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Among a wide range of possible applications of nanotechnology in agriculture, there has been a particular interest in developing novel nanoagrochemicals. While some concerns have been expressed regarding altered risk profile of the new products, many foresee a great potential to support the necessary increase in global food production in a sustainable way. A critical evaluation of nanoagrochemicals against conventional analogues is essential to assess the associated benefits and risks. In this assessment, recent literature was critically analysed to determine the extent to which nanoagrochemicals differ from conventional products. Our analysis was based on 78 published papers and shows that median gain in efficacy relative to conventional products is about 20–30%. Environmental fate of agrochemicals can be altered by nanoformulations, but changes may not necessarily translate in a reduction of the environmental impact. Many studies lacked nano-specific quality assurance and adequate controls. Currently, there is no comprehensive study in the literature that evaluates efficacy and environmental impact of nanoagrochemicals under field conditions. This is a crucial knowledge gap and more work will thus be necessary for a sound evaluation of the benefits and new risks that nanoagrochemicals represent relative to existing products.

Context:A Machine Learning based System (MLS) is a software system including one or more components that learn how to perform a task from a given data set. The increasing adoption of MLSs in safety critical domains such as autonomous driving, healthcare, and finance has fostered much attention towards the quality assurance of such systems. Despite the advances in software testing, MLSs bring novel and unprecedented challenges, since their behaviour is defined jointly by the code that implements them and the data used for training them.Objective:To identify the existing solutions for functional testing of MLSs, and classify them from three different perspectives: (1) the context of the problem they address, (2) their features, and (3) their empirical evaluation. To report demographic information about the ongoing research. To identify open challenges for future research.Method:We conducted a systematic mapping study about testing techniques for MLSs driven by 33 research questions. We followed existing guidelines when defining our research protocol so as to increase the repeatability and reliability of our results.Results:We identified 70 relevant primary studies, mostly published in the last years. We identified 11 problems addressed in the literature. We investigated multiple aspects of the testing approaches, such as the used/proposed adequacy criteria, the algorithms for test input generation, and the test oracles.Conclusions:The most active research areas in MLS testing address automated scenario/input generation and test oracle creation. MLS testing is a rapidly growing and developing research area, with many open challenges, such as the generation of realistic inputs and the definition of reliable evaluation metrics and benchmarks.

The quality assurance of teaching and learning as part of universities' governance and quality management has become a major subject in higher education and higher education politics worldwide. In addition, increasing academic attention has been paid to the quality assurance of teaching and learning, as is evident from the growing number of articles in specific journals of higher education. This paper maps the development and content of research in the literature regarding the quality assurance of teaching and learning. For this mapping, a bibliometric analysis of 1610 articles from 399 different journals from 1996 to 2013 was performed using SCOPUS. The aim of this mapping is to answer the following research question: Has the quality assurance of teaching and learning become a research specialty? A co-citation analysis identifies the following four thematic clusters: an Assessment-Cluster, a Quality-Cluster, a Quality-Management-Cluster and a Student-Evaluation-of-Teaching-Cluster. Based on a categorization of the literature's core content, two distinct views on the quality assurance of teaching and learning become evident, representing an antagonistic tension in the research between an education strand and a management strand of research. Several indications from the empirical evidence in this paper suggest that the quality assurance of teaching and learning is (becoming) a specialty. The identification and awareness of a specialty as a cognitive organizing characteristic combining two and more categories of research topics are of great importance for the creation of knowledge in the complex interdisciplinary research field of higher education. (HRK / Abstract übernommen).

In Europe, lung cancer ranks third among the most common cancers, remaining the biggest killer. Since the publication of the first European Society of Radiology and European Respiratory Society joint white paper on lung cancer screening (LCS) in 2015, many new findings have been published and discussions have increased considerably. Thus, this updated expert opinion represents a narrative, non-systematic review of the evidence from LCS trials and description of the current practice of LCS as well as aspects that have not received adequate attention until now. Reaching out to the potential participants (persons at high risk), optimal communication and shared decision-making will be key starting points. Furthermore, standards for infrastructure, pathways and quality assurance are pivotal, including promoting tobacco cessation, benefits and harms, overdiagnosis, quality, minimum radiation exposure, definition of management of positive screen results and incidental findings linked to respective actions as well as cost-effectiveness. This requires a multidisciplinary team with experts from pulmonology and radiology as well as thoracic oncologists, thoracic surgeons, pathologists, family doctors, patient representatives and others. The ESR and ERS agree that Europe’s health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of lung cancer and reduce the mortality rate. Now is the time to set up and conduct demonstration programmes focusing, among other points, on methodology, standardisation, tobacco cessation, education on healthy lifestyle, cost-effectiveness and a central registry.Key Points• Pulmonologists and radiologists both have key roles in the set up of multidisciplinary LCS teams with experts from many other fields.• Pulmonologists identify people eligible for LCS, reach out to family doctors, share the decision-making process and promote tobacco cessation.• Radiologists ensure appropriate image quality, minimum dose and a standardised reading/reporting algorithm, together with a clear definition of a “positive screen”.• Strict algorithms define the exact management of screen-detected nodules and incidental findings.• For LCS to be (cost-)effective, it has to target a population defined by risk prediction models.

