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Physical restraint is an emergency procedure restricting the movement of an individual and is used in events where students pose an imminent threat of physical harm to themselves or others. Students with disabilities are subjected to these procedures seven times more than typically developing students. Over the past decade, there has been substantial policy reform on the use of restraint; however, policies still vary across the country. Additionally, research on experiences of the use of and policy on restraint in school settings is incredibly limited. The current study expands the body of literature by investigating teachers' experiences, and factors associated with experiences, of restraint events and district policy utilizing a multiple-methods survey design. One hundred eighty Prekindergarten through 12th-grade teachers working in a variety of school settings across the country completed a self-report online survey. Results revealed variability in experiences of restraint events and school district policies. While most participants reported following the district policy as written, level of education significantly impacted teachers' adhering to the policy, wherein those with higher levels of education were less likely to follow the policy. Implications for policy and practice are provided.

Families of children with developmental disabilities in rural and underserved areas may lack access to direct service providers. Global pandemics such as COVID-19 have further affected access to service providers for most children, often shifting services online and increasing the role of technology and involvement of parents and caregivers in intervention. Thus, there is a need to examine the characteristics and effects of caregiver implemented technology-based interventions for children with developmental disabilities. The present synthesis evaluates the research on caregiver implemented technology-based interventions for children with autism spectrum disorder and other developmental disabilities aged 21 or younger. A systematic search of four electronic databases resulted in 14 single-case design studies which encompassed 58 participants with a developmental disability, along with 62 caregivers. Studies used a variety of technologies and involved strategies such as computer assisted instruction, self-management, and variations of video modeling. Interventions targeted a variety of outcomes and most incorporated behavioral strategies such as prompting or positive reinforcement. Results indicate positive outcomes without overly time intensive parent training; however, it is important to consider these findings within context of methodological strength, as only four included studies utilized strong experimental methods according to the evaluative framework provided by Reichow et al. (2008). Implications for practice and recommendations for future research are provided.

Objectives Early treatment of individuals at risk of developing rheumatoid arthritis (RA-risk) in the preclinical phase has the potential to positively impact both patients and society by preventing disease onset and improving patients’ quality of life. The PRAIRI study was a randomised, double-blind, placebo-controlled trial with the B-cell depleting agent rituximab (RTX), which resulted in a significant delay of arthritis development of up to 12 months in seropositive RA-risk individuals. Here, we report our findings on patient-reported outcomes (PROs) in this study population.Methods Seventy-eight RA-risk individuals were treated with one single dose of either placebo (PBO) or 1000 mg RTX plus 100 mg methylprednisolone (MP) and anti-histamines, regardless of treatment allocation, as co-medication. Data on quality of life were collected at baseline and 1, 4, 6, 12 and 24 months using established PRO questionnaires (visual analogue scale (VAS) pain, health assessment questionnaire disability index (HAQ-DI) score, EuroQol five dimension (EQ-5D) and both physical and mental component score of the 36-item short-form heath survey (SF-36)).Results No significant changes in quality of life over a 2 year follow-up were observed in at-risk individuals treated with RTX compared to PBO given the PRO scores at 24 months (mean difference±SEM: HAQ score=0.07±0.16; EQ-5D=−0.02±0.05; VAS pain=11.11±7.40). Furthermore, no significant effect of treatment on perceived arthritis severity at the time of clinically manifest disease (arthritis) was found.Conclusion One single dose of RTX plus MP administered to RA-risk individuals does not have a meaningful and measurable positive effect on PROs after 2 years of follow-up and/or perceived disease severity at the time of arthritis development.Trial registration number Trial registered at EU Clinical Trial Register, EudraCT Number: 2009-010955-29 (https://www.clinicaltrialsregister.eu/ctr-search/search?query=Prevention+of+RA+by+B+cell+directed+therapy).

