Non-laboratory Settings Research Articles

Grounding applied animal behavior practices in the experimental analysis of behavior.

Some of the earliest applications outside the laboratory of principles derived from the experimental analysis of behavior (EAB), such as the pioneering work of Keller and Marian Breland, involved animals. This translational tradition continues to the present as EAB-related behavior principles are applied with increasing frequency to behavior management and training practices with animals in nonlaboratory settings. Such translations, and those populations to which they are applied, benefit from a rigorous experimental analysis of practices that are promulgated in popular outlets. These translations both affirm the generality of those principles and serve as goads for laboratory and field research that can further articulate extant principles, develop new ones, and refine methods of application and assessment. This review considered several areas of basic EAB research and contemporary applied animal behavior (AAB) practices in relation to one another: (1) response establishment and maintenance, (2) response reduction and elimination, (3) chaining and conditioned reinforcement, and (4) discriminative stimulus control. Within each topic, a selection of processes and procedures in both EAB and AAB work were reviewed in relation to one another.

A Lightweight Framework for Perception Analysis Based on Multimodal Cognition-Aware Computing.

The VUCA environment challenged neuropsychological research conducted in conventional laboratories. Researchers expected to perform complex multimodal testing tasks in natural, open, and non-laboratory settings. However, for most neuropsychological scientists, the independent construction of a multimodal laboratory in a VUCA environment, such as a construction site, was a significant and comprehensive technological challenge. This study presents a generalized lightweight framework for perception analysis based on multimodal cognition-aware computing, which provided practical updated strategies and technological guidelines for neuromanagement and automation. A real-life test experiment on a construction site was provided to illustrate the feasibility and superiority of the method. The study aimed to fill a technology gap in the application of multimodal physiological and neuropsychological techniques in an open VUCA environment. Meanwhile, it enabled the researchers to improve their systematic technological capabilities and reduce the threshold and trial-and-error costs of experiments to conform to the new trend of VUCA.

High Sensitivity, Rapid Detection of Virus in High Traffic Environments.

The global pandemic caused by the SARS-CoV-2 virus has underscored the need for rapid, simple, scalable, and high-throughput multiplex diagnostics in non-laboratory settings. Here we demonstrate a multiplex reverse-transcription loop-mediated isothermal amplification (RT-LAMP) coupled with a gold nanoparticle-based lateral flow immunoassay (LFIA) capable of detecting up to three unique viral gene targets in 15 min. RT-LAMP primers associated with three separate gene targets from the SARS-CoV-2 virus (Orf1ab, Envelope, and Nucleocapsid) were added to a one-pot mix. A colorimetric change from red to yellow occurs in the presence of a positive sample. Positive samples are run through a LFIA to achieve specificity on a multiplex three-test line paper assay. Positive results are indicated by a characteristic crimson line. The device is almost fully automated and is deployable in any community setting with a power source.

Bio-SCAN: A CRISPR/dCas9-Based Lateral Flow Assay for Rapid, Specific, and Sensitive Detection of SARS-CoV-2.

Simple, rapid, specific, and sensitive point-of-care detection methods are needed to contain the spread of SARS-CoV-2. CRISPR/Cas9-based lateral flow assays are emerging as a powerful alternative for COVID-19 diagnostics. Here, we developed Bio-SCAN (biotin-coupled specific CRISPR-based assay for nucleic acid detection) as an accurate pathogen detection platform that requires no sophisticated equipment or technical expertise. Bio-SCAN detects the SARS-CoV-2 genome in less than 1 h from sample collection to result. In the first step, the target nucleic acid sequence is isothermally amplified in 15 min via recombinase polymerase amplification before being precisely detected by biotin-labeled nuclease-dead SpCas9 (dCas9) on commercially available lateral flow strips. The resulting readout is visible to the naked eye. Compared to other CRISPR-Cas-based pathogen detection assays, Bio-SCAN requires no additional reporters, probes, enhancers, reagents, or sophisticated devices to interpret the results. Bio-SCAN is highly sensitive and successfully detected a clinically relevant level (4 copies/μL) of synthetic SARS-CoV-2 RNA genome. Similarly, Bio-SCAN showed 100% negative and 96% positive predictive agreement with RT-qPCR results when using clinical samples (86 nasopharyngeal swab samples). Furthermore, incorporating variant-specific sgRNAs in the detection reaction allowed Bio-SCAN to efficiently distinguish between the α, β, and δ SARS-CoV-2 variants. Also, our results confirmed that the Bio-SCAN reagents have a long shelf life and can be assembled locally in nonlaboratory and limited-resource settings. Furthermore, the Bio-SCAN platform is compatible with the nucleic acid quick extraction protocol. Our results highlight the potential of Bio-SCAN as a promising point-of-care diagnostic platform that can facilitate low-cost mass screening for SARS-CoV-2.

