Background and aims Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data. Design Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017. Setting and Participants Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Measurements Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads. Findings Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data.

In this study, we examine associations between the quality of teacher-child interactions and infant outcomes during their first months in Portuguese childcare centers. Participants were 90 infants, their mothers and their teachers. A set of multiple regression models were conducted to determine whether classroom quality related to active engagement and non-engagement and to adaptive behavior six months later, controlling for important covariates, namely developmental age, child temperament, mothers’ education, and home quality. Results showed that, in higher quality classrooms, infants spent more time actively engaged, less time non-engaged and six months later were rated as having higher levels of adaptive behaviors. Findings provide further evidence for the need to better support teachers in fostering infant active engagement and unfolding capacities as part of high-quality daily experiences in childcare.

Concurrent programming is dominated by thread based solutions with lock based critical sections. Careful attention has to be paid to avoid race and deadlock conditions. Real-Time for The Masses (RTFM) takes an alternative language approach, introducing tasks and named critical sections (via resources) natively in the RTFM-core language. RTFM-core programs can be compiled to native C-code, and efficiently executed onto single-core platforms under the Stack Resource Policy (SRP) by the RTFM-kernel. In this paper we formally define the well-formedness criteria for SRP based resource management, and develop a certified (formally proven) implementation of the corresponding compilation from nested critical sections of the input RTFM-core program to a resulting flat sequence of primitive operations and scheduling primitives. Moreover we formalise the properties for resource ceilings under SRP and develop a certified algorithm for their computation. The feasibility of the described approach is shown through the adoption of the Why3 platform, which allows the necessary verification conditions to be automatically generated and discharged through a variety of automatic external SMT-solvers and interactive theorem provers. Moreover, Why3 supports the extraction of certified Ocaml code for proven implementations in WhyML. As a proof of concept the certified extracted development is demonstrated on an example system.

Network diversity multiple access (NDMA) is the family of algorithms with the highest potential throughput in the literature of signal-processing assisted random access protocols. NDMA uses the concept of protocol-induced retransmissions to create an adaptive source of diversity. This diversity is used to resolve packet collisions employing signal separation tools without the explicit need (or as a complement) of a multiple antenna receiver. This paper proposes a further improvement on the performance of NDMA by allowing each terminal access to an outdated copy of its individual channel state information (CSI). Based on this decentralized CSI, each terminal conveniently decides to transmit only if the estimated channel gain surpasses a threshold that is optimized to maximize performance. This ensures that the probability of terminal presence detection, and thus the probability of correct estimation of the collision multiplicity are considerably improved at the receiver end. The paper is focused on the modelling of the receiver operational characteristic (ROC) of the terminal presence detector considering that the CSI used by each terminal is potentially inaccurate (outdated) due to feedback delay. The results indicate that when the correlation coefficient that describes the accuracy of the available CSI tends to zero, the scheme degrades into the conventional NDMA. By contrast, when the quality of the channel state information improves, the throughput can nearly achieve the nominal channel rate (minimum throughput penalty). The selection of the detector thresholds for channel gain and terminal presence is optimized to maximize system performance.

The state-of-the-art models and schedulability analysis for mixed-criticality multicore systems overlook low-level aspects of the system. To improve their credibility, we therefore incorprate, in this work, the effects of delays from memory contention on a shared bus. Specifically, to that end, we adopt the predictable memory reservation mechanism proposed by the Single Core Equivalence framework. Additionally, we explore how the reclamation, for higher-criticality tasks, of cache resources allocated to lower-criticality tasks, whenever there is a criticality (mode) change in the system, can improve schedulability.

The development of demand response programs has been allowing to improve power system performance in several ways, both in terms of the management of electricity markets, as well as regarding benefits in its operation. In order to model the remuneration for the participation of consumers in the scheduling of resources, this paper proposes a methodology based on the use of four incentive-based tariffs for the remuneration of demand response participation. It considers steps, quadratic, constant and linear remuneration. The optimization model enables Virtual Power Players to minimize operation costs, considering different critical situations of management and operation. The optimization problem has been solved by Quantum Particle Swarm Optimization. The case study concerns 168 consumers, classified into 5 consumer types, 118 distributed generation resources and 4 external suppliers.

In this paper, we develop a framework for building context-aware applications in IoT. The IoT paradigm brings in various new issues such as macroprogramming, interoperability for heterogeneous devices and in-network processing. Solutions to these issues can enable IoT to support all available resources in an efficient manner and also enable ease of access for users. In addition, this can help in collecting useful information about the user and the system, such as context. Understanding context of different entities and taking actions accordingly will enable a context-aware IoT. However, no complete solution is available to this issue of achieving context-awareness in IoT. In this paper, as a step towards a context-aware framework, we present a mobilityenabling extension of the T-Res programming abstraction. We implement a web-based framework for users to write contextaware applications. We then describe and implement an automated mechanism for deploying these applications.

Several methods have been proposed for performing schedulability analysis for both uni-processor and multi-processor real-time systems. Very few of these works use the power of formal logic to write unambiguous specifications and to allow the usage of theorem provers for building the proofs of interest with greater correctness guarantees. In this paper we address this challenge by: 1) defining a formal language that allows to specify periodic resource models; 2) describe a transformational approach to reasoning about timing properties of resource models by transforming the latter specifications into a SMT problem.

The Event Handler systems is part of the Arrowhead Framework, which aims to apply Service Oriented Architecture to the embedded systems' world. The Event Handler system is a component that supports the handling of events, and in that sense it enriches service-oriented applications with the capabilities of interacting via the publish/subscribe paradigm. In fact, the Event Handler core system is in charge of the notification of events that occur in a given Arrowhead compliant installation, manages producers and consumers of events, allows filtering of messages, and manages historical data regarding events. This latter capability is performed either on local files, on a database, or through another component of the Arrowhead Framework - the Historian system. Two examples of the application of the Event Handler system are described: the management of application faults, and the support to quality of service of orchestrated services.

In mixed-criticality multicore systems, the appropriate degree of isolation between applications of different criticalities is a primary objective. However, efficient utilization of the platform’s processing capacity and other resources is still desirable and important. In recent work, we, therefore, proposed an approach that reclaims cache resources assigned to low-criticality tasks when these are dispensed with, in the event of a system mode change. The reclaimed cache resources are reassigned from the lower-criticality tasks to the remaining higher-criticality tasks to improve performance. The per-task cache partitions can either be configured to hold frequently accessed (“hot”) pages, locked in place, or they can be used dynamically, with cache lines moved in and out. The first option simplifies WCET analysis while the second option simplifies the act of cache reconfiguration at runtime. Meanwhile, the performance implications of the two options are not immediately obvious. Therefore, in this work-in-progress, we explore an arrangement that combines both approaches, in order to achieve the best tradeoff between efficient analysis, low reconfiguration overheads and good schedulability Simple per task cache partitions (without page locking) are to be used for the portion of the cache that is subject to reclamation. At mode switch, the high-criticality tasks keep the pages they had locked in the cache and get additional partitions, out of reclaimed cache, to bring other pages in and out as needed.