Decentralized planning for self-adaptation in multi-cloud environment

The runtime management of Internet of Things (IoT) oriented applications deployed in multi-clouds is a complex issue due to the highly heterogeneous and dynamic execution environment. To effectively cope with such an environment, the cross-layer and multi-cloud effects should be taken into account and a decentralized self-adaptation is a promising solution to maintain and evolve the applications for quality assurance. An important issue to be tackled towards realizing this solution is the uncertainty effect of the adaptation, which may cause negative impact to the other layers or even clouds. In this paper, we tackle such an issue from the planning perspective, since an inappropriate planning strategy can fail the adaptation outcome. Therefore, we present an architectural model for decentralized self-adaptation to support the cross-layer and multi-cloud environment. We also propose a planning model and method to enable the decentralized decision making. The planning is formulated as a Reinforcement Learning problem and solved using the Q-learning algorithm. Through simulation experiments, we conduct a study to assess the effectiveness and sensitivity of the proposed planning approach. The results show that our approach can potentially reduce the negative impact on the cross-layer and multi-cloud environment

Weight filtration on the cohomology of complex analytic spaces

We extend Deligne's weight filtration to the integer cohomology of complex analytic spaces (endowed with an equivalence class of compactifications). In general, the weight filtration that we obtain is not part of a mixed Hodge structure. Our purely geometric proof is based on cubical descent for resolution of singularities and Poincar\'e-Verdier duality. Using similar techniques, we introduce the singularity filtration on the cohomology of compactificable analytic spaces. This is a new and natural analytic invariant which does not depend on the equivalence class of compactifications and is related to the weight filtration.Comment: examples added + minor correction

Metabolic aspects of cardiovascular diseases: Is FoxO1 a player or a target?

The O subfamily of forkhead (FoxO) 1 is a crucial regulator of cell metabolism in several tissues, including the heart, where it is involved in cardiac regulation of glucose and lipid metabolic pathways, and endothelium, controlling the levels of some relevant biomarkers in atherosclerotic process. Despite the growing understanding of FoxO1 biology, the metabolic consequences of FoxO1 modifications and its implication in CVD, atherosclerosis and T2DM are still not incompletely described. In this review we discuss how FoxO1 affects cardiovascular pathophysiology and which of its effects should be restrained or enhanced to preserve endothelial and heart functions

FIGARO: reinForcement learnInG mAnagement acRoss the computing cOntinuum

The widespread adoption of Artificial Intelligence applications to analyze data generated by Internet of Things sensors leads to the development of the edge computing paradigm. Deploying applications at the periphery of the network effectively addresses cost and latency concerns associated with cloud computing. However, it generates a highly distributed environment with heterogeneous devices, opening the challenges of how to select resources and place application components. Starting from a state-of-the-art design-time tool, we present in this paper a novel framework based on Reinforcement Learning, named FIGARO (reinForcement learnInG mAnagement acRoss the computing cOntinuum). It handles the runtime adaptation of a computing continuum environment, dealing with the variability of the incoming load and service times. To reduce the training time, we exploit the design-time knowledge, achieving a significant reduction in the violations of the response time constraint

Diabetes influences cancer risk in patients with increased carotid atherosclerosis burden

Background and aims: Atherosclerosis and cancer share several risk factors suggesting that at least in part their pathogenesis is sustained by common mechanisms. To investigate this relation we followed a group of subjects with carotid atherosclerosis at baseline up for malignancy development.Methods and results: we carried out an observational study exploring cancer incidence (study endpoint) in subjects with known carotid atherosclerosis at baseline (n = 766) without previous cancer or carotid vascular procedures. During the follow-up (160 +/- 111 weeks) 24 cancer occurred, corresponding to an overall annual incidence rate of 0.11%. 10 diagnosis of cancer occurred in individuals with a carotid stenosis >50% (n = 90) whereas 14 in patients with a carotid stenosis <50% patients (n = 676) (p < 0.001). Respect to patients without cancer, diabetes was markedly more common in subjects with cancer diagnosis during the FU (37.3%vs75.0%, p < 0.001). After controlling for classic risk factors, carotid stenosis >50% (HR = 2.831, 95%CI = 1.034-5.714; p = 0.036) and diabetes (HR = 4.831, 95%CI = 1.506-15.501; p = 0.008) remained significantly associated with cancer diagnosis.Conclusions: to our knowledge this is the first study reporting a significant risk of cancer development in subjects with diabetes and high risk of cerebrovascular events, highlighting the need of a carefully clinical screening for cancer in diabetic patients with overt carotid atherosclerosis. (C) 2019 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved

Toward Solving the Mystery of Elevated Tectonic Degassing in South Eastern Europe: Insights From Gas Discharges Along the Vardar Suture (North Macedonia)

Tectonic carbon degassing is an important contributor to the global carbon cycle. South Eastern Europe is an active extensional tectonic region. This is the result of intense geodynamic events related to the closure of the Tethys Ocean, whose remnants include an ophiolite orogenic belt and the Vardar megasuture. In North Macedonia, regional active fault systems, seismic activity, Cenozoic-Quaternary volcanism, large-scale degassing, and low-enthalpy geothermal resources are widespread. Nonetheless, a geochemical characterization of the gas manifestations is missing from the literature. Toward this contribution, we report the first characterization of chemical and isotopic compositions of fluids from the main geothermal and cold gas manifestations of North Macedonia, and we explore their origins, the processes controlling their chemistry, and their relationships with the regional geodynamic situation. Gas samples were collected along the whole country, and were analyzed for both their chemical (He, H2, H2S, O2, N2, CO2, CH4, Ar) and isotopic composition (δ13C-CO2, He, Ar). Based on their chemistry, samples can be subdivided into three groups: (a) N2-dominated, (b) CO2-dominated, and (c) H2S-rich, which are geographically well separated, following regional distributions. The CO2-dominated group is the most widespread, highlighting the importance of geogenic carbon degassing in the study area. Its origin is prevailingly crustal (δ13C-CO2 = −4.6–+1.0‰ vs. V-PDB; R/RA = 0.1–1.8), but a significant, up to 25%, mantle contribution can be inferred from the He isotope composition

Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models

A challenging topic in surface engineering is predicting the wetting properties of soft interfaces with different liquids. However, a robust computational protocol suitable for predicting wettability with molecular precision is still lacking. In this article, we propose a workflow based on molecular dynamics simulations to predict the wettability of polymer surfaces and test it against the experimental contact angle of several polar and nonpolar liquids, namely water, formamide, toluene, and hexane. The specific case study addressed here focuses on a poly(lactic-co-glycolic acid) (PLGA) flat surface, but the proposed experimental-modeling protocol may have broader fields of application. The structural properties of PLGA slabs have been modeled on the surface roughness determined with microscopy measurements, while the computed surface tensions and contact angles were validated against standardized characterization tests, reaching a discrepancy of less than 3% in the case of water. Overall, this work represents the initial step toward an integrated multiscale framework for predicting the wettability of more complex soft interfaces, which will eventually take into account the effect of surface topology at higher scales and synergically be employed with experimental characterization techniques

A Serum Resistin and Multicytokine Inflammatory Pathway Is Linked With and Helps Predict All-cause Death in Diabetes

Context: Type 2 diabetes (T2D) shows a high mortality rate, partly mediated by atherosclerotic plaque instability. Discovering novel biomarkers may help identify high-risk patients who would benefit from more aggressive and specific managements. We recently described a serum resistin and multicytokine inflammatory pathway (REMAP), including resistin, interleukin (IL)-1 beta, IL-6, IL-8, and TNF-alpha, that is associated with cardiovascular disease.Objective: We investigated whether REMAP is associated with and improves the prediction of mortality in T2D.Methods: A REMAP score was investigated in 3 cohorts comprising 1528 patients with T2D (409 incident deaths) and in 59 patients who underwent carotid endarterectomy (CEA; 24 deaths). Plaques were classified as unstable/stable according to the modified American Heart Association atherosclerosis classification.Results: REMAP was associated with all-cause mortality in each cohort and in all 1528 individuals (fully adjusted hazard ratio [HR] for 1 SD increase=1.34, P<.001). In CEA patients, REMAP was associated with mortality (HR=1.64, P=.04) and a modest change was observed when plaque stability was taken into account (HR=1.58; P=.07). REMAP improved discrimination and reclassification measures of both Estimation of Mortality Risk in Type 2 Diabetic Patients and Risk Equations for Complications of Type 2 Diabetes, well-established prediction models of mortality in T2D (P<.05-<.001).Conclusion: REMAP is independently associated with and improves predict all-cause mortality in T2D; it can therefore be used to identify high-risk individuals to be targeted with more aggressive management. Whether REMAP can also identify patients who are more responsive to IL-6 and IL-1 beta monoclonal antibodies that reduce cardiovascular burden and total mortality is an intriguing possibility to be tested

High sensitivity C-reactive protein increases the risk of carotid plaque instability in male dyslipidemic patients

Background: The aim of this study was to evaluate how the high sensitivity C-reactive protein (hs-CRP) values influence the risk of carotid plaque instability in association with other cardiovascular risk factors. Methods: One hundred and fifty-six carotid plaques from both symptomatic and asymptomatic patients requiring surgical carotid endarterectomy were retrospectively collected. According to the modified American Heart Association, atherosclerosis plaques have been histologically distinguished into unstable and stable. The following anamnestic and hematochemical data were also considered: age, gender, hypertension, diabetes mellitus, smoking habit, therapy, low-density lipoprotein (LDL)-C, kidney failure and hs-CRP. Results: The results of our study clearly show that high levels of hs-CRP significantly increase the carotid plaque instability in dyslipidemic patients. Specifically, a 67% increase of the risk of carotid plaque instability was observed in patients with high LDL-C. Therefore, the highest risk was observed in male dyslipidemic patients 2333 (95% CI 0.73-7.48) and in aged female patients 2713 (95% CI 0.14-53.27). Discussion: These data strongly suggest a biological relationship between the hs-CRP values and the alteration of lipidic metabolism mostly in male patients affected by carotid atherosclerosis. The measurement of hs-CRP might be useful as a potential screening tool in the prevention of atheroscletotic disease

A climate-sensitive forest model for assessing impacts of forest management in Europe

FORMIT-M is a widely applicable, open-access, simple and flexible, climate-sensitive forest management simulator requiring only standard forest inventory data as input. It combines a process-based carbon balance approach with a strong inventory-based empirical component. The model has been linked to the global forest sector model EFI-GTM to secure consistency between timber cutting and demand, although prescribed harvest scenarios can also be used. Here we introduce the structure of the model and demonstrate its use with example simulations until the end of the 21st century in Europe, comparing different management scenarios in different regions under climate change. The model was consistent with country-level statistics of growing stock volumes (R-2=0.938) and its projections of climate impact on growth agreed with other studies. The management changes had a greater impact on growing stocks, harvest potential and carbon balance than projected climate change, at least in the absence of increased disturbance rates.Peer reviewe