A model for the analysis of security policies in service function chains

Two emerging architectural paradigms, i.e., Software Defined Networking (SDN) and Network Function Virtualization (NFV), enable the deployment and management of Service Function Chains (SFCs). A SFC is an ordered sequence of abstract Service Functions (SFs), e.g., firewalls, VPN-gateways,traffic monitors, that packets have to traverse in the route from source to destination. While this appealing solution offers significant advantages in terms of flexibility, it also introduces new challenges such as the correct configuration and ordering of SFs in the chain to satisfy overall security requirements. This paper presents a formal model conceived to enable the verification of correct policy enforcements in SFCs. Software tools based on the model can then be designed to cope with unwanted network behaviors (e.g., security flaws) deriving from incorrect interactions of SFs in the same SFC

An aging evaluation of the bearing performances of glass fiber composite laminate in salt spray fog environment

The aim of the present paper is to assess the bearing performance evolution of pinned, glass-composite laminates due to environmental aging in salt-spray fog tests. Glass fibers/epoxy pinned laminates were exposed for up to 60 days in salt-spraying, foggy environmental conditions (according to ASTM B117 standard). In order to evaluate the relationship between mechanical failure mode and joint stability over increasing aging time, different single lap joints, measured by the changing hole diameter (D), laminate width (W) and hole free edge distance (E), were characterized at varying aging steps. Based on this approach, the property-structure relationship of glass-fibers/epoxy laminates was assessed under these critical environmental conditions. Furthermore, an experimental 2D failure map, clustering main failure modes in the plane E/D versus W/D ratios, was generated, and its cluster variation was analyzed at each degree of aging

Frequency-dependent attenuation and elasticity in unconsolidated earth materials: effect of damping

We use the Discrete Element Method (DEM) to understand the underlying attenuation mechanism in granular media, with special applicability to the measurements of the so-called effective mass developed earlier. We consider that the particles interact via Hertz-Mindlin elastic contact forces and that the damping is describable as a force proportional to the velocity difference of contacting grains. We determine the behavior of the complex-valued normal mode frequencies using 1) DEM, 2) direct diagonalization of the relevant matrix, and 3) a numerical search for the zeros of the relevant determinant. All three methods are in strong agreement with each other. The real and the imaginary parts of each normal mode frequency characterize the elastic and the dissipative properties, respectively, of the granular medium. We demonstrate that, as the interparticle damping, $\xi$, increases, the normal modes exhibit nearly circular trajectories in the complex frequency plane and that for a given value of $\xi$ they all lie on or near a circle of radius $R$ centered on the point $-iR$ in the complex plane, where $R\propto 1/\xi$. We show that each normal mode becomes critically damped at a value of the damping parameter $\xi \approx 1/\omega_n^0$, where $\omega_n^0$ is the (real-valued) frequency when there is no damping. The strong indication is that these conclusions carry over to the properties of real granular media whose dissipation is dominated by the relative motion of contacting grains. For example, compressional or shear waves in unconsolidated dry sediments can be expected to become overdamped beyond a critical frequency, depending upon the strength of the intergranular damping constant.Comment: 28 pages, 7 figure

Thermosensory mapping of skin wetness sensitivity across the body of young males and females at rest and following maximal incremental running

