Assessment of the USDA Biomass Harvest Trap (USDA-BHT) device as an insect harvest and mosquito surveillance tool.

Insects are a promising source of high-quality protein, and the insect farming industry will lead to higher sustainability when it overcomes scaling up, cost effectiveness, and automation. In contrast to insect farming (raising and breeding insects as livestock), wild insect harvesting (collecting agricultural insect pests), may constitute a simple sustainable animal protein supplementation strategy. For wild harvest to be successful sufficient insect biomass needs to be collected while simultaneously avoiding the collection of nontarget insects. We assessed the performance of the USDA Biomass Harvest Trap (USDA-BHT) device to collect flying insect biomass and as a mosquito surveillance tool. The USDA-BHT device was compared to other suction traps commonly used for mosquito surveillance (Centers for Disease Control and Prevention (CDC) light traps, Encephalitis virus surveillance traps, and Biogents Sentinel traps). The insect biomass harvested in the USDA-BHT was statistically higher than the one harvested in the other traps, however the mosquito collections between traps were not statistically significantly different. The USDA-BHT collected some beneficial insects, although it was observed that their collection was minimized at night. These findings coupled with the fact that sorting time to separate the mosquitoes from the other collected insects was significantly longer for the USDA-BHT, indicate that the use of this device for insect biomass collection conflicts with its use as an efficient mosquito surveillance tool. Nevertheless, the device efficiently collected insect biomass, and thus can be used to generate an alternative protein source for animal feed.

Harvesting insect pests for animal feed: potential to capture an unexploited resource.

The demand for animal protein grows as the human population increases. Technological and genetic advances in traditional animal agriculture will not produce enough protein to meet future needs without significant innovations such as the use of insects as protein sources. Insect farming is growing insects, whereas insect harvesting is collecting insects from their natural habitats to produce high-quality protein for animal feed or human food. Intensive agricultural environments produce tremendous quantities of pestiferous insects and with the right harvest technologies these insects can be used as a protein supplement in traditional animal daily rations. An avenue to exploit these insects is to use traps such as the United States Department of Agriculture-Biomass Harvest Trap (USDA-BHT) to efficiently attract, harvest, and store insects from naturally abundant agricultural settings. The modular design allows for a low cost, easy to build and fix device that is user friendly and has customizable attractants to target various pest species. Although insect harvesting faces substantial challenges, including insect biomass quantity, seasonal abundance and preservation, food safety, and economic and nutritional evaluation, the potential for utilizing these pests for protein shows tremendous promise. In this forum, insect harvesting is discussed, including its potential, limitations, challenges, and research needs. In addition, the use of a mass trapping device is discussed as a tool to increase the biomass of insects collected from the environment.

Conceptualization, design, and construction of a novel insect mass trapping device: the USDA Biomass Harvest Trap (USDA-BHT).

The use of insects as animal feed has the potential to be a green revolution for animal agriculture as insects are a rich source of high-quality protein. Insect farming must overcome challenges such as product affordability and scalability before it can be widely incorporated as animal feed. An alternative is to harvest insect pests from the environment using mass trapping devices and use them as animal feed. For example, intensive agricultural environments generate large quantities of pestiferous insects and with the right harvest technologies, these insects can be used as a protein supplement in traditional animal daily rations. Most insect trapping devices are limited by the biomass they can collect. In that context, and with the goal of using wild collected insects as animal feed, the United States Department of Agriculture-Biomass Harvest Trap (USDA-BHT) was designed and built. The USDA-BHT is a valuable mass trapping device developed to efficiently attract, harvest, and store flying insects from naturally abundant agricultural settings. The trap offers a modular design with adjustable capabilities, and it is an inexpensive device that can easily be built with commonly available parts and tools. The USDA-BHT is also user-friendly and has customizable attractants to target various pest species.

Elucidating the Gas-Phase Behavior of Nitazene Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry.

