In-field Validation Research Articles

System configuration, control development, and in-field validation of a hybrid electric wheel loader featuring electrically-boosted engine

This paper proposes an innovative next-generation wheel loader derived from a production series electric wheel loader by John Deere. The proposed wheel loader features a series hybrid electric powertrain with an energy storage system and an electrically-boosted turbocharged diesel engine. A detailed system design inclusive of powertrain configuration and control development including a novel heuristics-based vehicle power management is presented. A simulation model was created to evaluate the potential fuel savings of the proposed wheel loader, revealing a fuel saving potential of over 10% when compared to the baseline configuration. Subsequent in-field testing of an actual demo wheel loader verified its ability to achieve over 10% fuel savings, thereby confirming the simulation outcomes, demonstrating the promise of the proposed hybrid powertrain, and validating the efficacy of the control system developed in this research.

Enhancing visual autonomous navigation in row-based crops with effective synthetic data generation

Abstract Introduction Service robotics is recently enhancing precision agriculture enabling many automated processes based on efficient autonomous navigation solutions. However, data generation and in-field validation campaigns hinder the progress of large-scale autonomous platforms. Simulated environments and deep visual perception are spreading as successful tools to speed up the development of robust navigation with low-cost RGB-D cameras. Materials and methods In this context, the contribution of this work resides in a complete framework to fully exploit synthetic data for a robust visual control of mobile robots. A wide realistic multi-crops dataset is accurately generated to train deep semantic segmentation networks and enabling robust performance in challenging real-world conditions. An automatic parametric approach enables an easy customization of virtual field geometry and features for a fast reliable evaluation of navigation algorithms. Results and conclusion The high quality of the generated synthetic dataset is demonstrated by an extensive experimentation with real crops images and benchmarking the resulting robot navigation both in virtual and real fields with relevant metrics.

A Method for Evaluating Global Navigation Satellite System Position Accuracy in Small Unmanned Aircraft Systems

Highlights A novel UAS-based GNSS testing system was developed to assess both horizontal and vertical accuracy components. Recommendations are provided for further standard development related to UAS GNSS testing protocols. Future research can utilize this framework to enhance understanding of UAS GNSS accuracy. Abstract. Current standards for Global Navigation Satellite Systems (GNSS) testing are primarily designed for assessing horizontal positioning accuracy in ground-based applications. However, there is a notable absence of guidelines specifically addressing vertical accuracy assessment and applications that extend beyond ground-based scenarios, including those involving small unmanned aircraft systems (UAS). This effort aimed to develop a UAS-based GNSS testing system, tailored for the evaluation of GNSS receiver performance in dynamic low-altitude scenarios. The main objectives included (1) designing a GNSS testing system for UAS applications and (2) validating the system through field testing. The system development consisted of GNSS receiver configuration, data acquisition system design, processing procedures, and UAS payload and base station component design. The UAS payload featured multiple GNSS receivers operating in different modes, and data were collected using a custom Python script on a Raspberry Pi computer. For in-field validation, dynamic flight testing with vertical profiles was conducted. A robotic tracking total station (TTS) was used as the reference instrument for measuring the location of the UAS payload. The findings underscore the system's capabilities, primarily emphasizing its functionality rather than conducting an extensive assessment of the individual GNSS receiver performance. The UAS-based testing system that was developed was capable of satisfying most of the criteria for existing GNSS test standards. The insights derived from this process offer recommendations for standardizing UAS-based GNSS testing methods, with a particular focus on mission design, battery management, data processing, and environmental adaptability. Keywords: Dynamic Error, Global Navigation Satellite Systems (GNSS), Positioning Accuracy, Tracking Total Station (TTS), Unmanned Aircraft Systems (UAS).

