Back to the Past. The paleogeography as key to understand the Middle Palaeolithic peopling at Grotta dei Santi (Mt Argentario – Tuscany)

The mobility of hunter-gatherer groups is crucial in understanding Palaeolithic settlement dynamics. The concept of mobility cannot be separated from the space in which it occurs, including landscape components, localization of critical resources and of other sites, and routes between them. Nevertheless, the landscape is not constant in time due to the geomorphological changes that occurred in the long timescale of Prehistory. Here we present a paleogeographic reconstruction of the coastal area around Grotta dei Santi during the Neandertal occupation. A GIS-based approach, combining geological, bathymetric, and sea-level fluctuations data, allows us to reconstruct the landscape around the cave at about 45 ky BP. The cave today opens onto a cliff facing the sea. The Neandertal occupation occurred with a sea-level 74 m lower than present-day. Consequently, the cave faced a vast coastal plain, playing a strategic role due to its position, allowing both proximity and control of essential resources

Paleogeographic reconstruction of the Tuscan coastal area nearby Grotta dei Santi (Monte Argentario, Italy) during the Neandertal occupation

The mobility of hunter-gatherer groups is crucial in understanding Palaeolithic settlement dynamics. The concept of mobility cannot be separated from the space in which it occurs, including landscape components, localization of critical resources and of other sites, and routes between them. Nevertheless, the landscape is not constant in time due to the geomorphological changes that occurred in the long timescale of Prehistory. Here we present a paleogeographic reconstruction of the coastal area around Grotta dei Santi during the Neandertal occupation. A GIS-based approach, combining geological, bathymetric, and sea-level fluctuations data, allows us to reconstruct the landscape around the cave at about 45 ky BP. The cave today opens onto a cliff facing the sea. The Neandertal occupation occurred with a sea-level 74 m lower than present-day. Consequently, the cave faced a vast coastal plain, playing a strategic role due to its position, allowing both proximity and control of essential resources. © 2022 IMEKO TC-4 International Conference on Metrology for Archaeology and Cultural Heritage, MetroArchaeo 2022.All rights reserved

Early and Late Response and Glucocorticoid-Sparing Effect of Belimumab in Patients with Systemic Lupus Erythematosus with Joint and Skin Manifestations: Results from the Belimumab in Real Life Setting Study—Joint and Skin (BeRLiSS-JS)

Aim. To assess the efficacy of belimumab in joint and skin manifestations in a nationwide cohort of patients with SLE. Methods. All patients with skin and joint involvement enrolled in the BeRLiSS cohort were considered. Belimumab (intravenous, 10 mg/kg) effectiveness in joint and skin manifestations was assessed by DAS28 and CLASI, respectively. Attainment and predictors of DAS28 remission (<2.6) and LDA (≥2.6, ≤3.2), CLASI = 0, 1, and improvement in DAS28 and CLASI indices ≥20%, ≥50%, and ≥70% were evaluated at 6, 12, 24, and 36 months. Results. DAS28 < 2.6 was achieved by 46%, 57%, and 71% of patients at 6, 12, and 24 months, respectively. CLASI = 0 was achieved by 36%, 48%, and 62% of patients at 6, 12, and 24 months, respectively. Belimumab showed a glucocorticoid-sparing effect, being glucocorticoid-free at 8.5%, 15.4%, 25.6%, and 31.6% of patients at 6, 12, 24, and 36 months, respectively. Patients achieving DAS-LDA and CLASI-50 at 6 months had a higher probability of remission at 12 months compared with those who did not (p = 0.034 and p = 0.028, respectively). Conclusions. Belimumab led to clinical improvement in a significant proportion of patients with joint or skin involvement in a real-life setting and was associated with a glucocorticoid-sparing effect. A significant proportion of patients with a partial response at 6 months achieved remission later on during follow-up

ACCPndn: Adaptive Congestion Control Protocol in Named Data Networking by learning capacities using optimized Time-Lagged Feedforward Neural Network