Market-based control is a control approach that can be used to organize resource control problems by establishing an artificial market economy for the allocation of these resources. In such system, the set of market-clearing prices is the set of prices that result in an equilibrium between demanded and supplied resources throughout the system. In this paper, a new method has been proposed for solving the market-clearing problem, the problem of determining the market-clearing prices. The algorithm is applied on a complex representative power system and three simplified power systems based on the representative system under different operational scenarios. The proposed method is compared with existing reference root-finding algorithms. The comparison illustrates the proposed algorithm’s ability to address the numerical challenges the market-clearing problem poses. Dynamic simulation has been used to demonstrate the efficacy of the proposed algorithm in clearing the market in a wide range of dynamic conditions.

Image velocimetry has become an effective method of mapping flow conditions in rivers, but this analysis is typically performed in a post-processing mode after data collection is complete. In this study, we evaluated the potential to infer flow velocities in approximately real time as thermal images are being acquired from an uncrewed aircraft system (UAS). The sensitivity of thermal image velocimetry to environmental conditions was quantified by conducting 20 flights over four days and assessing the accuracy of image-derived velocity estimates via comparison to direct field measurements made with an acoustic Doppler current profiler (ADCP). This analysis indicated that velocity mapping was most reliable when the air was cooler than the water. We also introduced a workflow for River Velocity Measurement in Approximately Real Time (RiVMART) that involved transferring brief image sequences from the UAS to a ground station as distinct data packets. The resulting velocity fields were as accurate as those generated via post-processing. A new particle image velocimetry (PIV) algorithm based on staggered image sequences increased the number of image pairs available for a given image sequence duration and slightly improved accuracy relative to a standard PIV implementation. Direct, automated geo-referencing of image-derived velocity vectors based on information on the position and orientation of the UAS acquired during flight led to poor alignment with vectors that were geo-referenced manually by selecting ground control points from an orthophoto. This initial proof-of-concept investigation suggests that our workflow could enable highly efficient characterization of flow fields in rivers and might help support applications that require rapid response to changing conditions.

Driven by developments in the automotive industry, the availability of compact consumer-grade LiDAR (Light Detection and Ranging) sensors has increased significantly in recent years. Some of these sensors are also suitable for UAV-based surveying tasks. This paper first discusses the differences between consumer-grade and survey-grade LiDAR systems. Special attention will be paid to the scanning mechanisms used on the one hand and to different solutions for the transceiver units on the other hand. Based on the technical data of two concrete systems, the consumer-grade DJI Zenmuse L1 sensor and the survey-grade scanner RIEGL VUX-1UAV, the expected effects of the sensor parameters on the 3D point cloud are first discussed theoretically and then verified using an exemplary data set in Hessigheim (Baden-Württemberg, Germany). The analysis shows the possibilities and limitations of consumer-grade LiDAR. Compared to the low-cost sensor, the high-end scanner exhibits lower range measurement noise (5–10 mm) and better 3D point location accuracy. Furthermore, the higher laser beam quality of high-end devices (beam divergence, beam shape) enables more detailed object detection at the same point density. With moderate accuracy requirements of 5–10 cm, however, applications in the geodetic-cartographic context also arise for the considerably less expensive consumer-grade LiDAR systems.

Abstract Background Many studies have compared real-world clinical outcomes of immunotherapy in patients with metastatic non-small cell lung cancer (NSCLC) with reported outcomes data from pivotal trials. However, any differences observed could be only limitedly explored further for causation because of the unavailability of individual patient data (IPD) from trial participants. The present study aims to explore the additional benefit of comparison with IPD. Methods This study compares progression free survival (PFS) and overall survival (OS) of metastatic NSCLC patients treated with second line nivolumab in real-world clinical practice (n = 141) with IPD from participants in the Checkmate-057 clinical trial (n = 292). Univariate and multivariate Cox proportional hazards models were used to construct HRs for real-world practice versus clinical trial. Results Real-world patients were older (64 vs. 61 years), had more often ECOG PS ≥ 2 (5 vs. 0%) and were less often treated with subsequent anti-cancer treatment (28.4 vs. 42.5%) compared to trial patients. The median PFS in real-world patients was longer (3.84 (95%CI: 3.19-5.49) vs 2.30 (2.20-3.50) months) and the OS shorter than in trial participants (8.25 (6.93-13.2) vs. 12.2 (9.90-15.1) months). Adjustment with available patient characteristics, led to a shift in the hazard ratio (HR) for OS, but not for PFS (HRs from 1.13 (0.88-1.44) to 1.07 (0.83-1.38), and from 0.82 (0.66-1.03) to 0.79 (0.63-1.00), respectively). Conclusions This study is an example how IPD from both real-world and trial patients can be applied to search for factors that could explain an efficacy-effectiveness gap. Making IPD from clinical trials available to the international research community allows this.