Design, tuning and in-field validation of energy harvesters for railway bridges

Energy harvesters are a promising technology for powering infrastructure condition monitoring systems without batteries. When deployed on railway bridges they are typically tuned to the bridge’s natural frequency, however due to the dominance of train-induced forced vibration of the structure, this results in sub-optimal energy harvesting. As a solution, this paper presents a novel tuning strategy for energy harvesters on railway bridges. The strategy is based on a statistical analysis of the mechanical energy generated in the bridge during train passage and involves four steps: (i) measurement of bridge response due to train traffic, (ii) calculation of mechanical energy during train passage, (iii) statistical characterisation of the energy distribution, and finally, (iv) calculation of the tuning frequency. A case study is presented to compare the potential of the proposed strategy against tuning based upon the bridge natural frequency. First, an in-service railway bridge is monitored to determine its natural frequency and response to train traffic. Combining the field data with the proposed tuning strategy, the design of energy harvesters for the bridge is optimised. The design of harvesters tuned to natural frequencies is also studied. The underlying harvester type is a cantilever bimorph beam with a mass at the tip and load resistance. Additive manufacturing is used for the substructure, which is formed from PAHT-CF15 (High Temperature Polyamide carbon fibre reinforcement). The harvesters are manufactured and deployed on the bridge subject to live railway traffic. Field results show the devices designed using the new tuning strategy harvest up to 300% more energy. The energy harvested in a time window of three hours (18 train passages) is 7.65mJ.

Extended in-field and out-of-field validation of a compact Monte Carlo model of an IBA PROTEUS®ONE proton beam in TOPAS/GEANT4

Objective: This study evaluates a compact Monte Carlo (MC) model of a pencil beam scanning clinical proton beam using TOPAS to estimate the dose out-of-field (OOF). Compact modelling means that the model starts from a pristine proton beam at the nozzle exit, customised based on acceptance and commissioning data, instead of modelling the full treatment head and room. Approach: First, in-field validation tests were performed. Then, the OOF dose was validated in an RW3 phantom with bubble detectors for personal neutron dosimetry (measuring the neutron dose equivalent) and thermoluminiescent detectors (measuring the absorbed dose by protons and gammas). Measurements were performed at 15 and 35 cm from the distal edge of the field for five different irradiation plans, covering different beam orientations, proton energies and a 40 mm range shifter. TOPAS simulations were performed with QGSP Binary Cascade HP (BIC) and QGSP Bertini HP (Bertini) hadron physics lists. Main results: In-field validation shows that MC simulations agree with point dose measurements within −2.5 % and +1.5 % at locations on- and off-axis and before, in and after the Bragg peak or plateau. The gamma passing rate 2%/3mm of four simulated treatment plans compared to the dose distribution calculated by the TPS exceeds 97 % agreement score. OOF dose simulations showed an average overestimation of 27 % of the neutron dose equivalent for the BIC hadron physics list and an average underestimation of 20 % for the Bertini hadron physics list. The simulated absorbed dose of protons and gammas showed a systematic underestimation which was on average 21 % and 51 % for BIC and Bertini respectively. Significance: Our study demonstrates that a compact MC model can reliably produce in-field data, while out-of-field dose data are within the uncertainties of the detector systems and MC simulations nuclear models, and do so with shorter modelling and faster calculation time.

Efficacy of Peracetic Acid and Chlorine on the Reduction of Shiga Toxin-producing Escherichia coli and a Nonpathogenic E. coli Strain in Preharvest Agricultural Water

Produce-borne outbreaks of Shiga toxin-producing Escherichia coli (STEC) linked to preharvest water emphasize the need for efficacious water treatment options. This study quantified reductions of STEC and generic E. coli in preharvest agricultural water using commercially available sanitizers. Water was collected from two sources in Virginia (pond, river) and inoculated with either a seven-strain STEC panel or environmental generic E. coli strain TVS 353 (∼9 log10 CFU/100 mL). Triplicate inoculated water samples were equilibrated to 12 or 32°C and treated with peracetic acid (PAA) or chlorine (Cl) [low (PAA:6ppm, Cl:2–4 ppm) or high (PAA:10 ppm, Cl:10–12 ppm) residual concentrations] for an allotted contact time (1, 5, or 10 min). Strains were enumerated, and a log-linear model was used to characterize how treatment combinations influenced reductions. All Cl treatment combinations achieved a ≥3 log10 CFU/100 mL reduction, regardless of strain (3.43 ± 0.25 to 7.05 ± 0.00 log10 CFU/100 mL). Approximately 80% (19/24) and 67% (16/24) of PAA treatment combinations achieved a ≥3 log10 CFU/100 mL for STEC and E. coli TVS 353, respectively. The log-linear model showed contact time (10 > 5 > 1 min) and sanitizer type (Cl > PAA) had the greatest impact on STEC and E. coli TVS 353 reductions (p < 0.001). E. coli TVS 353 in water samples was more resistant to sanitizer treatment (p < 0.001) indicating applicability as a good surrogate. Results demonstrated Cl and PAA can be effective agricultural water treatment strategies when sanitizer chemistry is managed. These data will assist with the development of in-field validation studies and may identify suitable candidates for the registration of antimicrobial pesticide products for use against foodborne pathogens in preharvest agricultural water treatment.