Temporal convolutional networks predict dynamic oxygen uptake response from wearable sensors across exercise intensities

Oxygen consumption (dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2}) provides established clinical and physiological indicators of cardiorespiratory function and exercise capacity. However, dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2} monitoring is largely limited to specialized laboratory settings, making its widespread monitoring elusive. Here we investigate temporal prediction of dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2} from wearable sensors during cycle ergometer exercise using a temporal convolutional network (TCN). Cardiorespiratory signals were acquired from a smart shirt with integrated textile sensors alongside ground-truth dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2} from a metabolic system on 22 young healthy adults. Participants performed one ramp-incremental and three pseudorandom binary sequence exercise protocols to assess a range of dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2} dynamics. A TCN model was developed using causal convolutions across an effective history length to model the time-dependent nature of dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2}. Optimal history length was determined through minimum validation loss across hyperparameter values. The best performing model encoded 218 s history length (TCN-VO2 A), with 187, 97, and 76 s yielding <3% deviation from the optimal validation loss. TCN-VO2 A showed strong prediction accuracy (mean, 95% CI) across all exercise intensities (−22 ml min−1, [−262, 218]), spanning transitions from low–moderate (−23 ml min−1, [−250, 204]), low–high (14 ml min−1, [−252, 280]), ventilatory threshold–high (−49 ml min−1, [−274, 176]), and maximal (−32 ml min−1, [−261, 197]) exercise. Second-by-second classification of physical activity across 16,090 s of predicted dot{,{{mbox{V}}}}{{{mbox{O}}}}_{2} was able to discern between vigorous, moderate, and light activity with high accuracy (94.1%). This system enables quantitative aerobic activity monitoring in non-laboratory settings, when combined with tidal volume and heart rate reserve calibration, across a range of exercise intensities using wearable sensors for monitoring exercise prescription adherence and personal fitness.

Computational Measurement of Motor Imitation and Imitative Learning Differences in Autism Spectrum Disorder: Computational Motor Imitation Measurement in ASD.

Motor imitation is a critical developmental skill area that has been strongly and specifically linked to autism spectrum disorder (ASD). However, methodological variability across studies has precluded a clear understanding of the extent and impact of imitation differences in ASD, underscoring a need for more automated, granular measurement approaches that offer greater precision and consistency. In this paper, we investigate the utility of a novel motor imitation measurement approach for accurately differentiating between youth with ASD and typically developing (TD) youth. Findings indicate that youth with ASD imitate body movements significantly differently from TD youth upon repeated administration of a brief, simple task, and that a classifier based on body coordination features derived from this task can differentiate between autistic and TD youth with 82% accuracy. Our method illustrates that group differences are driven not only by interpersonal coordination with the imitated video stimulus, but also by intrapersonal coordination. Comparison of 2D and 3D tracking shows that both approaches achieve the same classification accuracy of 82%, which is highly promising with regard to scalability for larger samples and a range of non-laboratory settings. This work adds to a rapidly growing literature highlighting the promise of computational behavior analysis for detecting and characterizing motor differences in ASD and identifying potential motor biomarkers.