Background: Image guidance to assist left ventricular (LV) lead placement may improve outcome after cardiac resynchronization therapy (CRT), but previous approaches and results varied greatly, and multicenter feasibility is lacking altogether. Objective: We sought to investigate the multicenter feasibility of image guidance for periprocedural assistance of LV lead placement for CRT. Methods: In 30 patients from 3 hospitals, cardiac magnetic resonance imaging was performed within 3 months prior to CRT to identify myocardial scar and late mechanical activation (LMA). LMA was determined using radial strain, plotted over time. Segments without scar but clear LMA were classified as optimal for LV lead placement, according to an accurate 36-segment model of the whole heart. LV leads were navigated using image overlay with periprocedural fluoroscopy. After 6 months, volumetric response and super-response were defined as ≥15% or ≥30% reduction in LV end-systolic volume, respectively. Results: Periprocedural image guidance was successfully performed in all CRT patients (age 66 ± 10 years; 59% men, 62% with nonischemic cardiomyopathy, 69% with left bundle branch block). LV leads were placed as follows: within (14%), adjacent (62%), or remote (24%) from the predefined target. According to the conventional 18-segment model, a remote position occurred only once (3%). On average, 86% of patients demonstrated a volumetric response (mean LV end-systolic volume reduction 36 ± 29%), and 66% of all patients were super-responders. Conclusion: On-screen image guidance for LV lead placement in CRT was feasible in a multicenter setting. Efficacy will be further investigated in the randomized controlled ADVISE (Advanced Image Supported Lead Placement in Cardiac Resynchronization Therapy) trial (NCT05053568).

Abstract Empirical data on the health impacts of the COVID-19 pandemic remain scarce, especially among patients with chronic pain. We conducted a cross-sectional study matched by season to examine patient-reported health symptoms among patients with chronic pain pre- and post-COVID-19 pandemic onset. Survey responses were analyzed from 7535 patients during their initial visit at a tertiary pain clinic between April 2017–October 2020. Surveys included measures of pain and pain-related physical, emotional, and social function. The post-COVID-19 onset cohort included 1798 initial evaluations, and the control pre-COVID-19 cohort included 5737 initial evaluations. Patients were majority female, White/Caucasian, and middle-aged. The results indicated that pain ratings remained unchanged among patients after the pandemic onset. However, pain catastrophizing scores were elevated when COVID-19 cases peaked in July 2020. Pain interference, physical function, sleep impairment, and emotional support were improved in the post-COVID-19 cohort. Depression, anxiety, anger, and social isolation remained unchanged. Our findings provide evidence of encouraging resilience among patients seeking treatment for pain conditions in the face of the COVID-19 pandemic. However, our findings that pain catastrophizing increased when COVID-19 cases peaked in July 2020 suggests that future monitoring and consideration of the impacts of the pandemic on patients’ pain is warranted.

People derive considerable social benefits from interacting with others that they encounter across a host of environmental domains: their city, region, country, continent, and even the world at large. We explore the extent to which perceived happiness hinges on one's sense of connection within each domain, drawing upon a large international sample of 120k respondents from 74 nations in the World Value Survey (2017–2020). This large battery of social and political attitudes includes items that ask: “tell me how close you feel to…” followed by each of city, region, country, continent, and the world. Options ranged from ‘very close’ to ‘not very close at all.’ Perceived happiness was scored on a 4-option item asking: “taking all things together, would you say you are…” with options ranging from ‘very happy’ to ‘not at all happy.’ After accounting for various demographic variables like age, sex, education, urban/rural environment, and income, results from a stepwise ordinal logistic regression analysis showed that one's perceived happiness was predicted by feeling connected to almost all domains; and the more connected one felt, the happier they were. One's connection however to region was not significant, wherein we suspect the item was too ambiguous for a clear response. Implications for overall wellbeing are discussed, as are directions for future research.

