Semi-automatic Process Research Articles

Geoprocessing and Landscape Ecology for Assessment Fragmentation and Connectivity of the Habitats of the Microregion of Ceres, Goiás (Brazil)

This study aimed to map and evaluate the evolution of habitat fragmentation between 2009 and 2018, using the Microregion of Ceres (Goiás) as a sample reference, using principles of Landscape Ecology. The methodology comprised the mapping of the fragments in the two years analyzed, using the OLI/Landsat 8 sensor, using scenes 222/70 and 222/71. The SPRING 5.2 software was used, where the supervised classification was performed, applying the semi-automatic process. The computational algorithm applied to classify the scenes was Maxver, which classifies pixel by pixel and groups the information of each one into homogeneous regions. After extracting the fragments of native vegetation, the methodology proposed by Juvanhol et al. (2011), in which the fragments were grouped into classes: Very Small (MP) ≤5 hectares; Small (P) ≥5.01 and ≤10 hectares; Medium (M) ≥10.01 and ≤100 hectares and Large (G) ≥100.01 hectares. For the analysis based on metrics in Landscape Ecology, the ArcGis 9.2 Patch Analyst extension was used. The results showed the expansion of vegetation cover areas in the study area, concentrated on tops of hills, APP and legal reserves. However, they pointed out intense fragmentation of native vegetation, which hinders the performance of fragments as habitats. It is considered that, from the contemporary problem of degradation of natural environments to the detriment of economic development, studies like this are necessary in order to identify existing environmental problems and propose strategies to minimize and mitigate ecological imbalances.

In-situ X-ray difraction analysis of reverted austenite in supermartensitic stainless steel weld deposits

To improve the mechanical properties in supermartensitic stainless steel weld deposits, suitable post weld heat treatments (PWHT) are required, since these properties are controlled by the resulting microstructure. Some aspects of localized corrosion resistance could also be enhanced by the PWHT. In this sense, the austenite transformation or stability is a key issue. The aim of this work is to “in-situ” analyze the evolution of austenite during the thermal cycle associated to a post weld inter-critical heat treatment in a supermartensitic stainless steel weld deposit, by means of a thermomechanical simulator integrated on a synchrotron X-ray diffraction line. An all-weld metal coupon was welded with a semi-automatic process. Dilatometry measurements were performed at different heating rates (1, 10 and 100 K/s) in the thermomechanical simulator, to determine the critical transformation temperatures (Ac1 and Ac3) of the all-weld metal. To study the phase transformation during the applied thermal cycle (heating to 938 K at 1 K/s, maintenance during 15 min and cooling to room temperature at 2 K/s), in-situ synchrotron X-ray diffraction measurements were carried out in the facilities of National Laboratory Synchrotron Light (Campinas, Brasil). The microstructural evolution was discussed in terms of volumetric phase fractions, micro-deformation and crystallite size. The techniques used allow to detect the critical transformation temperatures, phase transformations and their kinetics, monitoring particularly the austenite evolution during the post weld heat treatment cycle. At the inter-critical temperature 71% of austenite was formed, after the 8.5 min from the 15 min of permanence. Finally, at room temperature 29% of stable reverted austenite was obtained. Both martensite and austenite there did not show significant variations during the thermal cycle both for microstrain and crystallite size.

OL92 - Radiomics features of 11[C]-MET PET/CT in primary brain tumors: preliminary results on grading discrimination using a machine learning model