The impact of standardized footwear on load and load symmetry

BackgroundThe inability to standardize footwear is a potential issue when measuring landing kinetics in non-laboratory settings. This study determined the impact of not standardizing footwear on load and load symmetry during landing. A secondary purpose of this study was to introduce the Load Analysis Program, an open-source MATLAB® user-interface for computing kinetic and kinetic symmetry from data collected using loadsol® sensors. MethodsForty uninjured participants completed bilateral and unilateral landing tasks in their own preferred athletic footwear and in laboratory-standardized footwear. Peak impact force, impulse, and a limb symmetry index of both kinetic outcomes were computed using loadsol® sensors (200 Hz) for both footwear conditions, and compared between footwear conditions using intraclass correlation coefficients and Bland-Altman plots. FindingsThe agreement between the preferred and standardized conditions was good to excellent for peak impact force, peak impact force limb symmetry index, and impulse limb symmetry index during the bilateral task (intraclass correlation coefficient = 0.870–0.951). The agreement was moderate to poor for unilateral limb symmetry index measures (intraclass correlation coefficient = 0.399–0.516). During the preferred footwear condition, impulse was greater for the left limb during bilateral landing, and peak impact force during unilateral landing on the right limb was decreased, when compared to the standardized footwear condition (p < 0.05). InterpretationThese results suggest that while not standardizing footwear can alter the results of certain load metrics, laboratory-relevant landing mechanics information can be obtained with participants wearing their own footwear.

Use of Portable Capillary Liquid Chromatography for Common Educational Demonstrations Involving Separations

High-performance liquid chromatography is one of the primary techniques covered in the undergraduate analytical chemistry curriculum. This technology report describes the use of a portable capillary-scale instrument that can provide similar performance to a benchtop instrument but generates less solvent waste and enables operation in nonlaboratory settings. Comparisons between the two instrument types were made for single-standard calibration analysis of caffeine in diet soda and aspirin content in over-the-counter tablets, with relative percent differences between the standards and samples under 5% for both instrument types and both samples. The capability to use the instrument in lecture and outreach demonstration activities was also explored. Portable instruments can serve similar pedagogical purposes to traditional instruments as well as provide a platform to introduce discussions on green analytical chemistry based on differences in solvent waste generation and power consumption.

Scaling N from 1 to 1,000,000: Application of the Generalized Matching Law to Big Data Contexts.

The generalized matching law (GML) has been used to describe the behavior of individual organisms in operant chambers, artificial environments, and nonlaboratory human settings. Most of these analyses have used a handful of participants to determine how well the GML describes choice in the experimental arrangement or how some experimental manipulation influences estimated matching parameters. Though the GML accounts very well for choice in a variety of contexts, the generality of the GML to all individuals in a population is unknown. That is, no known studies have used the GML to describe the individual behavior of all individuals in a population. This is likely because the data from every individual in the population has not historically been available or because time and computational constraints made population-level analyses prohibitive. In this study, we use open data on baseball pitches to provide an example of how big data methods can be combined with the GML to: (1) scale within-subjects designs to the population level; (2) track individual members of a population over time; (3) easily segment the population into subgroups for further analyses within and between groups; and (4) compare GML fits and estimated parameters to performance. These were accomplished for each of 2,374 individuals in a population using 8,467,473 observations of behavior-environment relationships spanning 11 years. In total, this study is a proof of concept for how behavior analysts can use data-science techniques to extend individual-level quantitative analyses of behavior to the population-level focused on domains of social relevance.

Design and Fabrication of Yttrium Ferrite Garnet-Embedded Graphitic Carbon Nitride: A Sensitive Electrocatalyst for Smartphone-Enabled Point-of-Care Pesticide (Mesotrione) Analysis in Food Samples.

As the use of pesticides in agriculture is increasing at an alarming rate, food contamination by pesticide residues is becoming a huge global problem. It is essential to develop a sensitive and user-friendly sensor device to quantify trace levels of pesticide and herbicide residues in food samples. Herein, we report an electrocatalyst made up of yttrium iron garnet (Y3Fe5O12; YIG) and graphitic carbon nitride (GCN) to attain picomolar-level detection sensitivity for mesotrione (MTO), which is a widely used herbicide in agriculture. First, YIG was prepared by a hydrothermal route; then, it was loaded on GCN sheets via a calcination method. The surface structures, composition, crystallinity, and interfacial and electrocatalytic properties of the YIG and YIG/GCN were analyzed. As the YIG/GCN displayed better surface and catalytic properties than YIG, YIG/GCN was modified on a screen-printed carbon electrode to fabricate a sensor for MTO. The YIG/GCN-modified electrode displayed a detection limit of 950 pM for MTO. The method was demonstrated in (spiked) fruits and vegetables. Then, the modified electrode was integrated with a miniaturized potentiostat called KAUSTat, which can be operated wirelessly by a smartphone. A first smartphone-based portable sensor was demonstrated for MTO that is suitable for use in nonlaboratory settings.