2-Benzylbenzimidazoles, or "nitazenes", are a class of novel synthetic opioids (NSOs) that are increasingly being detected alongside fentanyl analogs and other opioids in drug overdose cases. Nitazenes can be 20× more potent than fentanyl but are not routinely tested for during postmortem or clinical toxicology drug screens; thus, their prevalence in drug overdose cases may be under-reported. Traditional analytical workflows utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) often require additional confirmation with authentic reference standards to identify a novel nitazene. However, additional analytical measurements with ion mobility spectrometry (IMS) may provide a path toward reference-free identification, which would greatly accelerate NSO identification rates in toxicology laboratories. Presented here are the first IMS and collision cross section (CCS) measurements on a set of fourteen nitazene analogs using a structures for lossless ion manipulations (SLIM)-orbitrap MS. All nitazenes exhibited two high intensity baseline-separated IMS distributions, which fentanyls and other drug and druglike compounds also exhibit. Incorporating water into the electrospray ionization (ESI) solution caused the intensities of the higher mobility IMS distributions to increase and the intensities of the lower mobility IMS distributions to decrease. Nitazenes lacking a nitro group at the R1 position exhibited the greatest shifts in signal intensities due to water. Furthermore, IMS-MS/MS experiments showed that the higher mobility IMS distributions of all nitazenes possessing a triethylamine group produced fragment ions with m/z 72, 100, and other low intensity fragments while the lower mobility IMS distributions only produced fragment ions with m/z 72 and 100. The IMS, solvent, and fragmentation studies provide experimental evidence that nitazenes potentially exhibit three gas-phase protomers. The cyclic IMS capability of SLIM was also employed to partially resolve four sets of structurally similar nitazene isomers (e.g., protonitazene/isotonitazene, butonitazene/isobutonitazene/secbutonitazene), showcasing the potential of using high-resolution IMS separations in MS-based workflows for reference-free identification of emerging nitazenes and other NSOs.

Identification of Unique Fragmentation Patterns of Fentanyl Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry.

The opioid crisis in the United States is being fueled by the rapid emergence of new fentanyl analogs and precursors that can elude traditional library-based screening methods, which require data from known reference compounds. Since reference compounds are unavailable for new fentanyl analogs, we examined if fentanyls (fentanyl + fentanyl analogs) could be identified in a reference-free manner using a combination of electrospray ionization (ESI), high-resolution ion mobility (IM) spectrometry, high-resolution mass spectrometry (MS), and higher-energy collision-induced dissociation (MS/MS). We analyzed a mixture containing nine fentanyls and W-15 (a structurally similar molecule) and found that the protonated forms of all fentanyls exhibited two baseline-separated IM distributions that produced different MS/MS patterns. Upon fragmentation, both IM distributions of all fentanyls produced two high intensity fragments, resulting from amine site cleavages. The higher mobility distributions of all fentanyls also produced several low intensity fragments, but surprisingly, these same fragments exhibited much greater intensities in the lower mobility distributions. This observation demonstrates that many fragments of fentanyls predominantly originate from one of two different gas-phase structures (suggestive of protomers). Furthermore, increasing the water concentration in the ESI solution increased the intensity of the lower mobility distribution relative to the higher mobility distribution, which further supports that fentanyls exist as two gas-phase protomers. Our observations on the IM and MS/MS properties of fentanyls can be exploited to positively differentiate fentanyls from other compounds without requiring reference libraries and will hopefully assist first responders and law enforcement in combating new and emerging fentanyls.

Assessing the feasibility, safety, and nutritional quality of using wild-caught pest flies in animal feed.

Studies have investigated the potential of using farmed insects in animal feeds; however, little research has been done using wild-caught insects for this purpose. Concerns about inadequate quantities collected, environmental impacts, and the spread of pathogens contribute to the preferred utilization of farmed insects. Nevertheless, by harvesting certain pest species from intensified agricultural operations, producers could provide their animals with affordable and sustainable protein sources while also reducing pest populations. This study explores the possibility of collecting large quantities of pest flies from livestock operations and analyzes the flies' nutritional content, potential pathogen load, and various disinfection methods. Using a newly designed mass collection-trapping device, we collected 5 kg of biomass over 13 wk, primarily house flies, from a poultry facility. While a substantial number of pests were removed from the environment, there was no reduction in the fly population. Short-read sequencing was used to compare the bacterial communities carried by flies from differing source populations, and the bacterial species present in the fly samples varied based on farm type and collection time. Drying and milling the wild-caught flies as well as applying an additional heat treatment significantly reduced the number of culturable bacteria present in or on the flies, though their pathogenicity remains unknown. Importantly, these disinfection methods did not affect the nutritional value of the processed flies. Further research is necessary to fully assess the safety and viability of integrating wild-caught insects into livestock feed; however, these data show promising results in favor of such a system.

Standoff trace explosives vapor detection at meter distances.

