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Organisations, governments and users are increasingly vulnerable to cyberattacks, which effects may range from threatening the foundation of modern information society, to causing catastrophic failure of nation-wide critical infrastructure. As a result, a great deal of effort has been given to mitigating the risks stemming from cyber-attacks and has established the field of cyber-security. To defend against cyber-attacks, defenders are required to foresee threat actors’ actions some way in advance to implement protective means. This interdependency places anticipatory practice at the heart of cyber-security. Despite the importance of these activities, little work exists that considers the details of anticipatory practices in cyber-security. This chapter explores how a forward-looking stance and the use of that forward-looking stance to affect a change in the present are a key concept and goal of cyber-security. Literature on anticipation in cyber-security is reviewed and its importance illustrated through the use of a detailed case study. In this study, we draw upon empirical accounts of five cyber-threat analysts’ day-to-day practices to explore how futures are envisioned and used in the attempt to protect cyber-space. We find that anticipation of the future is, under different names, a well-considered stance in cyber-security that attracts attention from practitioners and theorists alike. The practices that were uncovered proved to be highly anticipatory in nature. Defenders take an “attack attitude”, where they aim to envision possible future attack behaviours to inform their defence responses. Analysts engage in external and internal knowledge acquisition activities to obtain knowledge about the attack and defence space and anticipate the future. Yet, obtaining this knowledge presents a major challenge due to the ambiguity and amount of information available. We conclude that improving cyber-defenders’ anticipatory capabilities may enhance the overall sense-making process and improve decision-making.

Item does not contain fulltext Our society will increasingly be an urban society, with large metropolitan regions as the centers of development. These metropolitan spaces are supposed to create the economic and technological dynamics to solve the problems of the very same urban society. They are extremely complex structures, overall, difficult to understand in all their dimensions and asking for new ways of management, strategy formation, and general politics: “if we cannot imagine, we cannot manage.” Stakeholders, citizens, and planners alike will be faced with the challenge to develop appropriate ideas guiding the dynamics and complex settings and to keep development horizons open for not yet anticipated trajectories. Vision-making processes become very important in such a context, in the best case creating open political horizons, interested in becoming and the “midwifing of futures.” A survey of 30 vision-making processes in Europe forms the empirical backcloth for a presentation and discussion of urban systems, vision-making documents, time horizons and instant futures, vision formulations, and the “perpetual pursuit of unknowable novelty.”

A complete kinetic study of pH-dependent isomerization of species 5-amino-3-imino-1,2,6,7-tetracyano-3H- pyrrolizine (HL) and 2-(5-amino-3,4-dicyano-2H-pyrrol-2- ylidene)-1,1,2-tricyanoethanide (L'-) in the pH range from 0.5 to 13 in aqueous solution, which spans over 7 order of magnitude for the pseudo-first order rates (log k from 4.8 to 2.5) has revealed for the first time the existence of the corresponding conjugate species L- and HL'. The study has allowed the determination of the pKa values of HL and HL', as well as all the individual forward and reverse isomerization rates of the acidic (HL/HL') and basic (L-/L'-) forms. While L'- is the sole species present at pH > ca. 7, species HL and HL' establish an equilibrium favoring the former compound at low pH, the distribution being ca. 79:21 at pH < ca. 2. At pH < 2, a slow decomposition of HL occurs via the initial formation of an unobserved and unstable protonated form H2L+. Geometry optimizations of all species at the B3LYP/LANL2DZ level, including water solvation energy, afford results in qualitative agreement with experiment and indicate the structural nature of the new species L- and HL'.

This paper describes some achievements in the segmentation of medical images using artificial neural networks. We have identified three main sources of a priori information available to help perform the task of medical image segmentation: anatomical knowledge about the imaged region, the physical principles of image generation and the "regulari ties" of biological structures. The exploitation of each of these forms of knowledge can be effectively achieved with suitable neural architectures, three of which are described in the paper. An important lesson learnt from using these architectures is that different kinds of knowledge unavoidably induce different limitations in the resulting segmentation systems, either in terms of generality or of performance. Our experience indicates that in several applications some of such limitations can be overcome through a careful exploitation and integration of available knowledge sources via proper neural modules.