1096 Background: Nowadays Artificial Intelligence (AI) algorithms have demonstrated remarkable progress in image-recognition tasks and could be useful for the new concept of precision medicine in order to help physicians in the choice of therapeutic strategies for brain tumors. Previous data suggest that, in primary brain tumor, amino acid PET may demarcate more accurately the active disease than paramagnetic enhanced MRI that is the standard method of the evaluation in brain tumors and help in the evaluation of disease grading, as a fundamental basis for the correct clinical management of these patients. The aim of this study is to propose a radiomics workflow in order to create a predictive model on 11[C]-MET PET/CT scan images capable to discriminate between low-grade and high-grade primary brain tumors. Materials and Methods: in this retrospective study we selected fifty-six patients affected by primary brain tumor who underwent 11[C]-MET PET/CT from January 2016 to December 2019 at the Nuclear Medicine department of the Cannizzaro Hospital of Catania. Histological specimen the analysis was available in all patients in order to confirm the diagnosis and grading disease. PET/CT acquisition was performed after 10 minutes from the administration of 11C-Methionine (401-610 MBq) for a time acquisition of 15 minutes. 11[C]-MET PET/CT images were acquired using two scanners (24 patients on a Siemens scan and 32 patients on a GE scan). Then, LIFEx software was used to perform the segmentation and the extraction of features in order to identify the volume of interest (VOI) and to extract features of first, second, and third-order. LIFEx calculates 44 RF reflecting the VOI shape, the VOI voxel values, the histogram of VOI values, or the VOI textural content. A novel mixed descriptive-inferential sequential approach was used to identify a subset of relevant features that correlate with the outcome. A machine learning model based on discriminant analysis was tested in the evaluation of grading prediction (low vs high-grade) of 11[C]-MET PET/CT. Results: The machine learning model applicated in this study to stratify brain tumors as “low” and “high” grade showed discriminant texture features as follow: two features in fixed ROI respectively NGLDM Busyness (p-value: 0.1615) and GLZLM LZLGE (p-value 0.3207); three features in total volume respectively SHAPE Sphericity (p-value 0.0314), SHAPE Compacity (p-value 0.0215) and HISTO Kurtosis (p-value 0.0232). The results of performances, using a semi-automatic and user-independent segmentation process and an innovative feature extraction process on fixed ROI, showed a good performance in prediction of disease grade with an accuracy of 70.31% (AUC 64.13%) in all patients, of 80.51% (AUC 65.73%) in GE tomograph, of 84.98%(AUC 78.91%) in Siemens Tomograph. Using our model of machine learning with discriminant analysis the results of the performances were suboptimal in all patients group( 24 Siemens plus 32 GE) with an accuracy of 57.25 % and AUC of 58.51%. However in subgroup analysis, despite the low number of patients and different scanner, our model demonstrated good performances in the prediction of disease grade as follow: GE Scanner Accuracy 71.64 and AUC 62.8%; Siemens Scanner Accuracy 72,88% and AUC 78.91%. Conclusions: This preliminary study on radiomics features analysis of 11[C]-MET PET/CT suggests a possible value of Artificial Intelligence to assess primary brain tumors and to predict disease outcome in terms of grading discrimination at diagnosis. Further studies are needed to improve radiomics algorithms to personalize predictive and prognostic models and potentially support the medical decision process.

Development of a Semiautomated Search Tool to Identify Grading From Pathology Reports for Tumors of the CNS and Prostate Cancers.

This study demonstrates the functionality of semiautomated algorithms to classify cancer-specific grading from electronic pathology reports generated from military treatment facilities. Two Perl-based algorithms are validated to classify WHO grade for tumors of the CNS and Gleason grades for prostate cancer. Case-finding cohorts were developed using diagnostic codes and matched by unique identifiers to obtain pathology records generated in the Military Health System for active duty service members from 2013 to 2018. Perl-based algorithms were applied to classify document-based pathology reports to identify malignant CNS tumors and prostate cancer, followed by a hand-review process to determine accuracy of the algorithm classifications. Inter-rater reliability, sensitivity, specificity, positive predictive values (PPVs), and negative predictive values were computed following abstractor adjudication. The high PPV for the Perl-based algorithms to classify CNS tumors (PPV > 98%) and prostate cancer (PPV > 99%) supports this approach to classify malignancies for cancer surveillance operations, mediated by a hand-reviewed semiautomated process to increase sensitivity by capturing ungraded cancers. Early detection was pronounced where 33.6% and 50.7% of malignant records retained a CNS WHO grade of II or a Gleason score of 6, respectively. Sensitivity metrics met criteria (> 75%) for brain (79.9%, 95% CI, 73.0 to 85.7) and prostate (96.7%, 95% CI, 94.9 to 98.0) cancers. Semiautomated, document-based text classification using Perl coding successfully leveraged identification of WHO and Gleason grades to classify pathology records for CNS tumors and prostate cancer. The process is recommended for data quality initiatives to support cancer reporting functions, epidemiology, and research.

