those forms of parallelism that are frequently encountered in parallel applications, and that can be efficiently implemented. The efficient portability of P 3 L applications is guaranteed by the compiler along with the novel structure of the support. The compiler automatically adapts the program features for each specific architecture, using the costs (in terms of performance) of the low‐level mechanisms exported by the architecture itself. In our methodology, these costs, along with other features of the architecture, are viewed through an abstract machine, whose interface is used by the compiler to produce the final object code.

Data centres are powerful ICT facilities which constantly evolve in size, complexity, and power consumption. At the same time users' and operators' requirements become more and more complex. However, existing data centre frameworks do not typically take energy consumption into account as a key parameter of the data centre's configuration. To lower the power consumption while fulfilling performance requirements we propose a flexible and energy-aware framework for the (re)allocation of virtual machines in a data centre. The framework, being independent from the data centre management system, computes and enacts the best possible placement of virtual machines based on constraints expressed through service level agreements. The framework's flexibility is achieved by decoupling the expressed constraints from the algorithms using the Constraint Programming (CP) paradigm and programming language, basing ourselves on a cluster management library called Entropy. Finally, the experimental and simulation results demonstrate the effectiveness of this approach in achieving the pursued energy optimization goals.

The influence of mobile phase composition variation, organic solvent type, and the concentration of buffer salts on the magnitude of the electroosmotic flow (EOF) velocity, retention, and selectivity in capillary electrochromatography (CEC) has been investigated systematically. The observed change in EOF is explained in terms of change of solvent and stationary phase properties. These findings provide guidelines for the practitioner to select optimal conditions for CEC separations. On the other hand, it is demonstrated that stationary phase properties also have a profound effect on EOF velocity, solute retention, and selectivity of separation. It is demonstrated that the column packed bed of silica-based reversed-phase particles is the main contributor to EOF in CEC. Variation of stationary phases in CEC can be used in a similar way as in HPLC to improve the selectivity of separation of neutral substances. This also applies to the separation of weakly basic substances like triazines. © 1997 John Wiley & Sons, Inc. J Micro Sep 9: 399–408, 1997

This paper focuses on energy efficiency aspects and related benefits of radio-access-network-as-a-service (RANaaS) implementation (using commodity hardware) as architectural evolution of LTE-advanced networks toward 5G infrastructure. RANaaS is a novel concept introduced recently, which enables the partial centralization of RAN functionalities depending on the actual needs as well as on network characteristics. In the view of future definition of 5G systems, this cloud-based design is an important solution in terms of efficient usage of network resources. The aim of this paper is to give a vision of the advantages of the RANaaS, to present its benefits in terms of energy efficiency and to propose a consistent system-level power model as a reference for assessing innovative functionalities toward 5G systems. The incremental benefits through the years are also discussed in perspective, by considering technological evolution of IT platforms and the increasing matching between their capabilities and the need for progressive virtualization of RAN functionalities. The description is complemented by an exemplary evaluation in terms of energy efficiency, analyzing the achievable gains associated with the RANaaS paradigm.

Until recently, there have been relatively few studies exploring the power consumption of ICT resources in data centres. In this paper, we propose a methodology to capture the behaviour of most relevant energy-related ICT resources in data centres and present a generic model for them. This is achieved by decomposing the design process into four modelling phases. Furthermore, unlike the state-of-the-art approaches, we provide detailed power consumption models at server and storage levels. We evaluate our model for different types of servers and show that it suffers from an error rate of 2% in the best case, and less than 10% in the worst case.

Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requirements on future 6G mobile network architectures. To meet these demands, it is essential to transcend classical boundaries and integrate communication, computation, control, and intelligence. This paper presents the 6G-GOALS approach to goal-oriented and semantic communications for AI-Native 6G Networks. The proposed approach incorporates semantic, pragmatic, and goal-oriented communication into AI-native technologies, aiming to facilitate information exchange between intelligent agents in a more relevant, effective, and timely manner, thereby optimizing bandwidth, latency, energy, and electromagnetic field (EMF) radiation. The focus is on distilling data to its most relevant form and terse representation, aligning with the source’s intent or the destination’s objectives and context, or serving a specific goal. 6G-GOALS builds on three fundamental pillars: i) AI-enhanced semantic data representation, sensing, compression, and communication, ii) foundational AI reasoning and causal semantic data representation, contextual relevance, and value for goal-oriented effectiveness, and iii) sustainability enabled by more efficient wireless services. Finally, we illustrate two proof-of-concepts implementing semantic, goal-oriented, and pragmatic communication principles in near-future use cases. Our study covers the project’s vision, methodologies, and potential impact.