The uncertainty associated with TL measurements has been related to the heating phase of the annealing and of the reading cycles, in particular, the need for stability of the ovens and the reproducibility of the heating rate during TL readout is pointed out. The cooling conditions are another element of importance in the annealing cycle of some TL materials. Therefore, sensitivity variations, in terms of cooling rate from high temperature to room temperature, have been investigated in BeO, LiF and CaF2:Dy loose detectors. Fast cooling in LiF but slow cooling in BeO markedly increases sensitivity, while CaF2:Dy is unaffected by cooling rate. The different behaviour of these TL materials could be explained by their different structures. The effect described is found not to be permanent, i.e. TL materials 'remember' only the last cooling cycle, since the crystalline structure of the detectors is not modified by thermal procedures carried out for annealing. To ensure reliability of the dosimetric data, extreme reproducibility of the entire annealing cycle is required.

International audience; The complex [Cp*2Mo2O5] (Cp* = η5-C5Me5) and its electrochemical reduction products in acetic acid/acetate-buffered (pH = 4.0) water/methanol solutions were investigated by combined electrochemical (EC) flowcell and on-line electrospray ionization mass spectrometry (ESI-MS). Mono-, di-, tri-, and tetranuclear organometallic molybdenum oxides were identified in the starting solution. The effect of the relevant ESI-MS parameters (ionic mode, heated capillary voltage, and heated capillary temperature) and of the concentration on the observed distribution of ions in the mass spectrometer was studied in order to minimize side reactions in the ESI chamber. It was verified that reduction in the ESI-MS is undetectable under open-circuit conditions. The on-line electrochemical study revealed the potential-dependent formation of previously unknown mono-, di-, tri-, and tetranuclear MoV, MoIV, and mixed-valence complexes. The compounds were identified by their characteristic isotope patterns and their ion trap MSn fragmentations. The observed formation potentials reflect the higher stability of the multinuclear species relative to the mononuclear ones with the same oxidation state.

The dream of controlling and guiding computer-based systems using human brain signals has slowly but steadily become a reality. The available technology allows real-time implementation of systems that measure neuronal activity, convert their signals, and translate their output for the purpose of controlling mechanical systems. This paper describes the state of the art of non-invasive BMIs and critically investigates both the current technological limits and the future potential that BMIs have for space applications. We present an assessment of the advantages that BMIs can provide and justify the preferred candidate concepts for space applications together with a vision of future directions for their implementation.

IntroductionItaly is one of the high-income countries hit hardest by Covid-19. During the first months of the pandemic, Italian healthcare workers were praised by media and the public for their efforts to face the emergency, although with limited knowledge and resources. However, healthcare workers soon had to face new challenges at a time when the national health system was working hard to recover. This study focuses on this difficult period to assess the impact of the COVID-19 pandemic on the mental health of Italian healthcare workers.Materials and MethodsHealthcare workers from all Italian regions [n = 5,502] completed an online questionnaire during the reopening phase after the first wave lockdown. We assessed a set of individual-level factors (e.g., stigma and violence against HCWs) and a set of workplace-level factors (e.g., trust in the workplace capacity to handle COVID-19) that were especially relevant in this context. The primary outcomes assessed were score ≥15 on the Patient Health Questionnaire-9 and score ≥4 on the General Health Questionnaire-12, indicators of clinically significant depressive symptoms and psychological distress, respectively. Logistic regression analyses were performed on depressive symptoms and psychological distress for each individual- and workplace-level factor adjusting for gender, age, and profession.ResultsClinically significant depressive symptoms were observed in 7.5% and psychological distress in 37.9% of HCWs. 30.5% of healthcare workers reported having felt stigmatized or discriminated, while 5.7% reported having experienced violence. Feeling stigmatized or discriminated and experiencing violence due to being a healthcare worker were strongly associated with clinically significant depressive symptoms [OR 2.98, 95%CI 2.36–3.77 and OR 4.72 95%CI 3.41–6.54] and psychological distress [OR 2.30, 95%CI 2.01–2.64 and OR 2.85 95%CI 2.16–3.75]. Numerous workplace-level factors, e.g., trust in the workplace capacity to handle COVID-19 [OR 2.43, 95%CI 1.92–3.07] and close contact with a co-worker who died of COVID-19 [OR 2.05, 95%CI 1.56–2.70] were also associated with clinically significant depressive symptoms. Similar results were found for psychological distress.ConclusionsOur study emphasizes the need to address discrimination and violence against healthcare professionals and improve healthcare work environments to strengthen the national health system's capacity to manage future emergencies.