TT52CAR19: Phase 1 Trial of CRISPR/Cas9 Edited Allogeneic CAR19 T Cells for Paediatric Relapsed/Refractory B-ALL

Background‘Off-the-shelf’ CAR T cell therapies are being investigated as alternatives to autologous CAR therapy, and can be generated using genome editing from allogeneic donors. Strategies to address HLA barriers include disruption of T cell receptor expression to prevent GVHD and removal of cell surface HLA expression to obviate host mediated rejection, as well as removal of CD52 to create a survival advantage in the presence of Alemtuzumab. In this study, lentiviral mediated CAR19 expression is linked to CRISPR editing through the incorporation of CRISPR guide RNA sequences within the vector 3'Long terminal repeat (LTR). The trial is in progress using pre-manufactured batches of TT52CAR19 T cells.Investigational medicinal product (IMP)Three allogeneic non-HLA matched donor derived CAR19 T cell banks were manufactured from steady state apheresis harvests from registry volunteer donors, using a semi-automated process under compliant conditions. Cells were activated with anti-CD3/CD28 (Transact) reagent and transduced with a lentiviral vector, TT52CAR19, and dual guide sgRNA cassettes targeting the T cell receptor alpha chain (TRAC) and CD52 loci. Next electroporation of Cas9 mRNA elicited transient genome editing, and automated magnetic bead depletion removed remaining TCRαβ+ T cells (mean 0.7%) and enriched CAR19+ T cells (mean 92.8%). Cells were cryopreserved in aliquots suitable for dose-banding and subjected to release testing, including flow cytometry, quantification of copy number (mean 3.83) and exclusion of replication competent lentivirus. Potency of each bank was confirmed in human:murine chimera experiments.Trial sponsorship & approvalsThe study is open at a single site and is sponsored by Great Ormond Street Hospital NHS trust and is supported by the Medical Research Council and National Institute for Health Research. Clinical trial authorisation was awarded by the MHRA after expert review, and ethical approval including gene therapy advisory committee (GTAC) review, and health research authority (HRA) approval. The study is open label, single arm and non-randomised.Study aims and ObjectivesThe study aims to establish the safety and feasibility of TT52CAR19 for the induction of molecular remission in children with relapsed /refractory CD19-positive B-cell acute lymphoblastic leukaemia (B-ALL) within 28 days, ahead of planned allogeneic haematopoietic stem cell transplantation (allo-SCT). Assessments include time to remission, duration of remission, disease-free survival and overall survival. Expansion, persistence and elimination of TT52CAR19 cells and tracking of immune recovery after allo-SCT is monitored. Recording of complications and toxicities, including possible genotoxic side effects from CRISPR/Cas9 modification provides safety profile information.Eligibility, infusion and outcomesThe study plans to treat 10 children aged between 6 months and < 18 years with CD19+ B-ALL quantified at >10 -4 in marrow (by flow or PCR) who are ineligible for autologous therapy. To date 2/4 children screened were found eligible and proceeded to lymphodepletion comprising Fludarabine, Cyclophosphamide and Alemtuzumab followed by a single infusion of 0.8-2.0x10 6 CAR19 T cells and a maximum of 5x10 4/kg TCRαβ T cells. In both cases, there was no GVHD or CRS >grade 1 and recovery of neutrophil counts by d28. Molecular remission was achieved in one child, where TT52CAR19 cells persistence was tracked by chimerism and copy number until further conditioning and allo-SCT. This child remains in remission >6 months later.ConclusionsFeasibility of pre-manufacturing off-the-shelf CRISPR/Cas9 edited CAR19 T cells is demonstrated and the trial has provided first in human safety data and preliminary indications of potent anti-leukaemic activity in one of two subjects dosed. DisclosuresQasim: Autolus: Current equity holder in publicly-traded company; Novartis: Honoraria; Servier: Research Funding; Tessa: Membership on an entity's Board of Directors or advisory committees.