Key points: Humans lack skin receptors for wetness (i.e. hygroreceptors), yet we present a remarkable wetness sensitivity. Afferent inputs from skin cold-sensitive thermoreceptors are key for sensing wetness; yet, it is unknown whether males and females differ in their wetness sensitivity across their body and whether high intensity exercise modulates this sensitivity. We mapped sensitivity to cold, neutral and warm wetness across five body regions and show that females are more sensitive to skin wetness than males, and that this difference is greater for cold than warm wetness sensitivity. We also show that a single bout of maximal exercise reduced the sensitivity to skin wetness (i.e. hygro-hypoesthesia) of both sexes as a result of concurrent decreases in thermal sensitivity. These novel findings clarify the physiological mechanisms underpinning this fundamental human sensory experience. In addition, they indicate sex differences in thermoregulatory responses and will inform the design of more effective sport and protective clothing, as well as thermoregulatory models. Abstract: Humans lack skin hygroreceptors and we rely on integrating cold and tactile inputs from A-type skin nerve fibres to sense wetness. Yet, it is unknown whether sex and exercise independently modulate skin wetness sensitivity across the body. We mapped local sensitivity to cold, neutral and warm wetness of the forehead, neck, underarm, lower back and dorsal foot in 10 males (27.8 ± 2.7 years; 1.92 ± 0.1 m2 body surface area) and 10 females (25.4 ± 3.9 years; 1.68 ± 0.1 m2 body surface area), at rest and post maximal incremental running. Participants underwent our quantitative sensory test where they reported the magnitude of thermal and wetness perceptions (visual analogue scale) resulting from the application of a cold (5°C below skin temperature) wet (0.8 mL of water), neutral wet and warm wet (5°C above skin temperature) thermal probe (1.32 cm2) to five skin sites. We found that: (i) females were ∼14% to ∼17% more sensitive to cold-wetness than males, yet both sexes were as sensitive to neutral- and warm-wetness; (ii) regional differences were present for cold-wetness only, and these followed a craniocaudal increase that was more pronounced in males (i.e. the foot was ∼31% more sensitive than the forehead); and (iii) maximal exercise reduced cold-wetness sensitivity over specific regions in males (i.e. ∼40% decrease in foot sensitivity), and also induced a generalized reduction in warm-wetness sensitivity in both sexes (i.e. ∼4% to ∼6%). For the first time, we show that females are more sensitive to cold wetness than males and that maximal exercise induce hygro-hypoesthesia. These novel findings expand our knowledge on sex differences in thermoregulatory physiology

fNIRS complexity analysis for the assessment of motor imagery and mental arithmetic tasks

Conventional methods for analyzing functional near-infrared spectroscopy (fNIRS) signals primarily focus on characterizing linear dynamics of the underlying metabolic processes. Nevertheless, linear analysis may underrepresent the true physiological processes that fully characterizes the complex and nonlinear metabolic activity sustaining brain function. Although there have been recent attempts to characterize nonlinearities in fNIRS signals in various experimental protocols, to our knowledge there has yet to be a study that evaluates the utility of complex characterizations of fNIRS in comparison to standard methods, such as the mean value of hemoglobin. Thus, the aim of this study was to investigate the entropy of hemoglobin concentration time series obtained from fNIRS signals and perform a comparitive analysis with standard mean hemoglobin analysis of functional activation. Publicly available data from 29 subjects performing motor imagery and mental arithmetics tasks were exploited for the purpose of this study. The experimental results show that entropy analysis on fNIRS signals may potentially uncover meaningful activation areas that enrich and complement the set identified through a traditional linear analysis

Independent and interactive effects of thermal stress and mental fatigue on manual dexterity

Many occupations and sports require high levels of manual dexterity under thermal stress and mental fatigue. Yet, multistressor studies remain scarce. We quantified the interactive effects of thermal stress and mental fatigue on manual dexterity. Seven males (21.1 \ub1 1.3 yr) underwent six separate 60-min trials characterized by a combination of three air temperatures (hot, 37C; neutral, 21C; cold, 7C) and two mental fatigue states (MF, mental fatigue induced by a 35-min cognitive battery; no-MF, no mental fatigue). Participants performed complex (O'Connor test) and simple (hand-tool test) manual tasks pre- and posttrial to determine stressor-induced performance changes. We monitored participants' rectal temperature and hand skin temperature (Thand) continuously and assessed the reaction time (handclick test) and subjective mental fatigue (5-point scale). Thermal stress (P < 0.0001), but not mental fatigue (P = 0.290), modulated Thand (heat, +3.3C [95% CI: +0.2, +6.5]; cold, 7.5C [10.7, 4.4]). Mental fatigue (P = 0.021), but not thermal stress (P = 0.646), slowed the reaction time (10%) and increased subjective fatigue. Thermal stress and mental fatigue had an interactive effect on the complex manual task (P = 0.040), with cold-no-MF decreasing the performance by 22% [39, 5], whereas neutral-MF, cold-MF, and heat-MF by 36% [53, 19], 34% [52, 17], and 36% [53, 19], respectively. Only mental fatigue decreased the performance in the simple manual task (30% [43, 16] across all thermal conditions; P = 0.002). Cold stress-induced impairments in complex manipulation increase with mental fatigue; yet combined stressors' effects are no greater than those of mental fatigue alone, which also impairs simple manipulation. Mental fatigue poses a greater challenge to manual dexterity than thermal stress