Abstract Several observational studies suggested that gut microbiome-affecting-medication impairs the effectiveness of immunotherapy in patients with metastatic non-small-cell lung cancer (NSCLC). We postulated that if the effectiveness of immunotherapy is affected by drug-related changes of the microbiome, a stronger association between the use of co-medication and overall survival (OS) will be observed in patients treated with immunotherapy as compared to patients treated with chemotherapy. In a retrospective matched cohort study, immunotherapy patients were matched (1:1) to patients treated with chemotherapy in the pre immunotherapy era. The association between the use of antibiotics, opioids, proton pump inhibitors, metformin and other antidiabetics on OS was assessed with multivariable cox-regression analyses. Interaction tests were applied to investigate whether the association differs between patients treated with immuno- or chemotherapy. A total of 442 patients were studied. The use of antibiotics was associated with worse OS (adjusted Hazard Ratio (aHR) 1.39, p = 0.02) independent of the type of therapy (chemotherapy or immunotherapy). The use of opioids was also associated with worse OS (aHR 1.33, p = 0.01). The other drugs studied showed no association with OS. Interaction term testing showed no effect modification by immuno- or chemotherapy for the association of antibiotics and opioids with OS. The use of antibiotics and opioids is similarly associated with worse outcomes in both chemotherapy and immunotherapy treated NSCLC patients. This suggests that the association is likely to be a consequence of confounding rather than disturbing the composition of the microbiome.

Although monoclonal antibodies (mAbs) have been shown to be extremely effective in treating a number of diseases, they often suffer from poor developability attributes, such as high viscosity and low solubility at elevated concentrations. Since experimental candidate screening is often materials and labor intensive, there is substantial interest in developing in silico tools for expediting mAb design. Here, we present a strategy using machine learning-based QSAR models for the a priori estimation of mAb solubility. The extrapolated protein solubilities of a set of 111 antibodies in a histidine buffer were determined using a high throughput PEG precipitation assay. 3D homology models of the antibodies were determined, and a large set of in house and commercially available molecular descriptors were then calculated. The resulting experimental and descriptor data were then used for the development of QSAR models of mAb solubilities. After feature selection and training with different machine learning algorithms, the models were evaluated with external test sets. The resulting regression models were able to estimate the solubility values of external test set data with R2 of 0.81 and 0.85 for the two regression models developed. In addition, three class and binary classification models were developed and shown to be good estimators of mAb solubility behavior, with overall test set accuracies of 0.70 and 0.95, respectively. The analysis of the selected molecular descriptors in these models was also found to be informative and suggested that several charge-based descriptors and isotype may play important roles in mAb solubility. The combination of high throughput relative solubility experimental techniques in concert with efficient machine learning QSAR models offers an opportunity to rapidly screen potential mAb candidates and to design therapeutics with improved solubility characteristics.

Abstract This study aims to assess how clinical outcomes of immunotherapy in real-world (effectiveness) correspond to outcomes in clinical trials (efficacy) and to look into factors that might explain an efficacy-effectiveness (EE) gap. All patients diagnosed with stage IV non-small cell lung cancer (NSCLC) in 2015–2018 in six Dutch large teaching hospitals (Santeon network) were identified and followed-up from date of diagnosis until death or end of data collection. Progression-free survival (PFS) and overall survival (OS) from first-line (1L) pembrolizumab and second-line (2L) nivolumab were compared with clinical trial data by calculating hazard ratios (HRs). From 1950 diagnosed patients, 1005 (52%) started with any 1L treatment, of which 83 received pembrolizumab. Nivolumab was started as 2L treatment in 141 patients. For both settings, PFS times were comparable between real-world and trials (HR 1.08 (95% CI 0.75–1.55), and HR 0.91 (95% CI 0.74–1.14), respectively). OS was significantly shorter in real-world for 1L pembrolizumab (HR 1.55; 95% CI 1.07–2.25). Receiving subsequent lines of treatment was less frequent in real-world compared to trials. There is no EE gap for PFS from immunotherapy in patients with stage IV NSCLC. However, there is a gap in OS for 1L pembrolizumab. Fewer patients proceeding to a subsequent line of treatment in real-world could partly explain this.