Activity Worksheets for Teaching and Learning Data Visualization.

In this work, the data visualization activity (DVA) worksheet method for teaching and learning data visualization is presented. The DVA worksheet method consists of a series of activity worksheets developed to guide novice instructors and students through the data visualization process. The activity worksheets help new faculty and visualization instructors, lacking formal training in pedagogy and data visualization, learn the data visualization process, design course work, and develop curriculum. The worksheets can be used for individual activities, or as a collection of activities to support data visualization capacity building. Each worksheet focuses on an individual step in the process, allowing the worksheets to be tailored to discipline-specific data visualization needs. We share the motivation and evolution of the worksheets from paper-based to the semi-automated process utilized in fall 2020. We conclude this work with a discussion and areas for improvement.

Marker-less augmented reality based on monocular vision for falx meningioma localization.

The existing augmented reality (AR) based neuronavigation systems typically require markers and additional tracking devices for model registration, which causes excessive preparatory steps. For fast and accurate intraoperative navigation, this work proposes a marker-less AR system that tracks the head features with the monocular camera. After the semi-automatic initialization process, the feature points between the captured image and the pre-loaded keyframes are matched for obtaining correspondences. The camera pose is estimated by solving the Perspective-n-Point problem. The localization error of AR visualization on scalp and falx meningioma is 0.417±0.057 and 1.413±0.282mm, respectively. The maximum localization error is less than 2mm. The AR system is robust to occlusions and changes in viewpoint and scale. We demonstrate that the developed system can successfully display the augmented falx meningioma with enough accuracy and provide guidance for neurosurgeons to locate the tumour in brain.

Impact of Inter-and Intra-Fraction Motion on Delivered Dose for Prostate SBRT Patients Treated on an MRL-Linac Using a Novel Semi-Automated Dose Accumulation Framework

Online MR-guided adaptive RT enables generation of an adapted treatment plan at each fraction to account for daily anatomical changes, with both inter- and intrafraction internal motion impacting the accumulated dose. Our objective is to quantify the impact of motion on the accumulated delivered dose for prostate SBRT patients treated on an MRL using a novel semi-automated process for dose accumulation.We included 18 prostate SBRT patients treated on a prospective clinical trial with 30 Gy in 5 fraction SBRT on an integrated 1.5 T MRL with consecutive 15 Gy in 1 brachytherapy boost. We performed dose accumulation across the MRL treatment using a novel semi-automated workflow to import, deformably register, and deform each fraction dose to a reference MR. All deformable image registration (DIR) steps were performed automatically without manual input. We accumulated both the adapted plan dose, as assessed on localization MR image, and the final delivered dose, assessed on beam-on images acquired during treatment delivery. We qualitatively evaluated the DIR for all registrations using a 3-point scale and extracted organ motion from the deformation vector field. To assess the impact of intrafraction motion during online adaptation, we compared target and organ-at-risk dose-volume (DVH) metrics on the total accumulated dose for adapted plans versus delivered dose via paired t-tests with Bonferroni Correction.We qualitatively scored the DIR agreement for CTV, proximal bladder, rectum, and femurs to be within 2 mm agreement for all fractions, however, the distal bladder was unacceptable (> 5 mm differences). Mean absolute intrafraction motion was evaluated over all patients and fractions to be 0.7 ± 0.6 mm LR, 2.0 ± 1.4 mm AP and 1.8 ± 1.3 mm SI for the CTV, and 1.7 ± 0.7 mm LR, 2.5 ± 1.1 mm AP and 2.6 ± 1.0 mm SI for the rectum. The CTV D98 for accumulated delivered dose met the clinical goal of > 2850 cGy for all patients, with no significant difference compared to the adapted plans. The accumulated rectum D1cc DVH metric exhibited a significant decrease for delivered dose (2406 cGy) compared to the adapted plan (2548 cGy, P < 0.005), whereas bladder D5cc exhibited a significant increase for delivered dose (2905 cGy) compared to the adapted plan (2757 cGy, P < 0.001). No differences existed for rectum D20, D50, or femur D5.Here we demonstrated the feasibility of MRL dose accumulation for both online adapted plan distributions and estimated delivered dose for prostate SBRT treatments. In the presence of intrafraction motion between adapted plan generation and beam delivery, our results suggest only a minor impact on the accumulated dose. In the future we plan to use this dose accumulation framework to investigate different treatment approaches, such as adaptive intraprostatic dose escalation.