Design, construction and modeling of a small-scale high temperature field rotor test rig

In-field validation of radiation thermometer performance is time consuming and expensive, especially when prototype experiments are performed. This study focuses on the development of a novel small-scale high temperature field simulation test rig for measuring turbine blade surface temperatures under changing environmental conditions. When developing and testing a radiation thermometer, the testing is typically performed directly on a test rig that can simultaneously provide a standardized environment and compare temperature data. This apparatus allows for static and dynamic temperature testing in a hostile environment by combining temperature, particle, and atmospheric effects. In the present study, a test rig will be utilized to analyze and validate the radiation thermometer, which will be subjected to harsh combined environmental variables with a temperature range of up to 2000K. Notably, the rotating head structure of the two materials allows for the application of a vast range of temperature measurements (700–2000 K), which is a distinctive characteristic of the design. The requirements of the test rig are defined based on the specimens to be tested. The necessity for the combined complete test setup, as well as its design and functionality, are discussed in this paper. Finally, validation experiments are conducted to demonstrate the test rig's accuracy in measuring turbine blade surface temperature, which is 0.25%.

The AERosol and TRACe gas Collector (AERTRACC): an online-measurement-controlled sampler for source-resolved emission analysis

Abstract. Probing sources of atmospheric pollution in complex environments often leads to the measurement and sampling of a mixture of different aerosol types due to fluctuations of the emissions or the atmospheric transport situation. Here, we present the AERosol and TRACe gas Collector (AERTRACC), a system for sampling various aerosol types independently on separate sampling media, controlled by parallel online measurements of particle, trace gas, and meteorological variables, like particle number or mass concentration, particle composition, trace gas concentration, and wind direction and speed. AERTRACC is incorporated into our mobile laboratory (MoLa) which houses online instruments that measure various physical and chemical aerosol properties, as well as trace gas concentrations. Based on preparatory online measurements with the whole MoLa setup, suitable parameters measured by these instruments are used to define individual sampling conditions for each targeted aerosol type using a dedicated software interface. Through evaluation of continuously online-measured data with regard to the sampling conditions, the sampler automatically switches between sampling and non-sampling for each of up to four samples, which can be collected in parallel. The particle phase and gas phase of each aerosol type, e.g., source emissions and background, are sampled onto separate filters with PM1 and PM10 cutoffs and thermal desorption tubes, respectively. Information on chemical compounds in the sampled aerosol is obtained by means of thermal desorption chemical ionization mass spectrometry (TD-CIMS) as the analysis method. The design, operation, and characterization of the sampler are presented. For in-field validation, wood-fired pizza oven emissions were sampled as targeted emissions separately from ambient background. Results show that the combination of well-chosen sampling conditions allows more efficient and effective separation of source-related aerosols from the background, as seen by the increases of particle number and mass concentration and concentration of organic aerosol types, with minimized loss of sampling time compared to alternative sampling strategies.

Estimation of Temporal Parameters During Running with a Wrist-worn Inertial Sensor: an In-field Validation.