Named Data Networking (NDN) is a promising network architecture being considered as a possible replacement for the current IP-based Internet infrastructure. However, NDN is subject to congestion when the number of data packets that reach one or various routers in a certain period of time is so high than its queue gets overflowed. To address this problem many congestion control protocols have been proposed in the literature which, however, they are highly sensitive to their control parameters as well as unable to predict congestion traffic well enough in advance. This paper develops an Adaptive Congestion Control Protocol in NDN (ACCPndn) by learning capacities in two phases to control congestion traffics before they start impacting the network performance. In the first phase – adaptive training – we propose a Time-Lagged Feedforward Network (TLFN) optimized by hybridization of particle swarm optimization and genetic algorithm to predict the source of congestion together with the amount of congestion. In the second phase -fuzzy avoidance- we employ a non-linear fuzzy logic-based control system to make a proactive decision based on the outcomes of first phase in each router per interface to control and/or prevent packet drop well enough in advance. Extensive simulations and results show that ACCPndn sufficiently satisfies the applied performance metrics and outperforms two previous proposals such as NACK and HoBHIS in terms of the minimal packet drop and high-utilization (retrying alternative paths) in bottleneck links to mitigate congestion traffics

African Linguistics in Central and Eastern Europe, and in the Nordic Countries

Non peer reviewe

A hybrid multiobjective RBF-PSO method for mitigating DoS attacks in Named Data Networking

Named Data Networking (NDN) is a promising network architecture being considered as a possible replacement for the current IP-based (host-centric) Internet infrastructure. NDN can overcome the fundamental limitations of the current Internet, in particular, Denial-of-Service (DoS) attacks. However, NDN can be subject to new type of DoS attacks namely Interest flooding attacks and content poisoning. These types of attacks exploit key architectural features of NDN. This paper presents a new intelligent hybrid algorithm for proactive detection of DoS attacks and adaptive mitigation reaction in NDN. In the detection phase, a combination of multiobjective evolutionary optimization algorithm with PSO in the context of the RBF neural network has been applied in order to improve the accuracy of DoS attack prediction. Performance of the proposed hybrid approach is also evaluated successfully by some benchmark problems. In the adaptive reaction phase, we introduced a framework for mitigating DoS attacks based on the misbehaving type of network nodes. The evaluation through simulations shows that the proposed intelligent hybrid algorithm (proactive detection and adaptive reaction) can quickly and effectively respond and mitigate DoS attacks in adverse conditions in terms of the applied performance criteria

Trapping in irradiated p-on-n silicon sensors at fluences anticipated at the HL-LHC outer tracker

The degradation of signal in silicon sensors is studied under conditions expected at the CERN High-Luminosity LHC. 200 $\mu$m thick n-type silicon sensors are irradiated with protons of different energies to fluences of up to $3 \cdot 10^{15}$ neq/cm$^2$. Pulsed red laser light with a wavelength of 672 nm is used to generate electron-hole pairs in the sensors. The induced signals are used to determine the charge collection efficiencies separately for electrons and holes drifting through the sensor. The effective trapping rates are extracted by comparing the results to simulation. The electric field is simulated using Synopsys device simulation assuming two effective defects. The generation and drift of charge carriers are simulated in an independent simulation based on PixelAV. The effective trapping rates are determined from the measured charge collection efficiencies and the simulated and measured time-resolved current pulses are compared. The effective trapping rates determined for both electrons and holes are about 50% smaller than those obtained using standard extrapolations of studies at low fluences and suggests an improved tracker performance over initial expectations

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Search for photonic signatures of gauge-mediated supersymmetry in 13 TeV pp collisions with the ATLAS detector

A search is presented for photonic signatures, motivated by generalized models of gauge-mediated supersymmetry breaking. This search makes use of proton-proton collision data at √s = 13 TeV corresponding to an integrated luminosity of 36.1 fb −1 recorded by the ATLAS detector at the LHC, and it explores models dominated by both strong and electroweak production of supersymmetric partner states. Experimental signatures incorporating an isolated photon and significant missing transverse momentum are explored. These signatures include events with an additional photon or additional jet activity not associated with any specific underlying quark flavor. No significant excess of events is observed above the Standard Model prediction, and 95% confidence-level upper limits of between 0.083 fb and 0.32 fb are set on the visible cross section of contributions from physics beyond the Standard Model. These results are interpreted in terms of lower limits on the masses of gluinos, squarks, and gauginos in the context of generalized models of gauge-mediated supersymmetry, which reach as high as 2.3 TeV for strongly produced and 1.3 TeV for weakly produced supersymmetric partner pairs