Development of Effective Risk Mitigation Strategy for Cell Culture Process of Recombinant Protein Production

Microbial contamination, instability in production yields and cell lines are the challenges that must be faced by any pharmaceutical biotechnology industry when conducting cell culture as one of the stages of its production process. In the past, Company X has experienced twice contamination cases during cell culture process for its recombinant protein products. As a result, Company X suffered financial lossess at approximately 3.05 billion rupiah and resulted in disruption of the stock of recombinant protein drug which are the active pharmaceutical ingredient for most of injection products. Therefore, an effective mitigation strategies are needed to manage any potential risks in the cell culture process. This study aims to design a risk mitigation strategy for risk in cell culture process by using House of Risk (HOR) method. There are two HOR matrices used in this study. HOR1 is used to determine which risk agents should be prioritized for prevention. In HOR2, several effective risk management strategies will be chosen. There are 40 risks events and 31 risk agents identified. Based on risk assessment results and applying Pareto Chart analysis there are two risk agents selected. Five proactive actions to mitigate these risks are proposed. They are training and personnel qualification program periodically, changing workflow become more efficient and convenient, more detailed revision of related documents, changing manual process to semi-automatic process gradually and additional person on each team as a verifier for double-checking.

Rethinking Authority Reconciliation Process

Entity identity management and name reconciliation are intrinsic to both Linked Open Data (LOD) and traditional library authority control. Does this mean that LOD sources can facilitate authority control? This Emblematica Online case study examines the utility of five LOD sources for name reconciliation, comparing design differences regarding ontologies, linking models, and entity properties. It explores the challenges of name reconciliation in the LOD environment and provides lessons learned during a semi-automated name reconciliation process. It also briefly discusses the potential values and benefits of LOD authorities to the authority reconciliation process itself and library services in general.

Data-Driven Object Pose Estimation in a Practical Bin-Picking Application.

This paper addresses the problem of pose estimation from 2D images for textureless industrial metallic parts for a semistructured bin-picking task. The appearance of metallic reflective parts is highly dependent on the camera viewing direction, as well as the distribution of light on the object, making conventional vision-based methods unsuitable for the task. We propose a solution using direct light at a fixed position to the camera, mounted directly on the robot’s gripper, that allows us to take advantage of the reflective properties of the manipulated object. We propose a data-driven approach based on convolutional neural networks (CNN), without the need for a hard-coded geometry of the manipulated object. The solution was modified for an industrial application and extensively tested in a real factory. Our solution uses a cheap 2D camera and allows for a semi-automatic data-gathering process on-site.

Localised manual therapy treatment has a preferential effect on the kinematics of the targeted motion segment