The aim of this study was to estimate the temporal gait parameters using a wrist-worn Inertial Measurement Unit (IMU) during an outdoor run. While it is easier to compute running gait parameters using foot IMUs, a wrist IMU is more convenient and less obtrusive when it comes to data acquisition. During a track run of 12 minutes, we equipped 14 highly-trained male runners with one IMU on the wrist and one on each foot. We trained machine learning models based on CNN, GPR, and Lasso regression using wrist IMU signals and validated them with a foot-worn IMU reference system. Lasso model performed the best, with the accuracy for cycle time, swing time, flight time, and contact time being 0.27 % ±0.1 %, 2.6 %±1.7 %, 7.3 % ±4.9 %, and 10.6 % ±5.5 %, respectively.

Field-Deployable Recombinase Polymerase Amplification Assay for Specific, Sensitive and Rapid Detection of the US Select Agent and Toxigenic Bacterium, Rathayibacter toxicus

Simple SummaryEarly, accurate, and rapid detection of R. toxicus is extremely important to improve inspections of imported annual ryegrass hay and seed at ports of entry and enhance in-field detection. RPA is a comparatively new, easy to use, and robust technology that can be performed in the palm of the hand without losing specificity. The RPA assay was more sensitive than endpoint PCR and did not require lab equipment in the field. The developed assay has tremendous applications for in-field plant diagnostics and biosecurity surveillance.Rathayibacter toxicus is a toxigenic bacterial pathogen of several grass species and is responsible for massive livestock deaths in Australia and South Africa. Due to concern for animal health and livestock industries, it was designated a U.S. Select Agent. A rapid, accurate, and sensitive in-field detection method was designed to assist biosecurity surveillance surveys and to support export certification of annual ryegrass hay and seed. Complete genomes from all known R. toxicus populations were explored, unique diagnostic sequences identified, and target-specific primers and a probe for recombinase polymerase amplification (RPA) and endpoint PCR were designed. The RPA reaction ran at 37 °C and a lateral flow device (LFD) was used to visualize the amplified products. To enhance reliability and accuracy, primers and probes were also designed to detect portions of host ITS regions. RPA assay specificity and sensitivity were compared to endpoint PCR using appropriate inclusivity and exclusivity panels. The RPA assay sensitivity (10 fg) was 10 times more sensitive than endpoint PCR with and without a host DNA background. In comparative tests, the RPA assay was unaffected by plant-derived amplification inhibitors, unlike the LAMP and end-point PCR assays. In-field validation of the RPA assay at multiple sites in South Australia confirmed the efficiency, specificity, and applicability of the RPA assay. The RPA assay will support disease management and evidence-based in-field biosecurity decisions.

Evaluating establishment of conservation practices in the Conservation Reserve Program across the central and western United States

The U.S. Department of Agriculture’s Conservation Reserve Program (CRP) is one of the largest private lands conservation programs in the United States, establishing perennial vegetation on environmentally sensitive lands formerly in agricultural production. Over its 35 year existence, the CRP has evolved to include diverse conservation practices (CPs) while concomitantly meeting its core goals of reducing soil erosion, improving water quality, and providing wildlife habitat. Ongoing threats to grasslands and decreased CRP acreage highlighted the need for a national evaluation of the effectiveness in providing the program’s intended benefits. To address this need, we conducted edge-of-field surveys of erosional features, vegetation, and soil cover on 1 786 fields across 10 CPs and 14 central and western states from 2016 to 2018. We grouped practices into three types (grassland, wetland, and wildlife) and states into six regions for analysis. Across practice types, ⩾99% of fields had no evidence of rills, gullies, or pedestaling from erosion, and 91% of fields had <20% bare soil cover, with region being the strongest predictor of bare soil cover. Seventy-nine percent of fields had ⩾50% grass cover, with cover differing by practice type and region. Native grass species were present on more fields in wildlife and wetland practices compared to grassland practices. Forb cover >50% and native forb presence occurred most frequently in wildlife practices, with region being the strongest driver of differences. Federally listed noxious grass and forb species occurred on 23% and 61% of fields, respectively, but tended to constitute a small portion of cover in the field. Estimates from edge-of-field surveys and in-field validation sampling were strongly correlated, demonstrating the utility of the edge-of-field surveys. Our results provide the first national-level assessment of CRP establishment in three decades, confirming that enrolled wildlife and wetland practices often have diverse perennial vegetation cover and very few erosional features.

FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service.

Background and Purpose:Considering the highly time-dependent therapeutic effect of endovascular treatment in patients with large vessel occlusion–associated acute ischemic stroke, prehospital identification of large vessel occlusion and subsequent triage for direct transport to a comprehensive stroke center offers an intriguing option for optimizing patient pathways.Methods:This prospective in-field validation study included 200 patients with suspected acute ischemic stroke who were admitted by emergency medical service to a comprehensive stroke center. Ambulances were equipped with smartphones running an app-based Field Assessment Stroke Triage for Emergency Destination scale for transmission prior to admission. The primary measure was the predictive accuracy of the transmitted Field Assessment Stroke Triage for Emergency Destination for large vessel occlusion and the secondary measure the predictive accuracy for endovascular treatment.Results:A Field Assessment Stroke Triage for Emergency Destination ⩾4 revealed very good accuracy to detect large vessel occlusion–related acute ischemic stroke with a sensitivity of 82.4% (95% confidence interval = 65.5–93.2), specificity of 78.3% (95% confidence interval = 71.3–84.3), and an area under the curve c-statistics of 0.89 (95% confidence interval = 0.85–0.94). Field Assessment Stroke Triage for Emergency Destination ⩾4 correctly identified 84% of patients who received endovascular treatment [73.5% specificity (95% confidence interval = 66.4–79.8)] with an area under the curve c-statistics of 0.82 (95% confidence interval = 0.74–0.89). In a hypothetical triage model of an urban setting, one secondary transportation would be avoided with every fifth patient screened.Conclusion:A smartphone app-based stroke triage completed by emergency medical service personnel showed adequate quality for the Field Assessment Stroke Triage for Emergency Destination to identify large vessel occlusion–associated acute ischemic stroke. We demonstrate feasibility of the use of a medical messaging service in prehospital stroke care. Based on these first results, a randomized trial evaluating the clinical benefit of such a triage system in an urban setting is currently in preparation.Clinical Trial Registration: https://clinicaltrials.gov Unique identifier: NCT04404504.

An accurate method for predicting spatial variability of maize yield from UAV-based plant height estimation: a tool for monitoring agronomic field experiments

Estimating aboveground biomass is important for monitoring crop growth in agronomic field experiments. Often this estimation is done manually, destructively (mowing) or not (counting) on a relatively limited number of sub-plots within an experiment. In the presence of spatial heterogeneity in experiment fields, sensors developed for precision agriculture, have shown great potential to automate this estimation efficiently and provide a spatially continuous measurement over an entire plot. This study investigated the suitability of using an unmanned aerial vehicle (UAV) for biomass and yield estimations in an agronomic field experiment. The main objectives of this work were to compare the estimates made from manual field sampling with those made from UAV data and finally to calculate the improvement that can be expected from the use of UAVs. A 6-ha maize field was studied, with plot treatments for the study of the exogenous organic matter (EOM) amendment effect on crop development. 3D surface models were created from high resolution UAV RGB imagery, before crop emergence and during crop development. The difference between both surface models resulted in crop height which was evaluated against 38 reference points with an R2 of 0.9 and prediction error of 0.16 m. Regression models were used to predict above-ground biomass and grain yield (fresh or dry). Dried grain yield prediction with a generalized additive model gave an error of 0.8 t ha−1 calculated on 100 in-field validation measurements, corresponding to a relative error of 14.77%. UAV-based yield estimates from dry biomass were 15% more accurate than manual yield estimation.