Cloud-native services face unique cybersecurity challenges due to their distributed infrastructure. They are susceptible to various threats like malware, DDoS attacks, and Man-in-the-Middle (MITM) attacks. Additionally, these services often process sensitive data that must be protected from unauthorized access. On top of that, the dynamic and scalable nature of cloud-native services makes it difficult to maintain consistent security, as deploying new instances and infrastructure introduces new vulnerabilities. To address these challenges, efficient security solutions are needed to mitigate potential threats while aligning with the characteristics of cloud-native services. Despite the abundance of works focusing on security aspects in the cloud, there has been a notable lack of research that is focused on the security of cloud-native services. To address this gap, this work is the first survey that is dedicated to exploring security in cloud-native services. This work aims to provide a comprehensive investigation of the aspects, features, and solutions that are associated with security in cloud-native services. It serves as a uniquely structured mapping study that maps the key aspects to the corresponding features, and these features to numerous contemporary solutions. Furthermore, it includes the identification of various candidate open-source technologies that are capable of supporting the realization of each explored solution. Finally, it showcases how these solutions can work together in order to establish each corresponding feature. The insights and findings of this work can be used by cybersecurity professionals, such as developers and researchers, to enhance the security of cloud-native services.

Cloud computing data centres, due to their housing of powerful ICT equipment, are high energy consumers and therefore accountable for large quantities of emissions. Therefore, energy saving strategies applicable to such data centres are a very promising research direction both from the economical and environmental stand point. In this paper, we study the case of private cloud computing environments from the perspective of energy saving incentives. However, the proposed approach can also be applied to any computing style: cloud (both public and private), traditional and supercomputing. To this end, we provide a generic conceptual description for ICT resources of a data centre and identify their corresponding energy-related attributes. Furthermore, we give power consumption prediction models for servers, storage devices and network equipment. We show that by applying appropriate energy optimisation policies guided through accurate power consumption prediction models, it is possible to save about 20% of energy consumption when typical single-site private cloud data centres are considered. Minimising the data centre’s energy consumption, on one hand acknowledges the potential of ICT for saving energy across many segments of the economy, on the other hand helps ICT sector to show the way for the rest of the economy by reducing its own carbon footprint. In this paper, we show that it is possible to save energy by studying the case of a single-site private cloud data centres. We believe that through the federation of several cloud data centres (both private and public), it is possible to minimise both the energy consumption as well as CO2 emissions.

Abstract Over the last couple of years, industry operators' associations issued requirements towards an end‐to‐end management and orchestration plane for 5G networks. Consequently, standard organisations started their activities in this domain. This article provides an analysis and an architectural survey of these initiatives and of the main requirements, proposes descriptions for the key concepts of domain, resource and service slicing, end‐to‐end orchestration and a reference architecture for the end‐to‐end orchestration plane. Then, a set of currently available or under development domain orchestration frameworks are mapped to this reference architecture. These frameworks, meant to provide coordination and automated management of cloud and networking resources, network functions and services, fulfil multi‐domain (i.e. multi‐technology and multi‐operator) orchestration requirements, thus enabling the realisation of an end‐to‐end orchestration plane. Finally, based on the analysis of existing single‐domain and multi‐domain orchestration components and requirements, this paper presents a functional architecture for the end‐to‐end management and orchestration plane, paving the way to its full realisation. Copyright © 2016 The Authors. Transactions on Emerging Telecommunications Technologies Published by John Wiley & Sons Ltd.

Abstract Hewlett–Packard Co. developed a framework for aligning business and IT strategy. It has allowed the company to make process changes regardless of the limitations of existing technology and it makes visible the changes new technologies and processes have on each other. Most important, the framework enjoys a high level of commitment from people throughout the organization.

Background: Service robots may offer an innovative assistive solution to improve the quality of life of frail elderly people, by assisting them in specific situations identified as relevant to maintain independence. Objective: This paper describes th

We analyze daily log-returns data for a set of 1200 stocks, taken from US stock markets, over a period of 2481 trading days (January 1996-November 2005). We estimate the degree of non-stationarity in daily market volatility employing a polynomial fit, used as a detrending function. We find that the autocorrelation function of absolute detrended log-returns departs strongly from the corresponding original data autocorrelation function, while the observed leverage effect depends only weakly on trends. Such effect is shown to occur when both skewness and long-time memory are simultaneously present. A fractional derivative random walk model is discussed yielding a quantitative agreement with the empirical results. Copyright © 2008 EPLA.

The power grid has become a critical infrastructure, which modern society cannot do without. It has always been a challenge to keep power supply and demand in balance; the more so with the recent rise of intermittent renewable energy sources. Demand response (DR) schemes are one of the counter measures, traditionally employed with large industrial plants. This paper suggests to consider data centers (DCs) as candidates for DR as they are large energy consumers and as they are able to adapt their power profile sufficiently well. To unlock this potential, we suggest a system of contracts that regulate collaboration and economic incentives between the DC and its energy supplier (GreenSDA) as well as between the DC and its customers (GreenSLA). Several presented use cases serve to validate the suitability of DCs for DR schemes.

