The evolution of phosphorus (P) management decision support tools (DSTs) and systems (DSS), in support of food and environmental security has been most strongly affected in developed regions by national strategies (i) to optimize levels of plant available P in agricultural soils, and (ii) to mitigate P runoff to water bodies. In the United States, Western Europe, and New Zealand, combinations of regulatory and voluntary strategies, sometimes backed by economic incentives, have often been driven by reactive legislation to protect water bodies. Farmer-specific DSSs, either based on modeling of P transfer source and transport mechanisms, or when coupled with farm-specific information or local knowledge, have typically guided best practices, education, and implementation, yet applying DSSs in data poor catchments and/or where user adoption is poor hampers the effectiveness of these systems. Recent developments focused on integrated digital mapping of hydrologically sensitive areas and critical source areas, sometimes using real-time data and weather forecasting, have rapidly advanced runoff modeling and education. Advances in technology related to monitoring, imaging, sensors, remote sensing, and analytical instrumentation will facilitate the development of DSSs that can predict heterogeneity over wider geographical areas. However, significant challenges remain in developing DSSs that incorporate "big data" in a format that is acceptable to users, and that adequately accounts for catchment variability, farming systems, and farmer behavior. Future efforts will undoubtedly focus on improving efficiency and conserving phosphate rock reserves in the face of future scarcity or prohibitive cost. Most importantly, the principles reviewed here are critical for sustainable agriculture.

To achieve efficient and flexible production at affordable prices, industrial automation is pushed towards a digital transformation. Such a transformation assumes an enhancement of current Industrial Automated Control Systems with a large amount of IoT-devices, forming an Industrial Internet of Things (IIoT). The aim is to enable a shift from automatic towards autonomous control in such systems. This paper discusses some of the main challenges IIoT systems are facing with respect to cybersecurity. We discuss our findings in an example of a flow-control loop, where we apply a simple threat model based on the STRIDE method to deduce cybersecurity requirements in an IIoT context. Moreover, the identified requirements are assessed in the light of current state of the art solutions, and a number of challenges are discussed with respect to a large-scale IIoT system, together with some suggestions for future work.

In process automation installations, the I/O system connect the field devices to the process controller over a fieldbus, a reliable, real-time capable communication link with signal values cyclical being exchanged with a 10–100 millisecond rate. If a deviation from intended behaviour occurs, analyzing the potentially vast data recordings from the field can be a time consuming and cumbersome task for an engineer. For the engineer to be able to get a full understanding of the problem, knowledge of the used I/O configuration is required. In the problem report, the configuration description is sometimes missing. In such cases it is difficult to use the recorded data for analysis of the problem.In this paper we present our ongoing work towards using neural network models as assistance in the interpretation of an industrial fieldbus communication recording. To show the potential of such an approach we present an example using an industrial setup where fieldbus data is collected and classified. In this context we present an evaluation of the suitability of different neural net configurations and sizes for the problem at hand.

There is a growing interest in using the Blockchain for resolving IoT security and trustworthiness issues existing in today’s complex systems. Blockchain concerns trust in peer to peer networks by providing a distributed tamper-resistant ledger. However, the combination of these two emerging technologies might create new problems and vulnerabilities that attackers might abuse.In this paper, we aim to investigate the trust mechanism of Lightweight Scalable BlockChain (LSB), that is a Blockchain specifically designed for Internet of Things networks, to show that a malicious participant in a Blockchain architecture have possibility to pursue an On-Off attack and downgrade the integrity of the distributed ledger. We choose a remote software update process as an instance to represent this violation. Finally, using the actor-based language Rebeca, we provide a model of a system under attack and verify the described attack scenario.