Landing biomechanics deficits in anterior cruciate ligament reconstruction patients can be assessed in a non-laboratory setting.

Landing biomechanics provide important information pertaining to second anterior cruciate ligament (ACL) injury risk in patients following ACL reconstruction (ACLR). While traditional motion analysis technologies are often impractical for use in non-laboratory settings, methods to assess landing biomechanics which are inexpensive, portable, and user-friendly have recently been developed and validated. The purpose of this study was to compare landing kinematics and kinetics between ACLR patients and uninjured controls in a non-laboratory setting. Sixteen ACLR patients (7 male/9 female, 6-12 months post-ACLR) and 16 gender-matched controls completed seven bilateral drop vertical jumps and seven unilateral drop landings on each limb. Plantar force was measured bilaterally using force sensing insoles and frontal and sagittal-plane knee kinematics were measured using two tablets, six reflective markers, and automated point tracking software. Plantar force impulse normalized symmetry index (NSI) and knee frontal plane projection angle (FPPA) range of motion were computed during bilateral landing, and knee flexion range of motion NSI was computed during unilateral landing and compared between groups using independent samples t tests. ACLR patients had larger NSIs (reflecting less symmetry) for plantar force impulse during bilateral landing (p < 0.001) and knee flexion range of motion during unilateral landing (p = 0.004). No between-group differences were observed for knee FPPA range of motion (p = 0.111). This study is an important step towards assessing landing biomechanics in non-research settings with the goal of providing quantitative injury risk metrics in a clinical setting that can be used for return to sport decision making.

Challenges and potential solutions for nanosensors intended for use with foods.

Nanotechnology-adapted detection technologies could improve the safety and quality of foods, provide new methods to combat fraud and be useful tools in our arsenal against bioterrorism. Yet despite hundreds of published studies on nanosensors each year targeted to the food and agriculture space, there are few nanosensors on the market in this area and almost no nanotechnology-enabled methods employed by public health agencies for food analysis. This Review shows that the field is currently being held back by technical, regulatory, political, legal, economic, environmental health and safety, and ethical challenges. We explore these challenges in detail and provide suggestions about how they may be surmounted. Strategies that may have particular effectiveness include improving funding opportunities and publication venues for nanosensor validation, social science and patent landscape studies; prioritizing research and development of nanosensors that are specifically designed for rapid analysis in non-laboratory settings; and incorporating platform cost and adaptability into early design decisions.

A new method for assessing landing kinematics in non-laboratory settings

Objectives1) Determine the concurrent validity of using automated 2D video analysis relative to 3D motion capture for assessing frontal and sagittal-plane knee kinematics during landing, 2) compare the accuracy of visually estimating joint center locations (2D Manual) with computing joint center locations using anatomical markers (2D Automatic), and 3) compare landing kinematics between a controlled laboratory setting and a non-laboratory setting. DesignValidity/repeatability study. SettingsBiomechanics research laboratory and non-laboratory athletic facility. ParticipantsThirty uninjured recreational athletes. Main Outcome MeasuresPeak knee flexion, knee flexion range of motion, peak knee frontal plane projection angle, and knee frontal plane projection angle range of motion during bilateral and unilateral landing were measured simultaneously in 3D using motion capture and in 2D using two low-cost video cameras during the first study session (biomechanics research laboratory), and in 2D only during the second study session (non-laboratory athletic facility). ResultsThere was good to excellent agreement between 3D motion capture and both 2D Manual (ICC = 0.86–0.99) and 2D Automatic (ICC = 0.89–0.99) video analysis methods. There was good to excellent agreement between data collected in a laboratory and non-laboratory setting (ICC = 0.75–0.95). ConclusionThe methods introduced in this study are inexpensive, reliable, and feasible for use in non-laboratory settings.

Quantitative E. coli Enzyme Detection in Reporter Hydrogel-Coated Paper Using a Smartphone Camera.

