Explore the vast range of titles available.

To adapt vehicle control and plan strategies in a predictive manner, it is usually desired to know the context of a driving environment. This paper aims at efficiently inferring the following five driving environments around vehicle’s vicinity: shopping zone, tourist zone, public station, motor service area, and security zone, whose existences are not necessarily mutually exclusive. To achieve that, we utilize the Point of Interest (POI) data from a navigation map as the semantic clue, and solve the inference task as a multilabel classification problem. Specifically, we first extract all relevant POI objects from a map, then transform these discrete POI objects into numerical POI features. Based on these POI features, we finally predict the occurrence of each driving environment via an inference engine. To calculate representative POI features, a statistical approach is introduced. To composite an inference engine, three inference systems are investigated: fuzzy inference system (FIS), support vector machine (SVM), and multilayer perceptron (MLP). In total, we implement 11 variants of inference engine following two inference strategies: independent and unified inference strategies, and conduct comprehensive evaluation on a manually collected dataset. The result shows that the proposed inference framework generalizes well on different inference systems, where the best overall F1 score 0.8699 is achieved by the MLP-based inference engine following the unified inference strategy, along with the fastest inference time of 0.0002 millisecond per sample. Hence, the generalization ability and efficiency of the proposed inference framework are proved.

Monitoring vegetation health and its response to climate conditions is critical for assessing the impact of climate change on urban environments. While many studies simulate and map the health of vegetation, there seems to be a lack of high-resolution, low-scale data and easy-to-use tools for managers in the municipal administration that they can make use of for decision-making. Data related to climate and vegetation indicators, such as those provided by the C3S Copernicus Data Store (CDS), are mostly available with a coarse resolution but readily available as freely available and open data. This study aims to develop a systematic approach and workflow to provide a simple tool for monitoring vegetation changes and health. We built a toolbox to streamline the geoprocessing workflow. The data derived from CDS included bioclimate indicators such as the annual moisture index and the minimum temperature of the coldest month (BIO06). The biophysical parameters used are leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR). We used a linear regression model to derive equations for downscaled biophysical parameters, applying vegetation indices derived from Sentinel-2, to identify the vegetation health status. We also downscaled the bioclimatic indicators using the digital elevation model (DEM) and Landsat surface temperature derived from Landsat 8 through Bayesian kriging regression. The downscaled indicators serve as a critical input for forest-based classification regression to model climate envelopes to address suitable climate conditions for vegetation growth. The results derived contribute to the overall development of a workflow and tool for and within the CoKLIMAx project to gain and deliver new insights that capture vegetation health by explicitly using data from the CDS with a focus on the City of Constance at Lake Constance in southern Germany. The results shall help gain new insights and improve urban resilient, climate-adaptive planning by providing an intuitive tool for monitoring vegetation health and its response to climate conditions.

Vaccines and other alternative products can help minimize the need for antibiotics by preventing and controlling infectious diseases in animal populations, and are central to the future success of animal agriculture. To assess scientific advancements related to alternatives to antibiotics and provide actionable strategies to support their development, the United States Department of Agriculture, with support from the World Organisation for Animal Health, organized the second International Symposium on Alternatives to Antibiotics. It focused on six key areas: vaccines; microbial-derived products; non-nutritive phytochemicals; immune-related products; chemicals, enzymes, and innovative drugs; and regulatory pathways to enable the development and licensure of alternatives to antibiotics. This article, part of a two-part series, synthesizes and expands on the expert panel discussions regarding opportunities, challenges and needs for the development of vaccines that may reduce the need for use of antibiotics in animals; new approaches and potential solutions will be discussed in part 2 of this series. Vaccines are widely used to prevent infections in food animals. Various studies have demonstrated that their animal agricultural use can lead to significant reductions in antibiotic consumption, making them promising alternatives to antibiotics. To be widely used in food producing animals, vaccines have to be safe, effective, easy to use, and cost-effective. Many current vaccines fall short in one or more of these respects. Scientific advancements may allow many of these limitations to be overcome, but progress is funding-dependent. Research will have to be prioritized to ensure scarce public resources are dedicated to areas of potentially greatest impact first, and private investments into vaccine development constantly compete with other investment opportunities. Although vaccines have the potential to improve animal health, safeguard agricultural productivity, and reduce antibiotic consumption and resulting resistance risks, targeted research and development investments and concerted efforts by all affected are needed to realize that potential.