Prehospital Triage of Patients with Suspected Stroke (PRESTO): A Prospective In-Field Validation of Eight Prehospital Stroke Scales to Detect Intracranial Large Vessel Occlusion

Background: Due to the time-sensitive effect of endovascular treatment (EVT), rapid prehospital identification of large vessel occlusion (LVO) in suspected stroke patients is essential to optimize outcome. Inter-hospital transfers are an important cause of delay of EVT. Prehospital stroke scales have been proposed to select patients with LVO for direct transport to an endovascular-capable intervention centre. We aimed to prospectively validate eight prehospital stroke scales in the field. Methods: In a multi-centre prospective observational cohort study, we included suspected stroke patients transported by ambulance in the Southwest Netherlands. Paramedics assessed items from eight prehospital stroke scales: Rapid Arterial oCclusion Evaluation (RACE), Los Angeles Motor Scale (LAMS), Cincinnati Stroke Triage Assessment Tool (C-STAT), Gaze-Face-Arm-Speech-Time (G-FAST), Prehospital Acute Stroke Severity (PASS), Cincinnati Prehospital Stroke Scale (CPSS), Conveniently-Grasped Field Assessment Stroke Triage (CG-FAST), and the FAST PLUS Test. Patients that presented beyond six hours from symptom onset were excluded. Primary outcome was the clinical diagnosis of ischaemic stroke with a proximal intracranial LVO in the anterior circulation (aLVO) on CT-angiography. Prehospital stroke scale performance was expressed as the area under the receiver operating characteristic curve (AUC) and was compared with National Institute of Health Stroke Scale (NIHSS) scores assessed by physicians at the emergency department. Findings: We included 1039 patients, of which 121 patients (12%) were diagnosed with aLVO. AUCs for the prehospital stroke scales ranged from 0·69 (FAST PLUS) to 0·82 (RACE). The performance of RACE was not significantly different from G-FAST (AUC=0·80, p=0·14) and CG-FAST (AUC=0·80, p=0·09), but was significantly different from the other scales (p-values<0·05). The NIHSS performed somewhat better (AUC 0·86, p-values<0·05). Interpretation: Prehospital stroke scales detect aLVO with good accuracy and approach the performance of the physician-assessed NIHSS. RACE is the best performing prehospital stroke scale, but does not differ significantly from G-FAST and CG-FAST. Trial Registration: This study was registered at the Netherlands Trial Register (www.trialregister.nl), NL7387 Funding: BeterKeten collaboration and Theia Foundation (Zilveren Kruis) Declaration of Interests: Diederik Dippel and Aad van der Lugt report funding from the Dutch Heart Foundation, Brain Foundation Netherlands, The Netherlands Organisation for Health Research and Development, Health Holland Top Sector Life Sciences & Health, and unrestricted grants from Penumbra Inc., Stryker, Stryker European Operations BV, Medtronic, Thrombolytic Science, LLC and Cerenovus for research, all paid to institution. Pieter Jan van Doormaal reports funding from Stryker, paid to institution and an unrestricted fee from Bayer. All other authors declare no conflict of interest. Ethics Approval Statement: This study was conducted in accordance with the Dutch Agreement on Medical Treatment Act and the European General Data Protection Regulation. The Institutional Review Board of the Erasmus MC University Medical Centre has reviewed the study protocol and confirmed that the Dutch Medical Research Involving Human Subjects Act is not applicable. Because our study met the exceptions of informed consent regulations, the need for informed consent was waived. Patients or their relatives were informed about the study and could withdraw from the study through an opt-out system.

Application of a recombinase polymerase amplification (RPA) assay and pilot field testing for Giardia duodenalis at Lake Albert, Uganda