Vapor detection is a noncontact sampling method, which is a less invasive means of explosives screening than physical swiping. Explosive vapor detection is a challenge due to the low levels of vapors available for detection. This study demonstrates that the parts-per-quadrillion sensitivity of atmospheric flow tube-mass spectrometry (AFT-MS) combined with a high-volume air sampler enables standoff detection of trace explosives vapor at distances of centimeters to meters. Standoff detection of explosives vapor was possible both upstream and downstream of the vapor source relative to room air currents. RDX vapor from a saturated source was detected at up to 2.5 m. Vapors from RDX residue and nitroglycerin residue were detected at distances up to 0.5 m. The sampling can be optimized by accounting for air movement in the room or environment, which could further extend standoff detection distances. Using AFT-MS with a high-volume sampler could also be effective for standoff vapor detection of drugs and additional chemical threats and could be useful for security screening applications such as at mail facilities, border crossings, and security checkpoints.

Fatal Food: Silver-Coated Grain Particles Display Larvicidal Activity in Culex quinquefasciatus.

Mosquitoes pose a significant risk to millions of people worldwide since they can transmit pathogens. Current methods to control mosquito populations include the use of synthetic pesticides. Nanotechnology may be a solution to develop new mosquito control. However, one barrier to expanding the impact of nanomaterials is the ability to mass-produce the particles. Here, we report a novel hybrid particle synthesis combining micro- and nanoparticles using the coprecipitation technique with the potential for mass production. These particles may have applications as a mosquito larvacide. The particles reported here were designed using a microparticle zein polymer as the core and a nanoparticle silver as the active ingredient. The hybrid NPs reported here targeted a late-stage mosquito larvae and that resulted in a high larval mortality concentration (1.0 ppm, LC90) and suppression of pupal emergence at 0.1 ppm. This research demonstrates the efficacy of a plant-based core with a metal-based AI coating (AgNPs) against larval mosquitoes.

A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis.

High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here, we overcome this limitation by using a dual-gated ion injection approach to couple an 11 m path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS platform. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after the module. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11 m SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140 k), and high-energy collision-induced dissociation (HCD) in ∼25 min over an m/z range of ∼1500 amu. The SLIM-Orbitrap platform was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (RpCCS) of ∼218 and an SLIM peak capacity of ∼156, while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG1+, GRGDS1+, and RpCCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. This new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtained using this system establish the foundation for reference-free identification of unknown ion structures.

Finding Explanations in AI Fusion of Electro-Optical/Passive Radio-Frequency Data.

In the Information Age, the widespread usage of blackbox algorithms makes it difficult to understand how data is used. The practice of sensor fusion to achieve results is widespread, as there are many tools to further improve the robustness and performance of a model. In this study, we demonstrate the utilization of a Long Short-Term Memory (LSTM-CCA) model for the fusion of Passive RF (P-RF) and Electro-Optical (EO) data in order to gain insights into how P-RF data are utilized. The P-RF data are constructed from the in-phase and quadrature component (I/Q) data processed via histograms, and are combined with enhanced EO data via dense optical flow (DOF). The preprocessed data are then used as training data with an LSTM-CCA model in order to achieve object detection and tracking. In order to determine the impact of the different data inputs, a greedy algorithm (explainX.ai) is implemented to determine the weight and impact of the canonical variates provided to the fusion model on a scenario-by-scenario basis. This research introduces an explainable LSTM-CCA framework for P-RF and EO sensor fusion, providing novel insights into the sensor fusion process that can assist in the detection and differentiation of targets and help decision-makers to determine the weights for each input.

Are You Still Using 6-Volt Batteries for Your Insect Traps?

The most prevalent insect sampling and surveillance problem is powering insect traps in the field. Most modern light traps use 6-V power supplies such as the Centers for Disease Control and Prevention (CDC) suction trap. Buck converter modules efficiently reduce 12-V direct current power to 6-V, which permits the use of higher voltage batteries with lower voltage traps, resulting in longer operational duration and reduced labor requirements associated with replacing and recharging batteries in the field. We evaluated several battery configurations of 6- and 12-V lead-acid batteries in various sizes (10-20 ampere-hours) and addressed, in the circuit design, common problems that occur when using the buck converter (such as crossing polarity and excessive battery depletion). The efficacy of each configuration was assessed by measuring the voltage and suction while powering a 6-V CDC light trap. The buck converter permitted the use of cheaper and more commonly available 12-V batteries to run the CDC light traps and resulted in longer effective operation time as measured by air speed.

Vapor detection and vapor pressure measurements of fentanyl and fentanyl hydrochloride salt at ambient temperatures.