Objectives We sought to determine the feasibility and characterize the extinction kinetics of circulating cell-free tumor DNA (cfDNA) testing in endometrial and ovarian carcinomas (ECs, OCs) using a clinically-approved commercially-available assay. Methods Women with suspected EC/OC undergoing surgery were consented for tissue and plasma sampling including pre-operative and serial post-operative draws. Tumour tissue and patient-matched buffy coat was extracted for DNA and sequenced for somatic mutations using FINDIT™ panel assay. Plasma samples were extracted for cfDNA and sequenced using FOLLOWIT™, Illumina platform, and analyzed using Contextual Genomics’s QUALITY NEXUS analysis pipelines. Low-frequency variants were confirmed by digital droplet PCR. Results 44 individuals had sufficient tissue and follow-up for inclusion; 24 ECs (13 endometrioid, 10 high-grade serous (HGS), 1 clear cell(CC)), 18 OCs (17 HGS 1, CC), and 2 synchronous endometrial and ovarian carcinomas. Eight ECs and 15 OC cases were advanced stage (II-IV) with residual disease in 2 ECs and 5 OCs, 8 recurrence events and 3 deaths recorded. Compliance with plasma sampling was high(>95%) when requested in hospital or at routine surveillance visits but dropped to 68% for ‘extra’ study-associated visits. Analysis to date reveals cfDNA was detectable in pre-operative samples of 19 individuals (9 ECs, 10 OCs including 4 early stage) and 6/10 tested post-operatively. Normalization of conventional tumour markers post-operatively took a median of 3mo in contrast to rapid loss of detectable cfDNA. Conclusions cfDNA testing is feasible and may enhance surveillance of endometrial and ovarian carcinomas by reflecting i) volume of disease pre-/post-operatively, ii) response to therapy, and/or iii) recurrence.

Changing the optical fiber parameters during long-term use can not be mathematically calculated. This paper analyses the change of optical fibers from the aspect of ageing under the influence of transmitted signals and the aspect of water influences. The analysis was carried out in such a way as to compare the measurements carried out after the installation of optical cables and measurements after 16 years of use. The analysis has been shown to vary greatly the loss of fiber optic splice for different wavelengths. These different loss for wavelengths 1310 nm and 1550 nm suggest that the loss of optical fiber has increased due to the impact of water.

The purpose of this research article is to provide the fresh evidence on the link between energy consumption (ENE) and economic growth (GDP) while controlling for the impact of CO2 emissions (CO) in the case of GCC (Gulf Cooperation Council) countries. To conduct the empirical study we have employed the panel VAR methodology in the period 1980-2014. The results suggest that economic growth increases the energy consumption. However, the negative link between CO2 emissions and economic growth is reported, implying the great awareness of the GCC countries on the environmental problems connected with the fossil fuels based energy. Thus, there is a serious incentive in these countries to deal with the potential environmental issues. One of the good alternatives is renewable energy. In addition, the increase in the energy efficiency is considered to be an important task in the future.

This paper presents a design of the mobile robot motion framework using slightly modified Vector Field Histogram (VFH) algorithm. The VFH algorithm provides both local motion planning and obstacle avoidance based on on-board sensors measurements. This framework utilizes Robot Operating System (ROS) for the software implementation and simulation purposes. The effectiveness of the proposed framework was verified in both static and dynamic unknown environments. The obtained simulation results indicate a proficiency of the VFH algorithm in navigating the mobile robot from the start to the goal position avoiding collision with obstacles. Trajectories obtained using the designed framework are smooth and without oscillations even in the presence of moving obstacles.

This paper treats a path planning problem for the mobile robot with differential constraints using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. In this paper, the planning problem is considered as a problem of finding a feasible path between the initial and goal point in a static environment with obstacles. Modifications on basic RRT algorithm are necessary due to differential constraints of non-holonomic car-like robot. Dubin’s vehicle is selected as robot model, which represents special case of Simple car that moves only forward with constant velocity and can only make left and right turns. Algorithm is implemented in ROS (Robot Operating System) and tested through realistic simulations in 2D environment consisted of free space and obstacles. The simulation setup was conducted using a 2D Stage simulator in ROS and RViz tool for visualization. Pioneer 3AT robot model was used as Dubin’s car for simulation purposes.

