Functional safety networks and protocols in the industrial internet of things era

Functional safety networks are becoming of paramount importance in industrial systems, due to the progressive innovation introduced by the Industry 4.0 paradigm, characterized by high production flexibility, reliability and scalability. In this context, new and challenging applications have emerged such as hyperautomation, which refers to the combination of machine vision, robotics, communication, and learning, with the explicit involvement of humans. This requires the pervasive and ubiquitous connectivity encompassed by the Industrial Internet of Things, typically achieved via wireless systems. As an example, wireless communications are today fundamental to open up to new categories of autonomous devices that can actively collaborate with human personnel in the production process. This challenging scenario has important implications for safety. Indeed, a reliable coordination among sensors, actuators and computing systems is required to provide satisfactory levels of safety, especially in the case of innovative processes and technologies, such as mobile and collaborative robotics. Hence, it becomes imperative to ensure the correct transfer of safety-critical data via communication networks. In this paper, we address the challenges concerned with functional safety networks and protocols in Industrial Internet of Things ecosystems. We first introduce the design characteristics of functional safety networks and discuss the adoption of safety protocols over wireless networks. Then, we specifically address one of such protocols, namely Fail Safety over EtherCAT (FSoE), and provide the results of an extensive experimental session carried out exploiting a prototype system, implemented using commercial devices based on a WiFi network. Finally, the outcomes of the experiments are used as a basis for a discussion about future trends of functional safety in the Industrial Internet of Things era

Optimal Inspection and Maintenance Planning for Deteriorating Structural Components through Dynamic Bayesian Networks and Markov Decision Processes

Civil and maritime engineering systems, among others, from bridges to offshore platforms and wind turbines, must be efficiently managed as they are exposed to deterioration mechanisms throughout their operational life, such as fatigue or corrosion. Identifying optimal inspection and maintenance policies demands the solution of a complex sequential decision-making problem under uncertainty, with the main objective of efficiently controlling the risk associated with structural failures. Addressing this complexity, risk-based inspection planning methodologies, supported often by dynamic Bayesian networks, evaluate a set of pre-defined heuristic decision rules to reasonably simplify the decision problem. However, the resulting policies may be compromised by the limited space considered in the definition of the decision rules. Avoiding this limitation, Partially Observable Markov Decision Processes (POMDPs) provide a principled mathematical methodology for stochastic optimal control under uncertain action outcomes and observations, in which the optimal actions are prescribed as a function of the entire, dynamically updated, state probability distribution. In this paper, we combine dynamic Bayesian networks with POMDPs in a joint framework for optimal inspection and maintenance planning, and we provide the formulation for developing both infinite and finite horizon POMDPs in a structural reliability context. The proposed methodology is implemented and tested for the case of a structural component subject to fatigue deterioration, demonstrating the capability of state-of-the-art point-based POMDP solvers for solving the underlying planning optimization problem. Within the numerical experiments, POMDP and heuristic-based policies are thoroughly compared, and results showcase that POMDPs achieve substantially lower costs as compared to their counterparts, even for traditional problem settings

An IoT Measurement System Based on LoRaWAN for Additive Manufacturing

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible

Urban Climate Action. The urban content of the NDCs: Global review 2022

This report was prepared by United Nations Human Settlement Programme (UN-Habitat) and the UNESCO Chair on Urban Resilience at the University of Southern Denmark (SDU.Resilience). It offers a global analysis of the urban content of 193 Nationally Determined Contributions (NDCs) submitted to the Secretariat of the United Nations Framework Convention on Climate Change (UNFCCC) before the 19th of June 2022. For this report, more than 200 indicators were used to analyse external data (e.g., Human Development Index and income categorisation) and data within the NDCs, including climate mitigation and adaptation challenges and responses, as well as specific sectors. This analysis is instrumental to supporting Parties’ efforts in further integrating national climate policies and urban climate actions, which is considered fundamental to raising ambition and developing adequate and timely actions as required by the current climate emergency. This review can be instrumental for advocacy and direct support to countries by partner organisations. The work was supported by a group of experts from bilateral and multilateral organisations and academia. Three expert group meetings were convened, and a peer review was organised for the final report

Experiência da mulher agricultora na governança da Associação OPAC Maniva, Manaus/Amazonas.