Controlling and dosing electrolytes is a key challenge in the operation of electroplating process chains. Electrolyte components are continuously degraded and dragged out during the production process. This process is influenced by a variety of internal and external factors such as process parameters, the electrolyte itself, anodes, the substrates and the production environment. The exact analytical measurement of the electrolyte composition requires extensive analytical equipment and typically cannot be completely realized within an industrial plating company. Therefore, this paper presents a model-based approach, integrated in a cyber-physical production system, for controlling and dosing electrolytes. A mathematical resource flow model is the basis for a dynamic agent-based simulation. This model uses available data from the manufacturing execution system and enterprise resource planning system to model the current composition of the electrolyte. The approach is successfully validated for two different electrolyte substances at an industrial acid zinc–nickel barrel plating process chain for automotive parts.

Vaccines and other alternative products are central to the future success of animal agriculture because they can help minimize the need for antibiotics by preventing and controlling infectious diseases in animal populations. To assess scientific advancements related to alternatives to antibiotics and provide actionable strategies to support their development, the United States Department of Agriculture, with support from the World Organisation for Animal Health, organized the second International Symposium on Alternatives to Antibiotics. It focused on six key areas: vaccines; microbial-derived products; non-nutritive phytochemicals; immune-related products; chemicals, enzymes, and innovative drugs; and regulatory pathways to enable the development and licensure of alternatives to antibiotics. This article, the second part in a two-part series, highlights new approaches and potential solutions for the development of vaccines as alternatives to antibiotics in food producing animals; opportunities, challenges and needs for the development of such vaccines are discussed in the first part of this series. As discussed in part 1 of this manuscript, many current vaccines fall short of ideal vaccines in one or more respects. Promising breakthroughs to overcome these limitations include new biotechnology techniques, new oral vaccine approaches, novel adjuvants, new delivery strategies based on bacterial spores, and live recombinant vectors; they also include new vaccination strategies in-ovo, and strategies that simultaneously protect against multiple pathogens. However, translating this research into commercial vaccines that effectively reduce the need for antibiotics will require close collaboration among stakeholders, for instance through public–private partnerships. Targeted research and development investments and concerted efforts by all affected are needed to realize the potential of vaccines to improve animal health, safeguard agricultural productivity, and reduce antibiotic consumption and resulting resistance risks.

Specific climate adaptation and resilience measures can be efficiently designed and implemented at regional and local levels. Climate and environmental databases are critical for achieving the sustainable development goals (SDGs) and for efficiently planning and implementing appropriate adaptation measures. Available federated and distributed databases can serve as necessary starting points for municipalities to identify needs, prioritize resources, and allocate investments, taking into account often tight budget constraints. High-quality geospatial, climate, and environmental data are now broadly available and remote sensing data, e.g., Copernicus services, will be critical. There are forward-looking approaches to use these datasets to derive forecasts for optimizing urban planning processes for local governments. On the municipal level, however, the existing data have only been used to a limited extent. There are no adequate tools for urban planning with which remote sensing data can be merged and meaningfully combined with local data and further processed and applied in municipal planning and decision-making. Therefore, our project CoKLIMAx aims at the development of new digital products, advanced urban services, and procedures, such as the development of practical technical tools that capture different remote sensing and in-situ data sets for validation and further processing. CoKLIMAx will be used to develop a scalable toolbox for urban planning to increase climate resilience. Focus areas of the project will be water (e.g., soil sealing, stormwater drainage, retention, and flood protection), urban (micro)climate (e.g., heat islands and air flows), and vegetation (e.g., greening strategy, vegetation monitoring/vitality). To this end, new digital process structures will be embedded in local government to enable better policy decisions for the future.