Physical activity, body mass, and dietary habits are known to be important determinants of overall health status, but there is an evident lack of studies that examine these issues specifically in preschool children. The aim of this study was to identify associations that may exist between adhering to the Mediterranean diet (MD), levels of physical activity (PA), and body composition indices in apparently healthy preschool children from southern Croatia. Participants were 5- to 6-year-old preschoolers from the Mediterranean part of the country (the Split-Dalmatia County; n = 260, 126 females). Adherence to the MD was observed by the Mediterranean Diet Quality Index (KIDMED), PA level was evaluated by the Preschool-age Children’s Physical Activity Questionnaire (Pre-PAQ), and responses were collected from the parents. The participants’ waist circumferences (in cm), waist-to-hip ratios, and body mass index (in kg/m2, and in a z-score calculated relative to the normative value for age and sex) were used as indicators of body composition. All children were of the same age and tested over a one-month period of the same year as a part of the regular examination undertaken before attending elementary school. With only 6% of the children having a low KIDMED score, adherence to the MD was high. MD adherence was higher in girls (Chi-square = 15.31, p < 0.01) and children who live on the coast of the Adriatic Sea (Chi-square = 18.51, p < 0.01). A mixed effects logistic regression (with kindergarten as random factor) identified sedentary activity to be negatively associated with MD adherence (OR per point: 0.65, 95% CI: 0.44–0.91). High adherence to the MD in the studied sample may be attributed to regulated feeding in kindergarten. Considering that most Croatian elementary schools do not provide food to their students, MD adherence should be investigated later in life and also in other parts of the country where the MD is culturally less prevalent.

The desired flexibility of industrial automation systems foresees among others flexible deployment and execution of control applications on distributed control nodes. This task can be performed more efficiently by an automated deployment algorithm yielding a valid deployment and optimizing non-functional objectives.Although extensively investigated, automated deployment approaches for the automotive domain cannot be translated to industrial control applications, due to a different execution semantics. Thus, in this paper, we present a method of satisfiability modulo theories (SMT)-based automated deployment of the industrial automation systems. We formalize and implement domain-relevant constraints and objectives. Our contribution is threefold: 1) we formalize the functional coupling and end-to-end deadline constraints and objectives while considering the semantics of control applications, 2) we encode the deployment problem into an SMT form, and 3) we validate the approach on an abstract example and a domain-relevant use case.The results obtained in this paper will allow application engineers to fulfill functional and real-time requirements by automatically solving the deployment problem.

An asset administration shell (AAS), as a key concept of the Industry 4.0, provides a machine-accessible interface to any kind of asset. An application implementing the devices functionality should be able to interact with different AASs.In this work, we specify the function blocks (FBs) for accessing properties and invoking operations of AASs. We analyzed the nature and requirements of such FBs while focusing on REST/HTTP- and OPC UA-based AASs and provided IEC 61499-based implementation.The results obtained in this paper will ease interaction with the complex AAS structure from the low-level devices.

Abstract Paper deals with seasonal changes in heavy metal bioaccumulation (Fe, Mn, Cu, Zn and Pb) in Utricularia vulgaris L. and Salvinia natans (L.) All. of two localities (Necik and Sinjak – active fishpond basins) in the area of Bardača fishpond. According to our results, the better accumulator of Fe (3035 mg/kg) and Zn was S. natans (163.55 mg/kg), whereas Utricularia vulgaris better accumulates Mn (620 mg/kg) and Cu (10.18 mg/kg). Amounts of Pb in both investigated macrophyte were below the detection level (<0.51 mg/kg). The values of the bioaccumulation factor (BAC) of the tested metals were >1 or ~1 for both species, and the BAC values decreased in the following order in both investigated species: Fe > Mn > Cu > Zn. The results obtained indicated that tested macrophyte show very good characteristics as bioaccumulators and, thanks to this fact, they could be used in phytoremediation technique successfully in water-polluted ecosystem.