Multivariate Pattern Analysis of Entropy estimates in Fast- and Slow-Wave Functional Near Infrared Spectroscopy: A Preliminary Cognitive Stress study

Functional near infrared spectroscopy (fNIRS) is a modality that can measure shallow cortical brain signals and also contains pulsatile oscillations that originate from heartbeat dynamics. In particular, while fNIRS slow waves (0 Hz to 0.6 Hz) refer to the standard hemodynamic signal, fast-wave (0.8 Hz to 3 Hz) fNIRS signals refer to cardiac oscillations. Using a cognitive stress experiment paradigm with mental arithmetic, the aim of this study was to assess differences in cortical activity when using slow-wave or fast-wave fNIRS signals. Furthermore, we aimed to see whether fNIRS fast and slow waves provide different information to discriminate mental arithmetic tasks from baseline. We used data from 10 healthy subjects from an open dataset performing mental arithmetic tasks and assessed fNIRS signals using mean values in the time domain, as well as complexity estimates including sample, fuzzy, and distribution entropy. A searchlight representational similarity analysis with pairwise t-test group analysis was performed to compare the representational dissimilarity matrices of each searchlight center. We found significant representational differences between fNIRS fast and slow waves for all complexity estimates, at different brain regions. On the other hand, no statistical differences were observed for mean values. We conclude that entropy analysis of fNIRS data may be more sensitive than traditional methods like mean analysis at detecting the additional information provided by fast-wave signals for discriminating mental arithmetic tasks and warrants further research

Inhomogeneous point-process entropy: an instantaneous measure of complexity in discrete systems

Measures of entropy have been widely used to characterize complexity, particularly in physiological dynamical systems modeled in discrete time. Current approaches associate these measures to finite single values within an observation window, thus not being able to characterize the system evolution at each moment in time. Here, we propose a new definition of approximate and sample entropy based on the inhomogeneous point-process theory. The discrete time series is modeled through probability density functions, which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through probability functions, the novel indices are able to provide instantaneous tracking of the system complexity. The new measures are tested on synthetic data, as well as on real data gathered from heartbeat dynamics of healthy subjects and patients with cardiac heart failure and gait recordings from short walks of young and elderly subjects. Results show that instantaneous complexity is able to effectively track the system dynamics and is not affected by statistical noise properties

Nonlinear neural patterns are revealed in high frequency functional near infrared spectroscopy analysis

Functional Near Infrared Spectroscopy (fNIRS) is a useful tool for measuring hemoglobin concentration. Linear theory of the hemodynamic response function supports low frequency analysis (<0.2 Hz). However, we hypothesized that nonlinearities, arising from the complex neurovascular interactions sustaining vasomotor tone, may be revealed in higher frequency components of fNIRS signals. To test this hypothesis, we simulated nonlinear hemodynamic models to explore how blood flow autoregulation changes may alter evoked neurovascular signals in high frequencies. Next, we analyzed experimental fNIRS data to compare neural representations between fast (0.2–0.6 Hz) and slow (<0.2 Hz) waves, demonstrating that only nonlinear representations quantified by sample entropy are distinct between these frequency bands. Finally, we performed group-level distance correlation analysis to show that the cortical distribution of activity is independent only in the nonlinear analysis of fast and slow waves. Our study highlights the importance of analyzing nonlinear higher frequency effects seen in fNIRS for a comprehensive analysis of cortical neurovascular activity. Furthermore, it motivates further exploration of the nonlinear dynamics driving regional blood flow and hemoglobin concentration