This paper presents a study on the potential of ultra-high accurate UAV-based 3D data capture by combining both imagery and LiDAR data. Our work is motivated by a project aiming at the monitoring of subsidence in an area of mixed use. Thus, it covers built-up regions in a village with a ship lock as the main object of interest as well as regions of agricultural use. In order to monitor potential subsidence in the order of 10 mm/year, we aim at sub-centimeter accuracies of the respective 3D point clouds. We show that hybrid georeferencing helps to increase the accuracy of the adjusted LiDAR point cloud by integrating results from photogrammetric block adjustment to improve the time-dependent trajectory corrections. As our main contribution, we demonstrate that joint orientation of laser scans and images in a hybrid adjustment framework significantly improves the relative and absolute height accuracies. By these means, accuracies corresponding to the GSD of the integrated imagery can be achieved. Image data can also help to enhance the LiDAR point clouds. As an example, integrating results from Multi-View Stereo potentially increases the point density from airborne LiDAR. Furthermore, image texture can support 3D point cloud classification. This semantic segmentation discussed in the final part of the paper is a prerequisite for further enhancement and analysis of the captured point cloud.

Benchmarks for protective immunity from infection or severe disease after SARS-CoV-2 vaccination are still being defined. Here, we characterized virus neutralizing and ELISA antibody levels, cellular immune responses, and viral variants in 4 separate groups: healthy controls (HCs) weeks (early) or months (late) following vaccination in comparison with symptomatic patients with SARS-CoV-2 after partial or full mRNA vaccination. During the period of the study, most symptomatic breakthrough infections were caused by the SARS-CoV-2 Alpha variant. Neutralizing antibody levels in the HCs were sustained over time against the vaccine parent virus but decreased against the Alpha variant, whereas IgG titers and T cell responses against the parent virus and Alpha variant declined over time. Both partially and fully vaccinated patients with symptomatic infections had lower virus neutralizing antibody levels against the parent virus than the HCs, similar IgG antibody titers, and similar virus-specific T cell responses measured by IFN-γ. Compared with HCs, neutralization activity against the Alpha variant was lower in the partially vaccinated infected patients and tended to be lower in the fully vaccinated infected patients. In this cohort of breakthrough infections, parent virus neutralization was the superior predictor of breakthrough infections with the Alpha variant of SARS-CoV-2.