There is a growing demand for rapid and sensitive detection approaches for pathogenic bacteria that can be applied by non-specialists in non-laboratory field settings. Here, the detection of the typical E. coli enzyme β-glucuronidase using a chitosan-based sensing hydrogel-coated paper sensor and the detailed analysis of the reaction kinetics, as detected by a smartphone camera, is reported. The chromogenic reporter unit affords an intense blue color in a two-step reaction, which was analyzed using a modified Michaelis–Menten approach. This generalizable approach can be used to determine the limit of detection and comprises an invaluable tool to characterize the performance of lab-in-a-phone type approaches. For the particular system analyzed, the ratio of reaction rate and equilibrium constants of the enzyme–substrate complex are 0.3 and 0.9 pM−1h−1 for β-glucuronidase in phosphate buffered saline and lysogeny broth, respectively. The minimal degree of substrate conversion for detection of the indigo pigment formed during the reaction is 0.15, while the minimal time required for detection in this particular system is ~2 h at an enzyme concentration of 100 nM. Therefore, this approach is applicable for quantitative lab-in-a-phone based point of care detection systems that are based on enzymatic substrate conversion via bacterial enzymes.

The potential of diagnostic point-of-care tests (POCTs) for infectious and zoonotic animal diseases in developing countries: Technical, regulatory and sociocultural considerations.

Remote and rural communities in low‐ and middle‐income countries (LMICs) are disproportionately affected by infectious animal diseases due to their close contact with livestock and limited access to animal health personnel). However, animal disease surveillance and diagnosis in LMICs is often challenging, and turnaround times between sample submission and diagnosis can take days to weeks. This diagnostic gap and subsequent disease under‐reporting can allow emerging and transboundary animal pathogens to spread, with potentially serious and far‐reaching consequences. Point‐of‐care tests (POCTs), which allow for rapid diagnosis of infectious diseases in non‐laboratory settings, have the potential to significantly disrupt traditional animal health surveillance paradigms in LMICs. This literature review sought to identify POCTs currently available for diagnosing infectious animal diseases and to determine facilitators and barriers to their use and uptake in LMICs. Results indicated that some veterinary POCTs have been used for field‐based animal disease diagnosis in LMICs with good results. However, many POCTs target a small number of key agricultural and zoonotic animal diseases, while few exist for other important animal diseases. POCT evaluation is rarely taken beyond the laboratory and into the field where they are predicted to have the greatest impact, and where conditions can greatly affect test performance. A lack of mandated test validation regulations for veterinary POCTs has allowed tests of varying quality to enter the market, presenting challenges for potential customers. The use of substandard, improperly validated or unsuitable POCTs in LMICs can greatly undermine their true potential and can have far‐reaching negative impacts on disease control. To successfully implement novel rapid diagnostic pathways for animal disease in LMICs, technical, regulatory, socio‐political and economic challenges must be overcome, and further research is urgently needed before the potential of animal disease POCTs can be fully realized.

Evaluating Medical Devices Remotely: Current Methods and Potential Innovations.

ObjectiveWe present examples of laboratory and remote studies, with a focus on studies appropriate for medical device design and evaluation. From this review and description of extant options for remote testing, we provide methods and tools to achieve research goals remotely.BackgroundThe FDA mandates human factors evaluation of medical devices. Studies show similarities and differences in results collected in laboratories compared to data collected remotely in non-laboratory settings. Remote studies show promise, though many of these are behavioral studies related to cognitive or experimental psychology. Remote usability studies are rare but increasing, as technologies allow for synchronous and asynchronous data collection.MethodWe reviewed methods of remote evaluation of medical devices, from testing labels and instruction to usability testing and simulated use. Each method was coded for the attributes (e.g., supported media) that need consideration in usability studies.ResultsWe present examples of how published usability studies of medical devices could be moved to remote data collection. We also present novel systems for creating such tests, such as the use of 3D printed or virtual prototypes. Finally, we advise on targeted participant recruitment.ConclusionRemote testing will bring opportunities and challenges to the field of medical device testing. Current methods are adequate for most purposes, excepting the validation of Class III devices.ApplicationThe tools we provide enable the remote evaluation of medical devices. Evaluations have specific research goals, and our framework of attributes helps to select or combine tools for valid testing of medical devices.