Organisations, governments and users are increasingly vulnerable to cyberattacks, which effects may range from threatening the foundation of modern information society, to causing catastrophic failure of nation-wide critical infrastructure. As a result, a great deal of effort has been given to mitigating the risks stemming from cyber-attacks and has established the field of cyber-security. To defend against cyber-attacks, defenders are required to foresee threat actors’ actions some way in advance to implement protective means. This interdependency places anticipatory practice at the heart of cyber-security. Despite the importance of these activities, little work exists that considers the details of anticipatory practices in cyber-security. This chapter explores how a forward-looking stance and the use of that forward-looking stance to affect a change in the present are a key concept and goal of cyber-security. Literature on anticipation in cyber-security is reviewed and its importance illustrated through the use of a detailed case study. In this study, we draw upon empirical accounts of five cyber-threat analysts’ day-to-day practices to explore how futures are envisioned and used in the attempt to protect cyber-space. We find that anticipation of the future is, under different names, a well-considered stance in cyber-security that attracts attention from practitioners and theorists alike. The practices that were uncovered proved to be highly anticipatory in nature. Defenders take an “attack attitude”, where they aim to envision possible future attack behaviours to inform their defence responses. Analysts engage in external and internal knowledge acquisition activities to obtain knowledge about the attack and defence space and anticipate the future. Yet, obtaining this knowledge presents a major challenge due to the ambiguity and amount of information available. We conclude that improving cyber-defenders’ anticipatory capabilities may enhance the overall sense-making process and improve decision-making.

Dendrimers are hyperbranched macromolecules, synthesized step by step (generation after generation) in an iterative fashion, which structure is reminiscent to that of the branches of trees. Most of their properties are due to their terminal functions, which can be easily modified at will to fulfill the desired properties. In particular, many types of catalytic entities have been used as terminal groups of dendrimers. In some cases, a dendritic effect , that is the enhancement of the catalytic properties when a catalyst is linked to a dendrimer, has been observed. It is also generally possible to recover and reuse the dendritic catalysts. The internal structure of dendrimers can also play a key-role, as it manages cavities which can accommodate the catalytic entities, and enable the substrates to interact with them. Catalytic sites included inside the structure of dendrimers are rare, excepted if they constitute the core of dendrimers (or of dendrons, which are dendritic wedges). Effect of the confinement on the catalysis outcome is generally the main aim of these works. Another type of dendritic catalytic entities taking profit of the internal structure concerns metallic nanoparticles used as core of dendrimers. In this chapter, we will gather information about catalytic entities included inside dendrimers, either covalently linked, or noncovalently entrapped, and on their syntheses. The main types of reactions studied, the role of the generation (size) of the dendrimers, their recovery and reuse, and in general the effect of the confinement inside the dendritic structures on the catalytic efficiency will be discussed.

Anaplastic thyroid carcinoma (ATC) has a rapidly fatal clinical course, being resistant to multimodal treatments. Microtubules, alpha/beta tubulin heterodimers, are crucial in cell signaling, division and mitosis and are among the most successful targets for anticancer therapy. Panobinostat (LBH589) is a potent deacetylase inhibitor acting both on histones and nonhistonic proteins, including alpha-tubulin. In vitro LBH589, evaluated in three ATC cell lines (BHT-101, CAL-62 and 8305C), resulted in impairment of cell viability, inhibition of colony formation, cell cycle arrest and apoptosis induction. Mechanistically, we showed that LBH589 not only affected the expression of p21 and cyclin D1, but markedly determined microtubule stabilization as evidenced by tubulin acetylation and increased tubulin polymerization. In a SCID xenograft model implanted with CAL-62 cells, the cytotoxic properties of LBH589 were confirmed. The drug at the dose of 20 mg/kg significantly impaired tumor growth (final tumor volume 2.5-fold smaller than in untreated animals); at this dose, no relevant side effects were observed. In tumors of treated animals, a significant reduction of Ki67, which was negatively correlated with tubulin acetylation, was observed. Moreover, acetyl-tubulin levels negatively correlated with tumor volume at sacrifice, reinforcing the opinion that tubulin acetylation has a role in the inhibition of tumor growth. In conclusion, LBH589, acting on both histones and nonhistonic proteins in anaplastic thyroid cancer, appears to be a promising therapeutic agent for the treatment of this kind of cancer which is known not to respond to conventional therapy

