Reconfiguration of optical-NFV network architectures based on cloud resource allocation and QoS degradation cost-aware prediction techniques

The high time required for the deployment of cloud resources in Network Function Virtualization network architectures has led to the proposal and investigation of algorithms for predicting trafc or the necessary processing and memory resources. However, it is well known that whatever approach is taken, a prediction error is inevitable. Two types of prediction errors can occur that have a different impact on the increase in network operational costs. In case the predicted values are higher than the real ones, the resource allocation algorithms will allocate more resources than necessary with the consequent introduction of an over-provisioning cost. Conversely, when the predicted values are lower than the real values, the allocation of fewer resources will lead to a degradation of QoS and the introduction of an under-provisioning cost. When over-provisioning and under-provisioning costs are different, most of the prediction algorithms proposed in the literature are not adequate because they are based on minimizing the mean square error or symmetric cost functions. For this reason we propose and investigate a forecasting methodology in which it is introduced an asymmetric cost function capable of weighing the costs of over-provisioning and under-provisioning differently. We have applied the proposed forecasting methodology for resource allocation in a Network Function Virtualization architectures where the Network Function Virtualization Infrastructure Point-of-Presences are interconnected by an elastic optical network.We have veried a cost savings of 40% compared to solutions that provide a minimization of the mean square error

Proposal and investigation of an artificial intelligence (Ai)-based cloud resource allocation algorithm in network function virtualization architectures

The high time needed to reconfigure cloud resources in Network Function Virtualization network environments has led to the proposal of solutions in which a prediction based-resource allocation is performed. All of them are based on traffic or needed resource prediction with the minimization of symmetric loss functions like Mean Squared Error. When inevitable prediction errors are made, the prediction methodologies are not able to differently weigh positive and negative prediction errors that could impact the total network cost. In fact if the predicted traffic is higher than the real one then an over allocation cost, referred to as over-provisioning cost, will be paid by the network operator; conversely, in the opposite case, Quality of Service degradation cost, referred to as under-provisioning cost, will be due to compensate the users because of the resource under allocation. In this paper we propose and investigate a resource allocation strategy based on a Long Short Term Memory algorithm in which the training operation is based on the minimization of an asymmetric cost function that differently weighs the positive and negative prediction errors and the corresponding over-provisioning and under-provisioning costs. In a typical traffic and network scenario, the proposed solution allows for a cost saving by 30% with respect to the case of solution with symmetric cost function

Polyphenols rich diets and risk of type 2 diabetes

Type 2 diabetes is an increasing health concern worldwide. Both genetic and environmental risk factors as improper dietary habits or physical inactivity are known to be crucial in the pathogen-esis of type 2 diabetes. Polyphenols are a group of plant-derived compounds with anti-inflammatory and antioxidant properties that are associated with a low prevalence of metabolic conditions charac-terized by insulin resistance, including obesity, diabetes, and hypertension. Moreover, there is now full awareness that foods that are rich in phytochemicals and polyphenols could play an important role in preserving human cardiovascular health and substantial clinical evidence indicates that regu-lar dietary consumption of such foods affects favorably carbohydrate metabolism. This review briefly summarizes the evidence relating dietary patterns rich in polyphenols with glucose metabolism and highlights the potential benefits of these compounds in the prevention of type 2 diabetes

Sepsis Team Organizational Model to Decrease Mortality for Intra-Abdominal Infections: Is Antibiotic Stewardship Enough?

Introduction. Sepsis is an overwhelming reaction to infection with significant morbidity, requiring urgent interventions in order to improve outcomes. The 2016 Sepsis-3 guidelines modified the previous definitions of sepsis and septic shock, and proposed some specific diagnostic and therapeutic measures to define the use of fluid resuscitation and antibiotics. However, some open issues still exist. Methods. A literature research was performed on PubMed and Cochrane using the terms “sepsis” AND “intra-abdominal infections” AND (“antibiotic therapy” OR “antibiotic treatment”). The inclusion criteria were management of intra-abdominal infection (IAI) and effects of antibiotic stewardships programs (ASP) on the outcome of the patients. Discussion. Sepsis-3 definitions represent an added value in the understanding of sepsis mechanisms and in the management of the disease. However, some questions are still open, such as the need for an early identification of sepsis. Sepsis management in the context of IAI is particularly challenging and a prompt diagnosis is essential in order to perform a quick treatment (source control and antibiotic treatment). Antibiotic empirical therapy should be based on the kind of infection (community or hospital acquired), local resistances, and patient’s characteristic and comorbidities, and should be adjusted or de-escalated as soon as microbiological information is available. Antibiotic Stewardship Programs (ASP) have demonstrated to improve antimicrobial utilization with reduction of infections, emergence of multi-drug resistant bacteria, and costs. Surgeons should not be alone in the management of IAI but ideally inserted in a sepsis team together with anaesthesiologists, medical physicians, pharmacists, and infectious diseases specialists, meeting periodically to reassess the response to the treatment. Conclusion. The cornerstones of sepsis management are accurate diagnosis, early resuscitation, effective source control, and timely initiation of appropriate antimicrobial therapy. Current evidence shows that optimizing antibiotic use across surgical specialities is imperative to improve outcomes. Ideally every hospital and every emergency surgery department should aim to provide a sepsis team in order to manage IAI