Using Magneto-Inertial Measurement Units to Pervasively Measure Hip Joint Motion during Sports

The use of wireless sensors to measure motion in non-laboratory settings continues to grow in popularity. Thus far, most validated systems have been applied to measurements in controlled settings and/or for prescribed motions. The aim of this study was to characterize adolescent hip joint motion of elite-level athletes (soccer players) during practice and recreationally active peers (controls) in after-school activities using a magneto-inertial measurement unit (MIMU) system. Opal wireless sensors (APDM Inc., Portland OR, USA) were placed at the sacrum and laterally on each thigh (three sensors total). Hip joint motion was characterized by hip acceleration and hip orientation for one hour of activity on a sports field. Our methods and analysis techniques can be applied to other joints and activities. We also provide recommendations in order to guide future work using MIMUs to pervasively assess joint motions of clinical relevance.

Validity of Using Automated Two-Dimensional Video Analysis to Measure Continuous Sagittal Plane Running Kinematics.

Two-dimensional video analysis is commonly used to assess kinematics when three-dimensional motion capture is unavailable. However, videos are often assessed using manual digitization, which limits the ability to extract outcomes that require continuous data. Here, we introduced a method to collect continuous kinematic data in 2D using an inexpensive camera and an open-source automated marker tracking program. We tested the validity of this method by comparing 2D video analysis to 3D motion capture for measuring sagittal-plane running kinematics. Twenty uninjured participants ran on a treadmill for 1-min while lower extremity kinematics were collected simultaneously in 3D using a motion capture system and in 2D using a single digital camera, both at 120Hz. Knee, ankle, and foot angle at contact, peak knee flexion, knee flexion excursion, and knee-ankle flexion vector coding variability were computed using both the 3D and 2D kinematic data, and were compared using intraclass correlation coefficients and Bland-Altman plots. The agreement between collection methods was excellent for foot angle at contact and knee flexion excursion, good for ankle and knee angle at contact and knee-ankle vector coding variability, and moderate for peak knee flexion. However, Bland-Altman plots revealed significant differences between the 2D and 3D collection methods, which varied across study participants. These low-cost methods could be useful for collecting continuous sagittal plane running kinematics in non-laboratory settings.

The use of Broca index to assess cut- off points for overweight in adults: A short review.

The Broca formula was developed in 1871 by Pierre Paul Broca (a French Army Doctor) to help establish ideal body weight or normal body weight. Initially, the Broca Index (BI) was used to work out the normal weight but was later expanded to ideal Body Weight. Ideal Body weight (kg) = [Height (cm)-100]. The common methods used to explore the levels of adiposity include body mass index (BMI), waist circumference, skinfolds, bioelectrical impedance analysis, dual energy x-ray absorptiometry (DEXA), computerized tomography (CT) and magnetic resonance imaging (MRI). Even though there have been several anthropometric measurements discoveries to assess obesity, BMI is still widely used in many clinic centers around the world. It remains simple and relatively inexpensive to measure and easily obtainable in non-laboratory settings. In this review, we will summarize the common methods used to measure body fat and their limitations. Second, we will show the correlation that may exist between Broca Index and BMI cutoffs. Last, we will underline some potential clinical usefulness that may present Broca index in assessing body fat.

Optimization of ultraviolet Raman spectroscopy for trace explosive checkpoint screening.

Raman spectroscopy has long been considered a gold standard for optically based chemical identification, but has not been adopted in non-laboratory operational settings due to limited sensitivity and slow acquisition times. Ultraviolet (UV) Raman spectroscopy has the potential to address these challenges through the reduction of fluorescence from background materials and increased Raman scattering due to the shorter wavelength (relative to visible or near-infrared excitation) and resonant enhancement effects. However, the benefits of UV Raman must be evaluated against specific operational situations: the actual realized fluorescence reduction and Raman enhancement depend on the specific target materials, target morphology, and operational constraints. In this paper, the wavelength trade-space in UV Raman spectroscopy is evaluated for one specific application: checkpoint screening for trace explosive residues. The optimal UV wavelength is evaluated at 244, 266, and 355nm for realistic trace explosive and explosive-related compound (ERC) residues on common checkpoint materials: we perform semi-empirical analysis that includes the UV penetration depth of common explosive and ERCs, realistic explosive and ERC residue particle sizes, and the fluorescence signal of common checkpoint materials. We find that while generally lower UV wavelength provides superior performance, the benefits may be significantly reduced depending on the specific explosive and substrate. Further, logistical requirements (size, weight, power, and cost) likely limit the adoption of optimal wavelengths. Graphical abstract.