BackgroundGiardia duodenalis is a gastrointestinal protozoan causing 184 million cases of giardiasis worldwide annually. Detection is by microscopy or coproantigen assays, although sensitivity is often compromised by intermittent shedding of cysts or trophozoites, or operator expertise. Therefore, for enhanced surveillance field-applicable, point-of-care (POC), molecular assays are needed. Our aims were to: (i) optimise the recombinase polymerase amplification (RPA) assay for the isothermal amplification of the G. duodenalis β-giardin gene from trophozoites and cysts, using published primer and probes; and (ii) perform a pilot field validation of RPA at a field station in a resource-poor setting, on DNA extracted from stool samples from schoolchildren in villages around Lake Albert, Uganda. Results were compared to an established laboratory small subunit ribosomal RNA (SSU rDNA) qPCR assay with additional testing using a qPCR targeting the triose phosphate isomerase (tpi) DNA regions that can distinguish G. duodenalis of two different assemblages (A and B), which are human-specific.ResultsInitial optimisation resulted in the successful amplification of predicted RPA products from G. duodenalis-purified gDNA, producing a double-labelled amplicon detected using lateral flow strips. In the field setting, of 129 stool samples, 49 (37.9%) were positive using the Giardia/Cryptosporidium QuikChek coproantigen test; however, the RPA assay when conducted in the field was positive for a single stool sample. Subsequent molecular screening in the laboratory on a subset (n = 73) of the samples demonstrated better results with 21 (28.8%) RPA positive. The SSU rDNA qPCR assay resulted in 30/129 (23.3%) positive samples; 18 out of 73 (24.7%) were assemblage typed (9 assemblage A; 5 assemblage B; and 4 mixed A+B). Compared with the SSU rDNA qPCR, QuikChek was more sensitive than RPA (85.7 vs 61.9%), but with similar specificities (80.8 vs 84.6%). In comparison to QuikChek, RPA had 46.4% sensitivity and 82.2% specificity.ConclusionsTo the best of our knowledge, this is the first in-field and comparative laboratory validation of RPA for giardiasis in low resource settings. Further refinement and technology transfer, specifically in relation to stool sample preparation, will be needed to implement this assay in the field, which could assist better detection of asymptomatic Giardia infections.

A biological control model to manage the vector and the infection of Xylella fastidiosa on olive trees.

Xylella fastidiosa pauca ST53 is the bacterium responsible for the Olive Quick Decline Syndrome that has killed millions of olive trees in Southern Italy. A recent work demonstrates that a rational integration of vector and transmission control measures, into a strategy based on chemical and physical control means, can manage Xylella fastidiosa invasion and impact below an acceptable economic threshold. In the present study, we propose a biological alternative to the chemical control action, which involves the predetermined use of an available natural enemy of Philaenus spumarius, i.e., Zelus renardii, for adult vector population and infection biocontrol. The paper combines two different approaches: a laboratory experiment to test the predation dynamics of Zelus renardii on Philaenus spumarius and its attitude as candidate for an inundation strategy; a simulated experiment of inundation, to preliminary test the efficacy of such strategy, before eventually proceeding to an in-field experimentation. With this double-fold approach we show that an inundation strategy with Zelus renardii has the potential to furnish an efficient and “green” solution to Xylella fastidiosa invasion, with a reduction of the pathogen incidence below 10%. The biocontrol model presented here could be promising for containing the impact and spread of Xylella fastidiosa, after an in-field validation of the inundation technique. Saving the fruit orchard, the production and the industry in susceptible areas could thus become an attainable goal, within comfortable parameters for sustainability, environmental safety, and effective plant health protection in organic orchard management.

The greenBag, the New Solution in Waste Separation

The greenBag is an innovative households’ Used Cooking Oil (UCO) disposal solution aiming to allow the collection of this feedstock interesting European but also Chinese and US market. The possibility to collect UCO produced by households represents the possibilities to increase the amount of biodiesel, respecting the ILUC directive, of the 60%. So far, there are no concrete solutions able to properly respond to this need, due to their huge prizes and due to the low performances, they provide. greenBag is a solution coming from an intensive research activity completed by an infield validation. It has been designed to reply to all the requirements coming from families and from the waste management companies, the two actors involved in UCO disposal. Indeed, two different types of users in general, and in particular the UCO collection, characterize waste collection solutions: families - that want simple solutions, easy to use and able to reward them; waste collection companies - that want cheap solutions, able to trace waste disposals and able to assure them a high quality of wastes. The currently available market solutions are all focused on waste companies and the current innovative ideas designed by Universities and Startups focus their attention only on one of the two involved actors. greenBag is currently the sole solution that aims to satisfy both actors, exploiting the disposal traceability not only to know how many waste people produces but also to quantify their efforts and making them aware about the overall disposal process.