Aim: An observational cohort study to determine whether localised manual therapy results in a preferential increase in mobility of the targeted motion segment.Method: Eighteen participants with mechanical neck pain had three MRIs of their cervical spine. The first two were taken prior to treatment in neutral and at the end of active rotation in their more limited rotation. Participants received localised manual therapy targeting a motion segment deemed to be relevant to their presentation until either their range increased by > 10° or 8 min, whichever came first. A third MRI was performed immediately after treatment with their head in the same rotated position as pre-treatment. In the images, each vertebra was segmented using a semi-automated process. Movement between neutral and rotated positions was calculated as Euler angles and distance of facet translations for each motion segment.Results: Rotation and lateral flexion at the targeted location increased by 40% (mean 0.86° (CI: 0.24–1.48) and 15% (mean 0.52° (CI: 0.17–1.21) respectively with only the CIs for rotation not containing zero. The mean changes for the non-targeted locations were less than 0.1° for each axis and all CIs contained zero. Facet translations at the targeted location increased by 25% (0.419 mm) and decreased by >4% (>0.01 mm) at the untreated locations but the wide CIs both contained zero.Conclusion: Localised manual therapy seems to have a preferential effect on mobility of the targeted motion segment. The findings support considering segmental dysfunction in clinical reasoning and the use of specifically targeted manual therapy interventions.

Verification of News Video Content: Findings from a Study of Journalism Students

ABSTRACT The rapid spread of misinformation online has been deemed as a growing problem in the current digital media environment with significant impact both on journalism and on society at large. As news practitioners are increasingly challenged by information overload and the need to process huge volumes of unstructured and unfiltered data within a very short time span, the veracity of online and User-Generated Content (UGC) and its spread through social media and video platforms has been identified as a key concern. This study aims to extend the body of knowledge on the verification of news video content, derived from social media platforms. Using a web-based tool that analyses the online context around a video post and presents a number of verification signals, a set of fake and real news videos coming from YouTube and Facebook were examined by a sample of journalism students (N = 90) regarding their veracity. A sample of professional journalists (N = 17) was also used for qualitative comparison purposes and additional results. The results of the study highlight the significance of online context as well as the efficacy of a semi-automated process in the verification of video content and journalism practice, in conjunction with useful verification features and practices.

Results of Using Automated Clinimacs Prodigy for CD34 Selection from Mobilized Peripheral Blood Stem Cell Products

Cell selection is an important part of graft manipulation for cellular therapies. The CliniMACS Plus system has been used in our laboratory for over 15 years to deplete T-cells from stem cell grafts of the unrelated donors for paediatric patients undergoing BMT. The recently introduced CliniMACS Prodigy® (Miltenyi Biotec) permits automated selection of CD34+ cells from mobilized peripheral blood stem cells (PBSCs) using monoclonal antibodies conjugated to paramagnetic particles in a complete closed system. We have been evaluating the Prodigy and we report the most extensive evaluation, to date, between the Prodigy and the CliniMACS Plus systems. METHODSWe validated the CD34 selection program on the Prodigy (LP-34, using the new version 2.0) against the standard semi-automatic CD34 selection process on the CliniMACS Plus. PBSCs were collected by apheresis from nine healthy adult subjects after mobilisation with G-CSF. Excess PBSCs were loaded onto the Prodigy the day after the clinical procedure. Target and non-target cells were enumerated using standard viable single platform flow cytometry. The nine Prodigy procedures were assessed for product quality against historical CliniMACS Plus data. Samples used for the Prodigy validation (not clinically infused), were only used when the requested CD34 dose had been achieved using the CliniMACS Plus.RESULTS (see Table 1):All nine Prodigy procedures were completed without event. Although there was no difference in procedure times between the two machines, there was a reduction in “hands on” time using the CliniMACS Prodigy. Eight of the nine PBSCs were collected from overseas and loaded onto the Prodigy the day after the clinical processing. The age of products loaded onto the instrument ranged from 21 to 139 hours, median 41 hours. Despite the age of the product there was no clumping observed. CONCLUSIONSCD34+ cells can be effectively selected from mobilized PBSCs with the CliniMACs Prodigy, including those that have had prolonged transit times. The recovery and purity of CD34+ cells was comparable to the CliniMACS Plus but depletion of T and B-cells was found to be lower on the Prodigy compared to the CliniMACS Plus. The T cell and B cell content per kg, from the Prodigy, was below 10x10^4/kg, the upper limit for clinical release criteria. The Prodigy offers a single device for CD34 cell selection, unlike the CliniMACS Plus which required the apheresis product to have prior processing (such as platelet removal, labelling and washing prior to cells etc.) on other equipment. The Prodigy process is fully automated and this translates into a reduction in the time required of experienced laboratory staff. Our results suggest that the Prodigy can be used for the routine clinical application of CD34 selection to HSCT products. Analysis of other complex cell manipulations using the CliniMACS Prodigy will require further validation. [Display omitted] DisclosuresGottlieb:Abbvie: Membership on an entity's Board of Directors or advisory committees; Indee: Membership on an entity's Board of Directors or advisory committees.