O presente relato visa narrar os desafios e oportunidades da mulher agricultora na coordenação geral da Associação do Organismo Participativo de Avaliação da Conformidade (OPAC), denominado de OPAC Maniva

Theory of the Relativistic Brownian Motion. The (1+1)-Dimensional Case

We construct a theory for the 1+1-dimensional Brownian motion in a viscous medium, which is (i) consistent with Einstein's theory of special relativity, and (ii) reduces to the standard Brownian motion in the Newtonian limit case. In the first part of this work the classical Langevin equations of motion, governing the nonrelativistic dynamics of a free Brownian particle in the presence of a heat bath (white noise), are generalized in the framework of special relativity. Subsequently, the corresponding relativistic Langevin equations are discussed in the context of the generalized Ito (pre-point discretization rule) vs. the Stratonovich (mid-point discretization rule) dilemma: It is found that the relativistic Langevin equation in the Haenggi-Klimontovich interpretation (with the post-point discretization rule) is the only one that yields agreement with the relativistic Maxwell distribution. Numerical results for the relativistic Langevin equation of a free Brownian particle are presented.Comment: see cond-mat/0607082 for an improved theor

The Schroedinger Problem, Levy Processes Noise in Relativistic Quantum Mechanics

The main purpose of the paper is an essentially probabilistic analysis of relativistic quantum mechanics. It is based on the assumption that whenever probability distributions arise, there exists a stochastic process that is either responsible for temporal evolution of a given measure or preserves the measure in the stationary case. Our departure point is the so-called Schr\"{o}dinger problem of probabilistic evolution, which provides for a unique Markov stochastic interpolation between any given pair of boundary probability densities for a process covering a fixed, finite duration of time, provided we have decided a priori what kind of primordial dynamical semigroup transition mechanism is involved. In the nonrelativistic theory, including quantum mechanics, Feyman-Kac-like kernels are the building blocks for suitable transition probability densities of the process. In the standard "free" case (Feynman-Kac potential equal to zero) the familiar Wiener noise is recovered. In the framework of the Schr\"{o}dinger problem, the "free noise" can also be extended to any infinitely divisible probability law, as covered by the L\'{e}vy-Khintchine formula. Since the relativistic Hamiltonians $|\nabla |$ and $\sqrt {-\triangle +m^2}-m$ are known to generate such laws, we focus on them for the analysis of probabilistic phenomena, which are shown to be associated with the relativistic wave (D'Alembert) and matter-wave (Klein-Gordon) equations, respectively. We show that such stochastic processes exist and are spatial jump processes. In general, in the presence of external potentials, they do not share the Markov property, except for stationary situations. A concrete example of the pseudodifferential Cauchy-Schr\"{o}dinger evolution is analyzed in detail. The relativistic covariance of related waveComment: Latex fil

Genome-wide signatures of complex introgression and adaptive evolution in the big cats.

The great cats of the genus Panthera comprise a recent radiation whose evolutionary history is poorly understood. Their rapid diversification poses challenges to resolving their phylogeny while offering opportunities to investigate the historical dynamics of adaptive divergence. We report the sequence, de novo assembly, and annotation of the jaguar (Panthera onca) genome, a novel genome sequence for the leopard (Panthera pardus), and comparative analyses encompassing all living Panthera species. Demographic reconstructions indicated that all of these species have experienced variable episodes of population decline during the Pleistocene, ultimately leading to small effective sizes in present-day genomes. We observed pervasive genealogical discordance across Panthera genomes, caused by both incomplete lineage sorting and complex patterns of historical interspecific hybridization. We identified multiple signatures of species-specific positive selection, affecting genes involved in craniofacial and limb development, protein metabolism, hypoxia, reproduction, pigmentation, and sensory perception. There was remarkable concordance in pathways enriched in genomic segments implicated in interspecies introgression and in positive selection, suggesting that these processes were connected. We tested this hypothesis by developing exome capture probes targeting ~19,000 Panthera genes and applying them to 30 wild-caught jaguars. We found at least two genes (DOCK3 and COL4A5, both related to optic nerve development) bearing significant signatures of interspecies introgression and within-species positive selection. These findings indicate that post-speciation admixture has contributed genetic material that facilitated the adaptive evolution of big cat lineages