A Movement-Tremors Recorder for Patients of Neurodegenerative Diseases

Neurodegenerative diseases such as Alzheimer, Parkinson, motor neuron, and Chorea affect millions of people today. Their effect on the central nervous system causes the loss of brain functions as well as motor disturbances and sometimes cognitive deficits. In such a scenario, the monitoring and evaluation of early symptoms are mandatory for the improvement of the patient’s quality of life. Here, the authors describe the development, the laboratory calibration, and the “in-field validation” under the medical supervision of a movement tremors recorder for subjects affected by neurodegenerative diseases. The developed device is based on an array of four accelerometers connected to an embedded development board. This system is able to monitor tremor/movement, accidental falls, and, moreover, it can track the Alzheimer subjects’ geographical position. A remote supervisor can collect data from the system through Bluetooth, Wi-Fi, or GSM connections. A data compression algorithm was developed directly on board in order to increase the efficiency of data transmission and reduce power consumptions.

Abstract TMP64: In-Field Paramedic Validation of the Ambulance Clinical Triage for Acute Stroke Treatment (ACT-FAST) Algorithm for Endovascular Thrombectomy

Background: Clinical triage for endovascular thrombectomy (EVT) is the most easily deployable solution to reduce unequal geographical access to comprehensive stroke centers, but current tools have limited prehospital validation. We present results of the ongoing paramedic validation study of Ambulance Clinical Triage For Acute Stroke Treatment (ACT-FAST), a published algorithmic severity-based triage tool utilizing only 2 examination steps designed for specificity and practicality. Methods: From July 2017, Ambulance Victoria paramedics assessed ACT-FAST (arm drift followed by speech if right arm weak, or shoulder tap for inattention if left arm weak plus screening eligibility questions) in suspected stroke patients pre-hospital in Melbourne, Australia, and in the Royal Melbourne Hospital Emergency Department. Algorithm results were validated against in-hospital CT imaging. Results: Data were available from n=196 assessments (ED n=76, pre-hospital n=120). Figure 1 shows correlation with CT imaging. Overall, ACT-FAST had 92% sensitivity for ICA/M1 occlusions with NIHSS≥6 (AHA Class 1 indication for EVT). Specificity purely for large vessel occlusion was 83% (positive predictive value 57%). Only a small proportion of distal occlusions (6/46, 13%) or patients with normal imaging (4/67, 6%) were falsely identified. When considering all patients requiring comprehensive stroke center care including neurosurgery (large vessel occlusion, hemorrhage and tumor) generated a positive predictive value for ACT-FAST of 83.3%. Discussion: Current results of the real-world ACT-FAST paramedic field validation study show high accuracy for clinical recognition of patients likely to require EVT or comprehensive stroke center care. The overall benefits of expedited thrombectomy for the majority of patients with large vessel occlusion is likely to outweigh the theoretical harms of delayed thrombolysis for a small minority of patients not requiring EVT.

Design, Application and Infield Validation of a Pre-Hospital Emergent Large Vessel Occlusion Screening Tool: Ventura Emergent Large Vessel Occlusion Score

Background: The outcome of endovascular treatment for emergent large vessel occlusion (ELVO) is dependent on timely recanalization. To identify ELVO in the field, we present a simplified score, which has been applied and validated in the field by emergency medical services (EMS). Methods and Analysis: Ventura ELVO Scale (VES) comprise of 4 components: Eye Deviation, Aphasia, Neglect, and Obtundation with score range 0-4. The score of greater than or equal to 1 will be considered as ELVO positive. A positive VES along with positive Cincinnati scale prompts ELVO activation. EMS then notify to neurointervention protocol at the receiving stroke center. The performance of VES was evaluated retrospectively. For statistical analysis, SAS version 9.4 was used and Fisher's modelling was used for the comparative analysis. Results: Total 184 patients were included in the final analysis, 62 (33.7%) patients were called VES positive from the field. Out of 62, 36 (58%) patients had ELVO. The mean NIHSS on arrival was 16 in VES positive and 5 in VES negative patients. VES was 94.7% sensitive and 82.4% specific while the PPV and NPV of VES were 58.1% and 98.4%, respectively. It showed 84.9% accuracy. Conclusions: VES is an effective and simplified prehospital screening tool for detection of ELVO in the field. Its implementation can beat the target door to groin time to improve outcomes and in future it can be used for rerouting of ELVO patients to comprehensive stroke center.