Mimicking the process of manual sequence stratigraphy well correlation

Stratigraphic correlation of well logs is based on interactive interpreter-based pattern recognition. A skilled interpreter identifies similar patterns (such as upward fining and coarsening) in user-defined well sections and links them using either a conscious or subconscious stratigraphic model. This manual stratigraphic correlation of numerous wells in mature fields can be time-consuming and error-prone. To expedite the process of stratigraphic correlation, we have performed semiautomatic stratigraphic correlation of wireline logs from multiple wells using improved dynamic time warping (IDTW). IDTW uses semblance, which compares the shape of the well logs, to replace the Euclidean distance in pairwise error computation. The resulting error matrix is compatible with the lateral nonstationary variation of well logs in the same formation. The workflow begins with interpreting stratigraphic well tops on user-defined well sections that is similar to the current process of stratigraphy analysis. The interpreted wells are then treated as reference wells to aid in interpreting well tops for other wells. Necessary manual interventions are incorporated during the semiautomatic stratigraphic correlation process. We applied our method to two experimental fields: a sand-rich reservoir and a mud-rich reservoir. The applications illustrate that our method performs well in aggradational strata and successfully predicts discontinuities with manual interventions.

Semi-automated stair climbing of a wheel hub-based patient transportation aid for emergency medical services

Abstract A novel approach for a patient transportation aid for emergency medical services bases on a wheel hub stair-climbing mechanism, which currently requires a manual adjustment relative to the stair edges. In this paper, an approach for an automation is presented which utilizes two distance sensors to characterize stairs and determine the relative position to them. A controller can then adjust the system’s position automatically. A user supervision concept copes with sensor inaccuracies or errors, resulting in a semi-automatic process. Within a formative usability study ( n = 11 n=11 users) the algorithm was able to reconstruct the stairs and drive the system neither falling down nor colliding with steps. The semi-automatic process reduced climbing time by 59 % and the participants reported a higher subjective usability compared to manual stair climbing.

Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland

Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. However, variability in snow cover can confound satellite-based efforts to monitor vegetation phenology. This research explores the utility of the PhenoCam Network cameras to estimate Fractional Snow Cover (FSC) in grassland. The goal is to operationalize FSC estimates from PhenoCams to inform and improve the satellite-based determination of phenological metrics. The study site is the Oakville Prairie Biological Field Station, located near Grand Forks, North Dakota. We developed a semi-automated process to estimate FSC from PhenoCam images through Python coding. Compared with previous research employing RGB images only, our use of the monochrome RGB + NIR (near-infrared) reduced pixel misclassification and increased accuracy. The results had an average RMSE of less than 8% FSC compared to visual estimates. Our pixel-based accuracy assessment showed that the overall accuracy of the images selected for validation was 92%. This is a promising outcome, although not every PhenoCam Network system has NIR capability.

Ambient Air Blade‐Coating Fabrication of Stable Triple‐Cation Perovskite Solar Modules by Green Solvent Quenching