We investigated the cumulative effects of predation by piscivorous colonial waterbirds on the survival of multiple salmonid (Oncorhynchus spp.) populations listed under the U.S. Endangered Species Act (ESA) and determined what proportion of all sources of fish mortality (1 -survival) were due to birds in the Columbia River basin, USA. Anadromous juvenile salmonids (smolts) were exposed to predation by Caspian terns (Hydroprogne caspia), double-crested cormorants (Nannopterum auritum), California gulls (Larus californicus), and ring-billed gulls (L. delawarensis), birds known to consume both live and dead fish. Avian consumption and survival probabilities (proportion of available fish consumed or alive) were estimated for steelhead trout (O. mykiss), yearling Chinook salmon (O. tshawytscha), sub-yearling Chinook salmon, and sockeye salmon (O. nerka) during out-migration from the lower Snake River to the Pacific Ocean during an 11-year study period (2008-2018). Results indicated that probabilities of avian consumption varied greatly across salmonid populations, bird species, colony location, river reach, and year. Cumulative consumption probabilities (consumption by birds from all colonies combined) were consistently the highest for steelhead, with annual estimates ranging from 0.22 (95% credible interval = 0.20-0.26) to 0.51 (0.43-0.60) of available smolts. The cumulative effects of avian consumption were significantly lower for yearling and sub-yearling Chinook salmon, with consumption probabilities ranging annually from 0.04 (0.02-0.07) to 0.10 (0.07-0.15) and from 0.06 (0.3-0.09) to 0.15 (0.10-0.23), respectively. Avian consumption probabilities for sockeye salmon smolts was generally higher than for Chinook salmon smolts, but lower than for steelhead smolts, ranging annually from 0.08 (0.03-0.22) to 0.25 (0.14-0.44). Although annual consumption probabilities for birds from certain colonies were more than 0.20 of available smolts, probabilities from other colonies were less than 0.01 of available smolts, indicating that not all colonies of birds posed a substantial risk to smolt mortality. Consumption probabilities were lowest for small colonies and for colonies located a considerable distance from the Snake and Columbia rivers. Total mortality attributed to avian consumption was relatively small for Chinook salmon (less than 10%) but was the single greatest source of mortality for steelhead (greater than 50%) in all years evaluated. Results suggest that the potential benefits to salmonid populations of managing birds to reduce smolt mortality would vary widely depending on the salmonid population, the species of bird, and the size and location of the breeding colony.

(1) Background: Although the specificity of brush cytology for the detection of malignant pancreaticobiliary strictures is high, its sensitivity is low. Fluorescence in situ hybridization (FISH) can be used to detect chromosomal aneuploidy in biliary brushing specimens, and when used as an adjunct to routine cytology, it significantly improves diagnostic sensitivity. (2) Methods: We searched our laboratory information system to identify all bile duct brush cytology cases with follow-up surgical pathology between January 2001 and September 2019. Cytologic diagnoses were classified as negative, atypical, suspicious, or malignant. Correlated surgical pathological diagnoses were classified as benign or malignant. FISH test results were obtained for a subset of cytology cases with concurrent FISH testing, and the sensitivity, specificity, positive predictive value, and negative predictive value in identifying malignancy for cytology alone, FISH alone, and combined cytology and FISH were calculated. (3) Results: A total of 1017 brushing cytology cases with histologic correlation were identified. A total of 193 FISH tests were performed concurrently with cytological specimens. Malignant diagnoses were identified in 623 of 1017 patients, while 394 patients had benign strictures. The sensitivity, specificity, positive predictive, and negative predictive rate were 65%, 78%, 83%, and 49% for cytology alone; 72%, 67%, 63%, and 68% for FISH alone; and 85%, 42%, 60%, and 74% for combined cytology and FISH, respectively. Among FISH-positive cases, the risk of malignancy for polysomy was 82% and 32% for trisomy. (4) Conclusions: FISH improves the sensitivity and negative predictive rate of bile duct brush cytology. The combination of cytology and FISH has increased the sensitivity from 65% to 85% and the negative predictive rate from 49% to 74% when compared to cytology alone. A patient with a polysomy FISH result had a significantly higher risk of malignancy than a patient with a trisomy 7 result (82% vs. 32%, p < 0.00001).

Objectives Measuring quality of care is important, however many of the quality indicators used do not focus on outcome of treatment and aspects which are valuable for patients and physicians. The project ‘Care for Outcomes’ aims to establish a relevant set of outcome indicators for lung cancer.Setting Network of seven large, non-university teaching hospitals in the Netherlands (Santeon).Methods By reviewing the literature, a list of potential outcome indicators for patients with lung cancer was composed and subsequently prioritised by expert’s opinion. Three external parties, with expertise on lung cancer, clinical management and public health, evaluated and reduced the list of indicators to a working set. Finally, the resulting selection of outcome indicators was tested for feasibility and discrimination in patient data, by collecting retrospective data and performing regression and survival analyses.Participants Development of the indicator set in six Santeon hospitals. Retrospective cohort study in 5922 patients diagnosed with lung cancer (all types and stages).Results Selected outcome indicators were divided into three levels of outcome (tiers). The first tier about survival and the process of recovery include mortality, survival, positive resection margins, rethoracotomy after resection and quality of life at baseline and after 3, 6 and 12 months. Tier 2 concerning the sustainability of the recovery include complications after resection and toxicity after chemotherapy and/or radiation. Tier 3 about sustainability of health revealed no measurable outcomes. The retrospective data collection showed differences between hospitals and variation in case mix.Conclusion A relevant set of outcome indicators for lung cancer was systematically developed. This set has the potential to compare quality of care between hospitals and inform patients with lung cancer about outcomes. The project is ongoing in the current Santeon Value-Based Health Care programme through quality and improvement cycles.