Constraints on massive gravity theory from big bang nucleosynthesis

The massive gravity cosmology is studied in the scenario of big bang nucleosynthesis. By making use of current bounds on the deviation from the fractional mass, we derive the constraints on the free parameters of the theory. The cosmological consequences of the model are also discussed in the framework of the PAMELA experiment.Comment: 5 page

Antibiotic De-Escalation in Emergency General Surgery

Background. Antibiotic treatment in emergency general surgery (EGS) is a major challenge for surgeons, and a multidisciplinary approach is necessary in order to improve outcomes. Intra-abdominal infections are at high risk of increased morbidity and mortality, and prolonged hospitalization. An increase in multi-drug resistance bacterial infections and a tendency to an antibiotic overuse has been described in surgical settings. In this clinical scenario, antibiotic de-escalation (ADE) is emerging as a strategy to improve the management of antibiotic therapy. The objective of this article is to summarize the available evidence, current strategies and unsolved problems for the optimization of ADE in EGS. Methods. A literature search was performed on PubMed and Cochrane using “de-escalation”, “antibiotic therapy” and “antibiotic treatment” as research terms. Results. There is no universally accepted definition for ADE. Current evidence shows that ADE is a feasible strategy in the EGS setting, with the ability to optimize antibiotic use, to reduce hospitalization and health care costs, without compromising clinical outcome. Many studies focus on Intensive Care Unit patients, and a call for further studies is required in the EGS community. Current guidelines already recommend ADE when surgery for uncomplicated appendicitis and cholecystitis reaches a complete source control. Conclusions. ADE in an effective and feasible strategy in EGS patients, in order to optimize antibiotic management without compromising clinical outcomes. A collaborative effort between surgeons, intensivists and infectious disease specialists is mandatory. There is a strong need for further studies selectively focusing in the EGS ward setting

Monocular electro-optical stereo scanner

MEOSS is a single optics and single spectral band camera. Three CCD's working in pushbroom mode are mounted perpendicular to the flight direction on a common focal plate. Their oblique views of + and - 23 degrees forward and backward, as well as nadir oriented, lead to threefold stereoscopic images. This principle allows a nearly simultaneous generation of all three images of a stereo triplet. The time gap between the forward and aft looking images guarantees constant illumination conditions. The ground resolution of MEOSS will be 52 by 80 m ground pixel size, height resolution of 55 m and swath width of 255 km. The drifting ground coverage pattern of MEOSS is unique compared to polar orbiting satellites and will allow images of an area to be taken at different times of the day. A scene will consist of 3144 scan lines, with each having 3236 pixels. The data will be received by the Deep Space Network of JPL Goldstone and mailed to Goddard

Short-term cardiac outcome in survivors of COVID-19: a systematic study after hospital discharge

Background: COVID-19 has caused considerable morbidity and mortality worldwide and cardiac involvement has been reported during infection. The short-term cardiac outcome in survivors of COVID-19 is not known. Objective: To examine the heart of patients who survived COVID-19 and to compare the cardiac outcome between patients who recovered from mild-to-moderate or severe illness. Methods: With use of ECG and echocardiography, we examined the heart of 105 patients who had been hospitalized with COVID-19 and were consecutively recruited after hospital discharge while attending follow-up visits. Survivors of COVID-19 were compared with 105 matched controls. We also compared the cardiac outcome and lung ultrasound scan between COVID-19 patients who had mild-to-moderate or severe illness. Results: Cardiac data were collected a median of 41\ua0days from the first detection of COVID-19. Symptoms were present in a low percentage of patients. In comparison with matched controls, no considerable structural or functional differences were observed in the heart of survivors of COVID-19. Lung ultrasound scan detected significantly greater residual pulmonary involvement in COVID-19 patients who had recovered from severe than mild-to-moderate illness. No significant differences were detected in ECG tracings nor were found in the left and right ventricular function of patients who had recovered from mild-to-moderate or severe illness. Conclusions: In a short-term follow-up, no abnormalities were identified in the heart of survivors of COVID-19, nor cardiac differences were detected between patients who had different severity of illness. With the limitations of a cross-sectional study, these findings suggest that patients who recover from COVID-19 do not have considerable cardiac sequelae. Graphic abstract: [Figure not available: see fulltext.

Non-chaotic dynamics in general-relativistic and scalar-tensor cosmology

In the context of scalar-tensor models of dark energy and inflation, the dynamics of vacuum scalar-tensor cosmology are analysed without specifying the coupling function or the scalar field potential. A conformal transformation to the Einstein frame is used and the dynamics of general relativity with a minimally coupled scalar field are derived for a generic potential. It is shown that the dynamics are non-chaotic, thus settling an existing debate.Comment: 20 pages, LaTeX, to appear in Class. Quantum Gra

Limits on Dark Matter Effective Field Theory Parameters with CRESST-II

CRESST is a direct dark matter search experiment, aiming for an observation of nuclear recoils induced by the interaction of dark matter particles with cryogenic scintillating calcium tungstate crystals. Instead of confining ourselves to standard spin-independent and spin-dependent searches, we re-analyze data from CRESST-II using a more general effective field theory (EFT) framework. On many of the EFT coupling constants, improved exclusion limits in the low-mass region (< 3-4 GeV) are presented.Comment: 7 pages, 9 figure