The effects of zinc and sodium hydroxide concentrations in an alkaline non-cyanide zinc bath on the electrodeposition characteristics of zinc deposits are systematically investigated. Using microstructural and phase analyses of specimens with specifically designed geometries, the study indicates that the bath formulations critically control the electrogalvanizing characteristics and affect the coating surface morphology, deposition rate, throwing power, coating uniformity, and residual stresses developed during and after electrogalvanizing. The coatings produced from baths with a moderate Zn-to-NaOH ratio of 0.067–0.092 appear to provide uniform and compact deposits, moderately high deposition rate, and relatively low residual stresses.

Background Enterococcus cecorum (EC) infection currently is one of the most important bacterial diseases of modern broiler chickens but can also affect ducks or other avian species. However, little is known concerning pathogenesis of EC and most studies concentrate on examinations of EC strains from broilers only. The objective of this study was to compare pathogenic and commensal EC strains from different animal species concerning different phenotypic and genotypic traits. Results Pathogenic and commensal EC strains were not clearly separated from each other in a phylogenetic tree based on partial sequences of the 16S-rRNA-gene and also based on the fatty acid profile determined with gas chromatography. C 12:0 , C 14:0 , C 15:0 , C 16:0 , C 17:0 , C 18:0 , C 18:1 w7c, C 18:1 w9c and C 20:4 w6,9,12,15c were detected as the major fatty acids. None of the 21 pathogenic EC strains was able to utilize mannitol, while 9 of 29 commensal strains were mannitol positive. In a dendrogram based on MALDI-TOF MS data, pathogenic strains were not clearly separated from commensal isolates. However, significant differences concerning the prevalence of several mass peaks were confirmed between the two groups. Two different antisera were produced but none of the serotypes was predominantly found in the pathogenic or commensal EC isolates. Enterococcal virulence factors gelE , esp , asa1 , ccf , hyl and efaAfs were only detected in single isolates via PCR. No virulence factor was found significantly more often in the pathogenic isolates. The chicken embryo lethality of the examined EC isolates varied from 0 up to 100%. The mean embryo lethality in the pathogenic EC isolates was 39.7%, which was significantly higher than the lethality of the commensal strains, which was 18.9%. Additionally, five of the commensal isolates showed small colony variant growth, which was never reported for EC before. Conclusions Pathogenic and commensal EC isolates from different animal species varied in chicken embryo lethality, in their ability to metabolize mannitol and probably showed divergent mass peak patterns with MALDI-TOF MS. These differences may be explained by a separate evolution of pathogenic EC isolates. Furthermore, different serotypes of EC were demonstrated for the first time.

Map-matching is widely used in automotive navigation systems to locate vehicle positions on a given digital road map. Various map-matching algorithms have been developed focusing on different application needs. Within the Ghosthunter project, a weighting-function-based map-matching algorithm has been developed for detecting wrong-way driving in order to improve road safety, particularly in Autobahn entrance and exit areas. This paper aims at exploring the potential use of lane-level attributes and height data in improving the success rate of the previously presented algorithm. This algorithm performs well in entrance and exit areas to the Autobahn, with a high success rate of 99.5% in identifying the road on which the vehicle is actually travelling. In the enhanced algorithm presented in this paper the weight coefficients used for computing the total weighting score of candidate roads are adjusted with the aid of one or both kinds of these precise data. The results confirmed that the usage of these precise data can effectively help to detect and correct mismatches at junctions and overpasses.

Trueperella (T.) bernardiae is a well-known bacterial pathogen in infections of humans, rarely in animals. In the present study, five T. bernardiae isolates, isolated from five Peking ducks of four different farms, were identified by phenotypic properties, by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, and genotypically by sequencing the 16S ribosomal RNA (rRNA) gene, the superoxide dismutase A encoding gene sodA, and the glyceraldehyde-3-phosphate dehydrogenase encoding gene gap. In addition, the T. bernardiae isolates could be identified with a newly developed loop-mediated isothermal amplification (LAMP) assay based on the gyrase encoding housekeeping gene gyrA. All these tests clearly identified the T. bernardiae isolates to the species level. However, the detection of the specific gene gyrA with the newly designed LAMP assay appeared with a high sensitivity and specificity, and could help to identify this bacterial species in human and animal infections in future. The importance of the T. bernardiae isolates for the clinical condition of the ducks and for the problems at farm level remains unclear.