This paper presents a study on the potential of ultra-high accurate UAV-based 3D data capture. It is motivated by a project aiming at the deformation monitoring of a ship lock and its surrounding. This study is part of a research and development project initiated by the German Federal Institute of Hydrology (BfG) in Koblenz in partnership with the Office of Development of Neckar River Heidelberg (ANH). For this first official presentation of the project, data from the first flight campaign will be analysed and presented. Despite the fact that monitoring aspects cannot be discussed before data from additional flight campaigns will be available later this year, our results from the first campaign highlight the potential of high-end UAV-based image and LiDAR sensors and their data fusion. So far, only techniques from engineering geodesy could fulfil the aspired accuracy demands in the range of millimetres. To the knowledge of the authors, this paper for the first time addresses such ultra-high accuracy applications by combing high precision UAV-based LiDAR and dense image matching. As the paper is written at an early stage of processing only preliminary results can be given here.

Digital airborne camera systems and their high geometric resolution demand for new algorithms and procedures of image data analysis and interpretation. Parameters describing image quality are necessary for various fields of application (e.g. sensor and mission design, sensor comparison, algorithm development, in-orbit-behaviour of instruments). The effective sensor resolution is one important parameter which comprehensively estimates the optical quality of a given imaging sensor-lens combination. Although determination of resolving power is a well-studied field of research, there are still some scientific questions to be answered when it comes to a standardized (eventually absolute) determination. This is also research object of a committee of the “German Institute for Standardization” and the given contribution outlines the current state of investigation concerning effective resolving power for airborne camera systems. Therefore an approach using signal processing techniques to calculate the effective image resolution will be described. The open scientific issues will be introduced, explained and answered to some extend.

The multi-lens multispectral cameras (MSCs), such as Micasense Rededge and Parrot Sequoia, can record multispectral information by each separated lenses. With their lightweight and small size, which making they are more suitable for mounting on an Unmanned Aerial System (UAS) to collect high spatial images for vegetation investigation. However, due to the multi-sensor geometry of multi-lens structure induces significant band misregistration effects in original image, performing band co-registration is necessary in order to obtain accurate spectral information. A robust and adaptive band-to-band image transform (RABBIT) is proposed to perform band co-registration of multi-lens MSCs. First is to obtain the camera rig information from camera system calibration, and utilizes the calibrated results for performing image transformation and lens distortion correction. Since the calibration uncertainty leads to different amount of systematic errors, the last step is to optimize the results in order to acquire a better co-registration accuracy. Due to the potential issues of parallax that will cause significant band misregistration effects when images are closer to the targets, four datasets thus acquired from Rededge and Sequoia were applied to evaluate the performance of RABBIT, including aerial and close-range imagery. From the results of aerial images, it shows that RABBIT can achieve sub-pixel accuracy level that is suitable for the band co-registration purpose of any multi-lens MSC. In addition, the results of close-range images also has same performance, if we focus on the band co-registration on specific target for 3D modelling, or when the target has equal distance to the camera.