Fitness-Proportional Negative Slope Coefficient is a fitness landscapes measure that has recently been introduced as a potential indicator of problem hardness for optimisation. It is inspired to an older measure, the Negative Slope Coefficient, and it has been theoretically modelled. Preliminary experiments have suggested that it may be a good predictor of problem hardness. However, this measure has not undergone any convincing and comprehensive empirical testing. Our objective is to fill this gap. So, we perform empirical tests using a large set of invertible functions of unitation. We find that while this measure may correctly predict the degree of evolvability of a landscape, this does not necessarily correlate with the difficulty of problems. Some landscapes may show, for example, limited evolvability and yet be easy to solve because either solutions are already present in the initial population or the computational resources provided exceed evolvability obstacles. Or it may be impossible to solve them irrespective of their evolvability simply because they are far too vast for the computational resources provided. These situations are hardly captured by the Fitness-Proportional Negative Slope Coefficient.

The crossover bias theory for bloat [18] is a recent result which predicts that bloat is caused by the sampling of short, unfit programs. This theory is clear and simple, but it has some weaknesses: (1) it implicitly assumes that the population is large enough to allow sampling of all relevant program sizes (although it does explain what to expect in the many practical cases where this is not true, e.g., because the population is small); (2) it does not explain what is meant by its assumption that short programs are unfit. In this paper we discuss these weaknesses and propose a refined version of the crossover bias theory that clarifies the relationship between bloat and finite populations, and explains what features of the fitness landscape cause bloat to occur. The theory, in particular, predicts that smaller populations will bloat more slowly than larger ones. Additionally, the theory predicts that bloat will only be observed in problems where short programs are less fit than longer ones when looking at samples created by fitness-based importance sampling, i.e. samplings of the search space in which fitter programs have a higher probability of being sampled (e.g., the Metropolis-Hastings method). Experiments with two classical GP benchmarks fully corroborate the theory. Copyright 2008 ACM.

The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been tested empirically on a large variety problems showing considerable reliability in distinguishing easy from hard problems. However, neither a theoretical justification nor a theoretical analysis of the nsc have ever been given. This paper presents a modification of nsc, the fitness-proportional negative slope coefficient (fpncs), for which it is possible to give a theoretical explanation and analysis. To illustrate the approach we compute fpnsc theoretically for the class of invertible functions of unitation, and for two mutation operators. We apply the theory to compute fpnsc for three benchmark functions: Onemax, Trap and Onemix. We then compare the predictions of fpnsc with the success probability recorded in actual runs. The results suggest that fpnsc is able to broadly discriminate between easy and hard GA problems. Copyright 2007 ACM.

The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.

In this paper we propose a Stochastic User Equilibrium (SUE) algorithm that can be adopted as a model, known as a simulation model, that imitates the behaviour of transportation systems. Indeed, analyses of real dimension networks need simulation algorithms that allow network conditions and performances to be rapidly determined. Hence, we developed an MSA (Method of Successive Averages) algorithm based on the Ant Colony Optimisation paradigm that allows transportation systems to be simulated in less time but with the same accuracy as traditional MSA algorithms. Finally, by means of Blum’s theorem, we stated theoretically the convergence of the proposed ACO-based algorithm.

Elitism is commonly used in generational GP to ensure that the best individuals discovered in a generation are not lost, and are made available for possible further improvements to new generations. Using two GP systems and four problems, we show how elitism reduces the growth of mean program size.

International audience; This paper presents an investigation of genetic programming fitness landscapes. We propose a new indicator of problem hardness for tree-based genetic programming, called negative slope coefficient, based on the concept of fitness cloud. The negative slope coefficient is a predictive measure, i.e. it can be calculated without prior knowledge of the global optima.The fitness cloud is generated via a sampling of individuals obtained with the Metropolis-Hastings method. The reliability of the negative slope coefficient is tested on a set of well known and representative genetic programming benchmarks, comprising the binomial-3 problem, the even parity problem and the artificial ant on the Santa Fe trail.