Purpose The purpose of this review article is to investigate the usefulness of different types of life cycle assessment (LCA) studies of electrified vehicles to provide robust and relevant stakeholder information. It presents synthesized conclusions based on 79 papers. Another objective is to search for explanations to divergence and “complexity” of results found by other overviewing papers in the research field, and to compile methodological learnings. The hypothesis was that such divergence could be explained by differences in goal and scope definitions of the reviewed LCA studies. Methods The review has set special attention to the goal and scope formulation of all included studies. First, completeness and clarity have been assessed in view of the ISO standard’s (ISO 2006a , b ) recommendation for goal definition. Secondly, studies have been categorized based on technical and methodological scope, and searched for coherent conclusions. Results and discussion Comprehensive goal formulation according to the ISO standard (ISO 2006a , b ) is absent in most reviewed studies. Few give any account of the time scope, indicating the temporal validity of results and conclusions. Furthermore, most studies focus on today’s electric vehicle technology, which is under strong development. Consequently, there is a lack of future time perspective, e.g., to advances in material processing, manufacturing of parts, and changes in electricity production. Nevertheless, robust assessment conclusions may still be identified. Most obvious is that electricity production is the main cause of environmental impact for externally chargeable vehicles. If, and only if, the charging electricity has very low emissions of fossil carbon, electric vehicles can reach their full potential in mitigating global warming. Consequently, it is surprising that almost no studies make this stipulation a main conclusion and try to convey it as a clear message to relevant stakeholders. Also, obtaining resources can be observed as a key area for future research. In mining, leakage of toxic substances from mine tailings has been highlighted. Efficient recycling, which is often assumed in LCA studies of electrified vehicles, may reduce demand for virgin resources and production energy. However, its realization remains a future challenge. Conclusions LCA studies with clearly stated purposes and time scope are key to stakeholder lessons and guidance. It is also necessary for quality assurance. LCA practitioners studying hybrid and electric vehicles are strongly recommended to provide comprehensive and clear goal and scope formulation in line with the ISO standard (ISO 2006a , b ).

This paper presents the use of a projector-based spatial augmented reality system in an industrial quality assurance setting to highlight spot-weld locations on vehicle panels for manual welding operators. The aim of this work is to improve the precision and accuracy of manual spot-weld placements with the aid of visual cues as a proactive step by the automotive manufacturer to enhance product quality. The prototype system was deployed at General Motors (GM) Holden plant in Elizabeth, Australia on the production line building Holden Cruze vehicles. Production trials were conducted and techniques developed to analyse and validate the precision and accuracy of spot-welds both with and without the visual cues. A reduction of 52 % of the standard deviation of manual spot-weld placement was observed when using augmented reality visual cues. The average standard deviation with-AR assistance (19 panels and 114 spot-welds) was calculated at 1.94 mm compared to without-AR (45 panels and 270 spot-welds) at 4.08 mm. All welds were within the required specification and panels evaluated in this study were used as the final product made available to consumers. The visual cues enabled operators to spot-weld at a higher degree of precision and accuracy.

As a key node of engineering quality assurance, the engineering testing industry is obviously lagging behind other industries in its data application aspect, and there are various problems in policy, technology, and resources. Such problems have obviously affected the development trend of the entire industry, and it is urgent to solve the data problems in the engineering testing industry. By combing and analysing the status quo of data application in the industry, the article found three common problems of data application, no data available, inability to apply and no system management. These common problems directly affect the data application level of the entire industry. Based on the identified problems, this article further analyze the causes of the problems and point out the general direction of the industry data governance strategies.

With the rapid development of china wind power, a large number of wind turbines will reach the warranty period in the next few years. As an important part of the acceptance evaluation work, power performance assessment is receiving more and more attention. In order to objectively and efficiently evaluate the power curve performance of wind farm units during the warranty period, this paper uses SCADA data to perform power curve evaluation, develops the evaluation method, and uses wind speed to correct the results. Finally, combined with the actual case of wind farm, the feasibility of this estimation method is verified. The method proposed in this paper provides a basis for conducting wind power quality assurance acceptance.

Quality control procedures are essential in many industrial production pipelines. These repetitive and precise tasks are frequently complex, including several steps that must be performed correctly by different operators. To facilitate these, quality control tests are often documented with static media like video recordings, photos, or diagrams. However, the need for the operator to divide attention between the visual instructions and the task, and the lack of feedback lead to slow processes, with potential for improvement. By using augmented reality (AR), operators can focus on the task at hand while receiving visual feedback where it is needed. Nevertheless, existing prototypes are still at early stages, being tested only in laboratory conditions, far from mimicking real scenarios. The major contributions of this work are twofold: first, we present an AR-based quality control system capable of generating virtual content to guide operators by overlaying information in a video stream while performing real-time validation. The system evaluates the current status of the procedure to ensure the automatic progression to the next phase. Second, an evaluation was conducted in an industrial shop floor during 1 week, with seven operators to verify if the system was robust and understand possible efficiency gains when compared to the alternative, i.e., video instructions. Results showed that AR had a significant impact in procedures’ execution time (reduction of 36%), while reducing the risk of human errors, which means AR technologies may represent a profitable and sustainable solution when applied to real-world industrial scenarios, in the long run.