There is a need for non-contact, real-time vapor detection of drugs to combat illicit transportation and help curb the opioid epidemic. The low volatility of drugs, like fentanyl, makes room temperature vapor detection of illicit drugs challenging, but feasible by atmospheric flow tube-mass spectrometry (AFT-MS). AFT-MS is a non-contact vapor detection approach capable of ultra-trace detection of drugs, including fentanyl and its analogs at low parts-per-quadrillion (ppqv) levels. The determination of vapor pressure values of fentanyl is necessary to understand potential vapor concentrations that may be available for detection. In this paper, vapor pressures of fentanyl free base and fentanyl hydrochloride salt (a common form of the illicit drug) were measured as a function of temperature at or near ambient conditions using the transpiration (gas saturation) method and AFT-MS. Based on our measurements, the vapor pressure of fentanyl at 25 °C is 9.0 × 10-14 atm (90 ppqv), and the vapor pressure of fentanyl hydrochloride at 25 °C is 1.8 × 10-17 atm (0.018 ppqv). We also demonstrate non-contact, real-time vapor detection of fentanyl. Preconcentration of vapors can further extend the detection capabilities. The collection, desorption, and detection of fentanyl vapors at ambient conditions was demonstrated for sampling times of seconds to an hour resulting in increased signal. AFT-MS is a viable detection method of fentanyl and other drugs for screening of packages and cargo.

Interpretable Passive Multi-Modal Sensor Fusion for Human Identification and Activity Recognition.

Human monitoring applications in indoor environments depend on accurate human identification and activity recognition (HIAR). Single modality sensor systems have shown to be accurate for HIAR, but there are some shortcomings to these systems, such as privacy, intrusion, and costs. To combat these shortcomings for a long-term monitoring solution, an interpretable, passive, multi-modal, sensor fusion system PRF-PIR is proposed in this work. PRF-PIR is composed of one software-defined radio (SDR) device and one novel passive infrared (PIR) sensor system. A recurrent neural network (RNN) is built as the HIAR model for this proposed solution to handle the temporal dependence of passive information captured by both modalities. We validate our proposed PRF-PIR system for a potential human monitoring system through the data collection of eleven activities from twelve human subjects in an academic office environment. From our data collection, the efficacy of the sensor fusion system is proven via an accuracy of 0.9866 for human identification and an accuracy of 0.9623 for activity recognition. The results of the system are supported with explainable artificial intelligence (XAI) methodologies to serve as a validation for sensor fusion over the deployment of single sensor solutions. PRF-PIR provides a passive, non-intrusive, and highly accurate system that allows for robustness in uncertain, highly similar, and complex at-home activities performed by a variety of human subjects.

Proton Affinity Values of Fentanyl and Fentanyl Analogues Pertinent to Ambient Ionization and Detection.

Proton affinity is a major factor in the atmospheric pressure chemical ionization of illicit drugs. The detection of illicit drugs by mass spectrometry and ion mobility spectrometry relies on the analytes having greater proton affinities than background species. Evaluating proton affinities for fentanyl and its analogues is informative for predicting the likelihood of ionization in different environments and for optimizing the compounds' ionization and detection, such as through the addition of dopant chemicals. Herein, density functional theory was used to computationally determine the proton affinity and gas-phase basicity of 15 fentanyl compounds and several relevant molecules as a reference point. The range of proton affinities for the fentanyl compounds was from 1018 to 1078 kJ/mol. Fentanyl compounds with the higher proton affinity values appeared to form a bridge between the oxygen on the amide and the protonated nitrogen on the piperidine ring based on models and calculated bond distances. Experiments with fragmentation of proton-bound clusters using atmospheric flow tube-mass spectrometry (AFT-MS) provided estimates of relative proton affinities and showed proton affinity values of fentanyl compounds >1000 kJ/mol, which were consistent with the computational results. The high proton affinities of fentanyl compounds facilitate their detection by ambient ionization techniques in complex environments. The detection limits of the fentanyl compounds with AFT-MS are in the low femtogram range, which demonstrates the feasibility of trace vapor drug detection.

Review of Vesicular Stomatitis in the United States with Focus on 2019 and 2020 Outbreaks.