Although halide perovskite solar cell (PSC) technology reaches, in few years, efficiencies greater than 25%, the cost‐ceffective perspective is achievable only if scalable processes in real manufacturing conditions (i.e., pilot line and/or plant factory) are designed and optimized for the full device stack. Herein, a full semiautomatic scalable process based on the blade‐coating technique is demonstrated to fabricate perovskite solar modules in ambient conditions. An efficient and stable triple‐cation cesium methylammonium formamidinium (CsMAFA) perovskite is deposited in ambient air with a two‐step process assisted by air and green anti‐solvent quenching. The developed industry compatible coating process enables the fabrication of several highly reproducible small‐area cells on module size substrate with an efficiency exceeding 17% and with high reproducibility. Corresponding reproducible modules (less than 2% variability) with a 90% geometrical fill factor achieve an efficiency larger than 16% and T 80 = 750 h in light‐soaking condition at maximum power point and room temperature/ambient after encapsulation. Film deposition properties are assessed by different characterization techniques, namely, scanning electron microscopy, profilometry, UV–vis and photoluminescence (PL) spectroscopy, and PL and electroluminescence imaging. The techniques confirm less defects and local coating variations of the ambient air/bladed devices with respect to the nitrogen air/spinned devices.

Assessing Shoreline Change using Historical Aerial and RapidEye Satellite Imagery (Cape Jaffa, South Australia)

DaSilva, M.; Miot da Silva, G.; Hesp, P.A.; Bruce, D.; Keane, R., and Moore, C., 2021. Assessing shoreline change using historical aerial and RapidEye satellite imagery (Cape Jaffa, South Australia). Journal of Coastal Research, 37(3), 468–483. Coconut Creek (Florida), ISSN 0749-0208.The coastal zone is a dynamic area which can experience substantial natural change in short time periods, but changes are also associated with human modifications to the coastline. This case study is focused around assessing shoreline change associated with the Cape Jaffa Marina and canal estate in South Australia. The research comprises a GIS based analysis of shoreline change utilising aerial imagery from 1975 to 2005, which provides information of the morphological coastal trends prior to construction in 2008 of the marina/canal estate. In addition, imagery collected by the RapidEye satellite constellation was used to assess shoreline changes in the decade since construction, 2009 to 2019. The shoreline change statistics over the past few decades were calculated using the Digital Shoreline Analysis System extension of ESRI's ArcGIS. The image analysis workflow is based on the objective extraction of shoreline proxies from individual image statistics in a semi-automated process and is used to identify the waterline and edge of vegetation shoreline proxies in a time series analysis. The results provide a case study of a historically progradational sandy coastline experiencing substantial amounts of alongshore sediment transport, the corresponding obstruction from coastal infrastructure, and the resulting morphological changes to the Cape Jaffa shoreline. Shoreline change trends were altered from a predominantly accretional shoreline before the construction of the marina to one oscillating between extremes of erosion and accretion. The results showed significant accretion occurring updrift (Net Shore Movement (NSM) of 106 m) and significant erosion downdrift (NSM of –80 m) of the marina's training walls and entrance. The information derived from Earth observation satellites, such as RapidEye, can provide valuable insights into trend analysis due to their relatively high spatial (5 metre) and temporal resolution (5.5-day revisit).

STAGER: Semantic-Based Framework for Generating Adapters of Service-Based Generic-API for Portable Cloud Applications

In PaaS model, providers have different proprietary APIs, which make developers locked inside a specific platform and not able to easily port their applications among different platforms. So, vendor lock-in problem appeared. One solution to this problem is to use generic APIs with specific adapters. However, any update in a PaaS specific-API makes its corresponding adapter is unusable which causes, what we call, API synchronization problem. Therefore, STAGER (SemanTic-based GenERation of Generic-API Adapters) framework is proposed. STAGER framework provides a semi-automatic adapter generation process, which generates specific adapters of generic APIs for PaaS services (e.g., blob storage and datastore services) for target PaaS platforms. The adapter generation process is based on semantic annotations of the generic APIs and their corresponding PaaS specific-APIs. In order to evaluate STAGER framework, two generic APIs for blob storage and NoSQL datastore services have been proposed. STAGER framework is used to generate the adapters of these generic APIs for two PaaS platforms: Google App Engine (GAE) and Windows Azure. Although there is some overhead for semantically annotating the PaaS APIs, the evaluation results prove the feasibility of STAGER framework and promote the usage of the generated adapters for implementing portable cloud applications.