An alternative proof of well-posedness of stochastic evolution equations in the variational setting

We present a new proof of well-posedness of stochastic evolution equations in variational form, relying solely on a (nonlinear) infinite-dimensional approximation procedure rather than on classical finite-dimensional projection arguments of Galerkin type

Application-Aware Network Traffic Management in MEC-Integrated Industrial Environments

The industrial Internet of things (IIoT) has radically modified industrial environments, not only enabling novel industrial applications but also significantly increasing the amount of generated network traffic. Nowadays, a major concern is to support network-intensive industrial applications while ensuring the prompt and reliable delivery of mission-critical traffic flows concurrently traversing the industrial network. To this end, we propose application-aware network traffic management. The goal is to satisfy the requirements of industrial applications through a form of traffic management, the decision making of which is also based on what is carried within packet payloads (application data) in an efficient and flexible way. Our proposed solution targets multi-access edge computing (MEC)-integrated industrial environments, where on-premises and off-premises edge computing resources are used in a coordinated way, as it is expected to be in future Internet scenarios. The technical pillars of our solution are edge-powered in-network processing (eINP) and software-defined networking (SDN). The concept of eINP differs from INP because the latter is directly performed on network devices (NDs), whereas the former is performed on edge nodes connected via high-speed links to NDs. The rationale of eINP is to provide the network with additional capabilities for packet payload inspection and processing through edge computing, either on-premises or in the MEC-enabled cellular network. The reported in-the-field experimental results show the proposal feasibility and its primary tradeoffs in terms of performance and confidentiality

Landslide damming hazard susceptibility maps: a new GIS-based procedure for risk management

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Nutrients and pathways that regulate health span and life span

Both life span and health span are influenced by genetic, environmental and lifestyle factors. With the genetic influence on human life span estimated to be about 20\u201325%, epigenetic changes play an important role in modulating individual health status and aging. Thus, a main part of life expectance and healthy aging is determined by dietary habits and nutritional factors. Excessive or restricted food consumption have direct effects on health status. Moreover, some dietary interventions including a reduced intake of dietary calories without malnutrition, or a restriction of specific dietary component may promote health benefits and decrease the incidence of aging-related comorbidities, thus representing intriguing potential approaches to improve healthy aging. However, the relationship between nutrition, health and aging is still not fully understood as well as the mechanisms by which nutrients and nutritional status may affect health span and longevity in model organisms. The broad effect of different nutritional conditions on health span and longevity occurs through multiple mechanisms that involve evolutionary conserved nutrient-sensing pathways in tissues and organs. These pathways interacting each other include the evolutionary conserved key regulators mammalian target of rapamycin, AMP-activated protein kinase, insulin/insulin-like growth factor 1 pathway and sirtuins. In this review we provide a summary of the main molecular mechanisms by which different nutritional conditions, i.e., specific nutrient abundance or restriction, may affect health span and life span

Co-occurrence of autoimmune thyroid disease in a multiple sclerosis cohort

BACKGROUND: Multiple sclerosis (MS), Hashimoto's disease and Graves' disease are autoimmune diseases that may share similar pathogenic mechanisms. The co-occurrence rates and demographic characteristics of Graves' disease and Hashimoto's disease (HT) in our MS population are compared with the general population. METHODS: The prevalence of thyroid disease in our MS patients was determined by chart review and survey. Previous diagnosis of thyroid disease, age at diagnosis, treatment used, and about the use of disease modifying medications used to treat their MS were asked. Chart reviews were used to estimate the population prevalence of Graves' disease and Hashimoto's disease and to estimate the demographics of patients with thyroid disease. RESULTS: A significant co-occurrence of Graves' disease with MS (p = 0.002), and a non-significant co-occurrence of Hashimoto's disease were noted (p = 0.097). No difference in the age of onset or gender of thyroid disease in MS patients compared to the general population was found. CONCLUSION: There is a significant co-occurrence in patients with MS and Graves' disease, and a trend to co-occurrence in patients with MS and Hashimoto's disease. There are no differences in the demographics of patients with thyroid disease in our MS patients compared to the general population

Correction to: Morphological analysis and features of the landslide dams in the Cordillera Blanca, Peru

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Seaweed supplementation failed to affect fecal microbiota and metabolome as well as fecal iga and apparent nutrient digestibility in adult dogs

The present study investigated in dogs the dietary effects of intact seaweeds on some fecal bacterial populations and metabolites, fecal IgA and apparent total tract digestibility (ATTD). Ten healthy adult dogs were enrolled in a 5 × 5 replicated Latin square design to evaluate five dietary treatments: control diet (CD); CD + Ascophyllum nodosum; CD + Undaria pinnatifida; CD + Saccharina japonica; CD + Palmaria palmata (n replicates per treatment = 10). Seaweeds were added to food at a daily dose of 15 g/kg. The CD contained silica as a digestion marker. Each feeding period lasted 28 d, with a 7 d wash-out in between. Feces were collected at days 21 and 28 of each period for chemical and microbiological analyses. Fecal samples were collected during the last five days of each period for ATTD assessment. Dogs showed good health conditions throughout the study. The fecal chemical parameters, fecal IgA and nutrient ATTD were not influenced by algal supplementation. Similarly, microbiological analyses did not reveal any effect by seaweed ingestion. In conclusion, algal supplementation at a dose of 15 g/kg of diet failed to exert noticeable effects on the canine fecal parameters evaluated in the present study

A Framework for QoS- Enabled Semantic Routing in Industrial Networks: Overall Architecture and Primary Protocols

The manufacturing sector represents a notable use case of the Industry 4.0 revolution, heavily stressing the capability of plants to ensure the desired QoS. Currently, manufacturing plants are characterized by an increasing amount of non-mission-critical traffic, in addition to traditional mission-critical safety-related traffic, which is negligible in comparison. Since computing and networking capabilities are no longer as abundant as in the past, there is the need to properly manage available resources. To ensure challenging QoS requirements, we propose a novel protocol suite specifically designed for our QoS-enabled semantic routing framework. Such a framework adopts an architecture that fits the characteristics of modern manufacturing environments and exploits an overlay networking solution providing a semantic routing substrate that operates both at the application and network layers

Fog-Driven Context-Aware Architecture for Node Discovery and Energy Saving Strategy for Internet of Things Environments

The consolidation of the Fog Computing paradigm and the ever-increasing diffusion of Internet of Things (IoT) and smart objects are paving the way toward new integrated solutions to efficiently provide services via short-mid range wireless connectivity. Being the most of the nodes mobile, the node discovery process assumes a crucial role for service seekers and providers, especially in IoT-fog environments where most of the devices run on battery. This paper proposes an original model and a fog-driven architecture for efficient node discovery in IoT environments. Our novel architecture exploits the location awareness provided by the fog paradigm to significantly reduce the power drain of the default baseline IoT discovery process. To this purpose, we propose a deterministic and competitive adaptive strategy to dynamically adjust our energy-saving techniques by deciding when to switch BLE interfaces ON/OFF based on the expected frequency of node approaching. Finally, the paper presents a thorough performance assessment that confirms the applicability of the proposed solution in several different applications scenarios. This evaluation aims also to highlight the impact of the nodes' dynamic arrival on discovery process performance