Vesicular stomatitis (VS) is a vector-borne livestock disease caused by vesicular stomatitis New Jersey virus (VSNJV) or vesicular stomatitis Indiana virus (VSIV). The disease circulates endemically in northern South America, Central America, and Mexico and only occasionally causes outbreaks in the United States. Over the past 20 years, VSNJV outbreaks in the southwestern and Rocky Mountain regions occurred with incursion years followed by virus overwintering and subsequent expansion outbreak years. Regulatory response by animal health officials is deployed to prevent spread from lesioned animals. The 2019 VS incursion was the largest in 40 years, lasting from June to December 2019 with 1144 VS-affected premises in 111 counties in eight states (Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, Utah, and Wyoming) and was VSIV serotype, last isolated in 1998. A subsequent expansion occurred from April to October 2020 with 326 VS-affected premises in 70 counties in eight states (Arizona, Arkansas, Kansas, Missouri, Nebraska, New Mexico, Oklahoma, and Texas). The primary serotype in 2020 was VSIV, but a separate incursion of VSNJV occurred in south Texas. Summary characteristics of the outbreaks are presented along with VSV-vector sampling results and phylogenetic analysis of VSIV isolates providing evidence of virus overwintering.

Trace explosive residue detection of HMX and RDX in post-detonation dust from an open-air environment.

Explosives are often used in industry, geology, mining, and other applications, but it is not always clear what remains after a detonation or the fate and transport of any residual material. The goal of this study was to determine to what extent intact molecules of high explosive (HE) compounds are detectable and quantifiable from post-detonation dust and particulates in a field experiment with varied topography. We focused on HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane), which is less studied in field detonation literature, as the primary explosive material and RDX (1,3,5-Trinitroperhydro-1,3,5-triazine) as the secondary material. The experiment was conducted at Site 300, Lawrence Livermore National Laboratory's Experimental Test Site, in California, USA. Two 20.4 kg and one 40.8 kg above ground explosions (primarily comprised of LX-14, an HMX-based polymer-bonded high explosive) were detonated on an open-air firing area on separate days. The complex terrain of the firing area (e.g., buildings, berm, low-height obstacles) was advantageous to study HE deposition in relation to plume dynamics. Three types of samples were collected up to 100 m away from each shot: surface swipes of aluminum plates, surface swipes of fixed objects, and filters from air samples. We used atmospheric flow tube-mass spectrometry (AFT-MS) to quantify picogram levels of molecular residue of HE material in the post-detonation dust. An aliquot of sample extract in methanol (e.g., 1 µL of 0.5 mL) was placed onto a resistive material and then thermally desorbed into the AFT-MS. We successfully detected and quantified both HMX and RDX in many of the samples. Based on mass (pg) detected and solution dilution, we back-calculated the mass collected on the swipe or filter (ng per sample). The aerial distribution of molecular residue was consistent with the path of the plume, which was strongly determined by wind speed and direction at the time of each shot. The quantity of material detected appeared to correlate more with distance from the shot and the wind conditions than with shot size. This study demonstrates that the picogram detection levels of AFT-MS are well-suited for quantification of analytes (e.g., HMX and RDX) in environmental samples.

Vapor Pressures of RDX and HMX Explosives Measured at and Near Room Temperature: 1,3,5-Trinitro-1,3,5-triazinane and 1,3,5,7-Tetranitro-1,3,5,7-tetrazocane.

Knowing accurate saturated vapor pressures of explosives at ambient conditions is imperative to provide realistic boundaries on available vapor for ultra-trace detection. In quantifying vapor content emanating from low-volatility explosives, we observed discrepancies between the quantity of explosive expected based on literature vapor pressure values and the amount detected near ambient temperatures. Most vapor pressure measurements for low-volatility explosives, such as RDX (1,3,5-trinitro-1,3,5-triazinane) and HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane), have been made at temperatures far exceeding 25 °C and linear extrapolation of these higher temperature trends appears to underestimate vapor pressures near room temperature. Our goal was to measure vapor pressures as a function of temperature closer to ambient conditions. We used saturated RDX and HMX vapor sources at controlled temperatures to produce vapors that were then collected and analyzed via atmospheric flow tube-mass spectrometry (AFT-MS). The parts-per-quadrillion (ppqv) sensitivity of AFT-MS enabled measurement of RDX vapor pressures at temperatures as low as 7 °C and HMX vapor pressures at temperatures as low as 40 °C for the first time. Furthermore, these vapor pressures were corroborated with analysis of vapor generated by nebulizing low concentration solutions of RDX and HMX. We report updated vapor pressure values for both RDX and HMX. Based on our measurements, the vapor pressure of RDX at 25 °C is 3 ± 1 × 10-11 atm (i.e., 30 parts per trillion by volume, pptv), the vapor pressure of HMX is 1.0 ± 0.6 × 10-14 atm (10 ppqv) at 40 °C and, with extrapolation, HMX has a vapor pressure of 1.0 ± 0.6 × 10-15 atm (1.0 ppqv) at 25 °C.