UAV based imaging and 3D object point generation is an established technology. Some of the UAV users try to address (very) highaccuracy applications, i.e. inspection or monitoring scenarios. In order to guarantee such level of detail and accuracy high resolving imaging systems are mandatory. Furthermore, image quality considerably impacts photogrammetric processing, as the tie point transfer, mandatory for forming the block geometry, fully relies on the radiometric quality of images. Thus, empirical testing of radiometric camera performance is an important issue, in addition to standard (geometric) calibration, which normally is covered primarily. Within this paper the resolving power of ten different camera/lens installations has been investigated. Selected systems represent different camera classes, like DSLRs, system cameras, larger format cameras and proprietary systems. As the systems have been tested in wellcontrolled laboratory conditions and objective quality measures have been derived, individual performance can be compared directly, thus representing a first benchmark on radiometric performance of UAV cameras. The results have shown, that not only the selection of appropriate lens and camera body has an impact, in addition the image pre-processing, i.e. the use of a specific debayering method, significantly influences the final resolving power.

Different UAV platforms and sensors are used in mapping already, many of them equipped with (sometimes) modified cameras as known from the consumer market. Even though these systems normally fulfil their requested mapping accuracy, the question arises, which system performs best? This asks for a benchmark, to check selected UAV based camera systems in well-defined, reproducible environments. Such benchmark is tried within this work here. Nine different cameras used on UAV platforms, representing typical camera classes, are considered. The focus is laid on the geometry here, which is tightly linked to the process of geometrical calibration of the system. In most applications the calibration is performed in-situ, i.e. calibration parameters are obtained as part of the project data itself. This is often motivated because consumer cameras do not keep constant geometry, thus, cannot be seen as metric cameras. Still, some of the commercial systems are quite stable over time, as it was proven from repeated (terrestrial) calibrations runs. Already (pre-)calibrated systems may offer advantages, especially when the block geometry of the project does not allow for a stable and sufficient in-situ calibration. Especially for such scenario close to metric UAV cameras may have advantages. Empirical airborne test flights in a calibration field have shown how block geometry influences the estimated calibration parameters and how consistent the parameters from lab calibration can be reproduced.

The programmable sequence specificity of CRISPR has found uses in gene editing and diagnostics. This manuscript describes an additional application of CRISPR through a family of novel DNA enrichment technologies. CAMP (CRISPR Associated Multiplexed PCR) and cCAMP (chimeric CRISPR Associated Multiplexed PCR) utilize the sequence specificity of the Cas9/sgRNA complex to target loci for the ligation of a universal adapter that is used for subsequent amplification. cTRACE (chimeric Targeting Rare Alleles with CRISPR-based Enrichment) also applies this method to use Cas9/sgRNA to target loci for the addition of universal adapters, however it has an additional selection for specific mutations through the use of an allele-specific primer. These three methods can produce multiplex PCR that significantly reduces the optimization required for every target. The methods are also not specific to any downstream analytical platform. We additionally will present a mutation specific enrichment technology that is non-amplification based and leaves the DNA in its native state: TRACE (Targeting Rare Alleles with CRISPR-based Enrichment). TRACE utilizes the Cas9/sgRNA complex to sterically protect the ends of targeted sequences from exonuclease activity which digests both the normal variant as well as any off-target sequences.

In this paper we present the further evaluation of DLR’s modular airborne camera system MACS-Micro for small unmanned aerial vehicle (UAV). The main focus is on standardized calibration procedures and on photogrammetric workflows. The current prototype consists of an industrial grade frame imaging camera with 12 megapixel resolutions and a compact GNSS/IMU solution which are operated by an embedded computing unit (CPU). The camera was calibrated once pre-flight and several times post-flight over a period of 5 month using a three dimensional test field. The verification of the radiometric quality of the acquired images has been done under controlled static conditions and kinematic conditions testing different demosaicing methods. The validation of MACS-Micro is done by comparing a traditional photogrammetric evaluation with the workflows of Agisoft Photoscan and Pix4D Mapper. The analyses are based on an aerial survey of an urban environment using precise ground control points and acquired GNSS observations. Aerial triangulations with different configuratrions of ground control points (GCP’s) had been calculated, comparing the results of using a camera self-calibration and introducing fixed interior orientation parameters for Agisoft and Pix4D. The results are promising concerning the metric characteristics of the used camera and achieved accuracies in this test case. Further aspects have to be evaluated by further expanded test scenarios.