With Unmanned Aerial Vehicles (UAV), a swift response to urgent needs like search \& rescue missions or medical deliveries can be realized. Simultaneously, the legislator is establishing so-called geographical zones, which restrict UAV operations to mitigate the air and ground risk to third parties. These geographical zones serve a particular safety interest, but they may also hinder the efficient usage of UAVs on time-critical missions with a range-limiting battery capacity. In this study, we address a facility location problem for up to two UAV hangars with a robust optimization model considering demand hotspots, geographical zones as restricted areas, a standard mission to satisfy battery capacity constraints, and the impact of wind scenarios. To this end, water rescue missions are used exemplary, for which positive and negative location factors for UAV hangars and areas of increased drowning risk as demand points are derived from open-source georeferenced data. Optimal UAV mission trajectories are computed with an A* algorithm considering five different restriction scenarios. As this pathfinding is very time-consuming, binary occupancy grids and image processing algorithms accelerate the computation by identifying either entirely inaccessible or restriction-free connections beforehand. For the optimal UAV hangar locations, we maximize accessibility while minimizing the service time to the hotspots, resulting in a decrease from the average service time of 570.4 s for all facility candidates to 351.1 s for one and 287.2 s for two optimal UAV hangar locations.

It is important to be able to detect and differentiate between distinct porcine enteric coronaviruses that can cause similar diseases. However, the existence of naturally occurring recombinant coronaviruses such as swine enteric coronavirus (SeCoV) can give misleading results with currently used diagnostic methods. Therefore, we have developed and validated three duplex real-time quantitative RT-PCR assays for the simultaneous detection of, and differentiation between, porcine epidemic diarrhea virus (PEDV) and SeCoV. Transmissible gastroenteritis virus (TGEV) is also detected by two out of these three assays. In addition, a novel triplex assay was set up that was able to detect and differentiate between these alphacoronaviruses and the porcine deltacoronavirus (PDCoV). The validated assays have low limits of detection, close to 100% efficiency and were able to correctly identify the presence of PEDV and SeCoV in 55 field samples, while 20 samples of other pathogens did not give a positive result. Implementing one or more of these multiplex assays into the routine diagnostic surveillance for PEDV will ensure that the presence of SeCoV, TGEV and PDCoV will not go unnoticed.

As neck and/or shoulder pain (NSP) frequently occur together with tension-type headache (TTH) and migraine, we explored how concomitant NSP affects perceived treatment responses to an analgesic. An anonymous survey was performed among 895 TTH and migraine sufferers who used the analgesic 400 mg ibuprofen/100 mg caffeine. NSP was relatively abundant among patients (42.4% for TTH; 39.2% for migraine), and associated with >1 additional day with headache per month. Reported pain reduction was independent from NSP for TTH and migraine. More patients became pain-free at 2 h in migraine with NSP (42.9%) compared to migraine without NSP (32.2%), which is different from TTH with NSP (60.6%) and TTH without NSP (71.4%). For both, migraine and TTH, a recurrence of headache on the same day was more prevalent in those with concomitant NSP leading to a greater likelihood of taking a second dose of the analgesic. NSP frequently occurs together with TTH and migraine patients. In migraine, NSP seems to be associated with a better treatment response at 2 h. The more frequent recurrence of pain in those with concomitant NSP indicates that NSP makes both headache types worse. Further studies are needed to substantiate these effects.

The presence of antibiotic residues in honey has recently become a growing public health concern due to the overuse of these products in beekeeping and their transfer to the food industry. The aim of this study was to develop and validate a simple, selective and sensitive method for the simultaneous identification and quantification of residues of twenty-two sulfonamides, trimethoprim and dapsone in honey using a rapid and reliable liquid chromatography–tandem mass spectrometry (LC–MS/MS) method. The developed method showed good linearity, specificity, precision (repeatability and intra-laboratory reproducibility) and recovery. The decision limit (CCalpha) ranged between 2.16-22.12 µg/kg for CCα, while the detection capability (CCbeta) was between 2.16- 2.67-27.36 µg/kg. The method proved to be rapid, reliable and effective for the determination of sulfonamides, trimethoprim and dapsone from honey samples. The average recoveries were estimated to be between 70 and 106%. The relative standard deviations (RSDs) were between 6-18%. In practice, the method is essential to check the honey sold on the market and ensure its safety before it reaches the consumer.

African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral variants on clinical outcomes and infection-dynamics in pigs experimentally infected with ASFV, we have designed a deep sequencing strategy. Variant analysis revealed 3 distinct SNPs present in the virus inoculum (at 2.4%, 0.7%, and 13% frequency, respectively) that were maintained within all infected pigs (1-6 % frequency, and the latter at 16-21%). Several pigs displayed other unique SNPs at <10% frequency. In addition, a deletion of 10487 bp (resulting in the complete loss of 21 genes) was present at nearly 100% frequency in the ASFV DNA from one pig at position 6362-16849. This deletion was also found to be present at low levels in the virus inoculum and in two other infected pigs. The current methodology can be used for the currently circulating Eurasian ASFVs and also adapted to other ASFV strains and genotypes. Comprehensive deep sequencing is critical for following ASFV molecular evolution, especially for identification of modifications that affect virus virulence.