Non-contact vapor detection of illicit drugs via atmospheric flow tube-mass spectrometry.

Real-time, non-contact detection of illicit drugs is a desirable goal for the interdiction of these controlled substances, but the relatively low vapor pressures of such species present a challenge for trace vapor detection technologies. The introduction of atmospheric flow tube-mass spectrometry (AFT-MS), which has previously been demonstrated to detect gas-phase analytes at low parts-per-quadrillion levels for explosives and organophosphorus compounds, also enables the potential for non-contact drug detection. With AFT-MS, direct vapor detection of cocaine and methamphetamine from ∼5 µg residues at room temperature is demonstrated herein. Furthermore, thermal desorption of low- to sub-picogram levels of cocaine, methamphetamine, fentanyl, and heroin is observed via AFT-MS using a carrier flow rate of several L min-1 of air. These low levels can permit non-contact sampling through collection of vapor, effectively preconcentrating the analyte before desorption and analysis. Quantitative evaluation of the thermal desorption approach has yielded limits of detection (LODs) on the order of 10 fg for cocaine and fentanyl, 100 fg for methamphetamine, and 1.6 pg for heroin. The LOD for heroin was lowered to 300 fg by using tributyl phosphate as a dopant to form a proton-bound heterodimer with heroin. When used with AFT-MS, the intentional formation of specific drug-dopant adducts has the potential to enhance detection limits and selectivity of additional drug species. Species that are prone to form adducts present a challenge to analysis, but that difficulty can be overcome by the intentional addition of a dopant. Molecules unlikely to form adducts will remain essentially unimpacted, but the adduct-forming species will interact with the dopant to compress the analyte signal into a single peak. This approach would be valuable in the application of non-contact screening for illicit substances via vapor collection followed by thermal desorption for analysis.

Human Occupancy Detection via Passive Cognitive Radio.

Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be detected due to spectrum variation. In this paper, we present an advanced HOD system that dynamically reconfigures a CR to collect passive radio frequency (RF) signals at different places of interest. Principal component analysis (PCA) and recursive feature elimination with logistic regression (RFE-LR) algorithms are applied to find the frequency bands sensitive to human occupancy when the baseline spectrum changes with locations. With the dynamically collected passive RF signals, four machine learning (ML) classifiers are applied to detect human occupancy, including support vector machine (SVM), k-nearest neighbors (KNN), decision tree (DT), and linear SVM with stochastic gradient descent (SGD) training. The experimental results show that the proposed system can accurately detect human subjects-not only in residential rooms-but also in commercial vehicles, demonstrating that passive CR is a viable technique for HOD. More specifically, the RFE-LR with SGD achieves the best results with a limited number of frequency bands. The proposed adaptive spectrum sensing method has not only enabled robust detection performance in various environments, but also improved the efficiency of the CR system in terms of speed and power consumption.

Ambient vapor sampling and selective cluster formation for the trace detection of tributyl phosphate via atmospheric flow tube mass spectrometry.

In addition to serving as an f-element ligand and rare-earth method complexing agent, tributyl phosphate is a compound containing core functional groups that mimic those routinely found in degradation products from industrial processes. Because detection of trace quantities of tributyl phosphate can provide insight into the routes of contamination and degradation in the environment, there is a need to develop methods capable of detecting trace quantities of tributyl phosphate. Vapor detection at atmospheric pressure is one approach that is both sensitive and rapid. We present here the use of atmospheric flow tube mass spectrometry for the ambient vapor sampling of tributyl phosphate from headspace of ppb-level solutions in methanol. Gas phase clustering reactions were to enhance detection levels via the addition of small quantities of the dopants diethylamine, triethylamine, and pinacolyl methylphosphonate in the vapor stream. Detection of the tributyl phosphate vapor emanating from these solutions demonstrated a linear range for the protonated tributyl phosphate species of 1-1000 ppb from solution. The clusters of tributyl phosphate with diethylamine, triethylamine, and pinacolyl phosphonate each yielded linear ranges of 1-250 ppb for tributyl phosphate in solution. Despite smaller linear ranges, the addition of these dopant species added a layer of analytical selectivity and reduced variability in signals from quality control samples. These data were obtained using an atmospheric flow tube source coupled to a linear ion trap mass spectrometer, which demonstrates the applicability of trapping systems to the atmospheric flow tube ionization technique while monitoring positive ions.