Electron impact mass spectronomy analysis of the amino-terminal amino acid of the small subunit (SSU) of ribulose-1,5-bisphosphate carboxylase (Rubisco) showed that the amino-terminal methionine residue is post-translationally modified to N-methyl-methionine. Modification of the amino-terminal methionine residue was found in mature SSU proteins from the dicotyledonous plants pea and spinach as well as the monocotyledonous plants barley and corn. SSU methyltransferase is a soluble protein in the chloroplast stroma and accepts heterologously expressed non-methylated SSU as a substrate using S-adenosylmethionine as methyl-group donor. We show that this modification occurs after post-translational uptake of the precursor form of SSU into chloroplasts and processing to its mature size. This reaction represents a new step in the import and assembly pathway of Rubisco holoenzyme.

Abstract Market fragmentation has resulted in a multitude of network and cloud/data center operators, each focused on different countries, regions and technologies. This makes it difficult and costly to create infrastructure services spanning multiple domains, such as virtual connectivity or compute resources. In this article, we discuss the goals and work being done within the 5GEx (5G Exchange) project in realising a Europe‐wide multi‐domain platform. This platform aims at enabling cross‐domain orchestration of services over multiple administrations or over multi‐domain single administrations in the context of emerging 5G networking. The 5GEx vision is based on introducing a unification via network function virtualisation/software‐defined networking compatible multi‐domain orchestration for networks, clouds and services. We describe the motivation and 5GEx vision, the adopted architecture and the next steps in terms of implementation and experimentation. Copyright © 2016 John Wiley & Sons, Ltd.

Formal techniques for the specification of real time systems must be capable of describing system behavior as a set of relationships expressing the temporal constraints among events and actions, including properties of invariance, precedence, periodicity, liveness, and safety conditions. The paper describes a Temporal-Interval Logic with Compositional Operators (TILCO) designed expressly for the specification of real time systems. TILCO is a generalization of classical temporal logics based on the operators, eventually and henceforth; it allows both qualitative and quantitative specification of time relationships. TILCO is based on time intervals and can concisely express temporal constraints with time bounds, such as those needed to specify real time systems. This approach can be used to verify the completeness and consistency of specifications, as well as to validate system behavior against its requirements and general properties. TILCO has been formalized by using the theorem prover Isabelle/HOL. TILCO specifications satisfying certain properties are executable by using a modified version of the Tableaux algorithm. The paper defines TILCO and its axiomatization, highlights the tools available for proving properties of specifications and for their execution, and provides an example of system specification and validation.

The limits of ultrafast DNA analysis by CE were determined by investigating the influence of the effective capillary length and the electric field strength on the analysis time for a given peak resolution (10 bp). In accordance with theory, the use of a fast ramp power supply for narrow plug electrokinetic injection was found to be essential to minimize the extra column effects on peak dispersion. Two major column dispersion factors, longitudinal diffusion and thermal dispersion, were determined experimentally, as well as the influence of the electric field strength on the electrophoretic mobilities and diffusion coefficients of DNA. It was found that higher field strengths can be applied with lower thermal dispersion than predicted by classical CE models. This was attributed to the faster mass transport in the radial direction due to field-induced DNA orientation. Short capillaries (approximately 3-7 cm effective length) and moderate to high electric field strengths (approximately 600-800 V/cm) were used to perform a series of fast DNA separations. The dsDNA fragment standards phiX174/HaeIII and pBR322/HaeIII were separated within 30 s. The possibility for fast mutation detection was demonstrated using constant denaturant capillary electrophoresis (CDCE) for the analysis of a single base mutation in mitochondrial DNA in 72 s. The potential for fast DNA sequencing was illustrated by separating 300 ssDNA fragments within 180 s.

Participants in current team collaborations belong to different organizations, work on multiple objectives at the same time, and frequently change locations. They use different devices and infrastructures in collaboration processes that can last from a few hours to several years. All these factors pose new challenges to the development of collaborative working environments (CWEs). Existing CWEs are unable to support emerging teams because diverse collaboration services are not well integrated or adapting to the team context. We present the inContext approach to providing a novel pervasive CWE infrastructure for emerging team forms. inContext aggregates disparate collaboration services using Web services and Semantic Web technologies and provides a platform that captures diverse dynamic aspects of team collaborations. By utilizing runtime and historical context and interaction information, adaptation techniques can be deployed to cope with the changes of emerging teams.

The design, fabrication and test of a 2-18 GHz monolithic Low Noise Amplifier utilizing 0.25 μm AlGaN/GaN HEMT technology is reported. The measured noise figure of the amplifier is less than 4.7 dB over the 2 - 18 GHz frequency range, exhibiting a minimum of 3.3 dB at 3 GHz. The LNA gain is 23 dB. Even being a low-noise amplifier, the MMIC can withstand 10W input CW RF power, demonstrating no apparent degradation: to the authors knowledge this is the best RF LNA survivability reported to date in this frequency range using GaN technology.