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Networked radiation detection system for rapid tactical response [Slides]
Abstract not provided.
A Rapid Method for Detecting Normal or Modified Plant and Algal Carbonic Anhydrase Activity Using Saccharomyces cerevisiae
In recent years, researchers have attempted to improve photosynthesis by introducing components from cyanobacterial and algal CO2-concentrating mechanisms (CCMs) into terrestrial C3 plants. For these attempts to succeed, we need to understand the CCM components in more detail, especially carbonic anhydrase (CA) and bicarbonate (HCO3−) transporters. Heterologous complementation systems capable of detecting carbonic anhydrase activity (i.e., catalysis of the pH-dependent interconversion between CO2 and HCO3−) or active HCO3− transport can be of great value in the process of introducing CCM components into terrestrial C3 plants. In this study, we generated a Saccharomyces cerevisiae CA knock-out (ΔNCE103 or ΔCA) that has a high-CO2-dependent phenotype (5% (v/v) CO2 in air). CAs produce HCO3− for anaplerotic pathways in S. cerevisiae; therefore, the unavailability of HCO3− for neutral lipid biosynthesis is a limitation for the growth of ΔCA in ambient levels of CO2 (0.04% (v/v) CO2 in air). ΔCA can be complemented for growth at ambient levels of CO2 by expressing a CA from human red blood cells. ΔCA was also successfully complemented for growth at ambient levels of CO2 through the expression of CAs from Chlamydomonas reinhardtii and Arabidopsis thaliana. The ΔCA strain is also useful for investigating the activity of modified CAs, allowing for quick screening of modified CAs before putting them into the plants. CA activity in the complemented ΔCA strains can be probed using the Wilbur–Anderson assay and by isotope exchange membrane-inlet mass spectrometry (MIMS). Other potential uses for this new ΔCA-based screening system are also discussed.
Rapid culture free pathogen detection via spectrally resolved fluorescence microscopy
Methods and apparatus for rapid, culture free pathogen detection. The methods utilize optical spectroscopy techniques to identify and/or characterize pathogens in a sample via the detection of unique properties and/or analytes that are specific to particular pathogens.
Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs
Time-consuming, expensive and low sensitivity diagnostic methods used for monitoring bacterial infections lead to unnecessary or delays in prescription of the right antibiotic treatment. Determining an optimal clinical treatment requires rapid detection and identification of pathogenic bacteria and their sensitivity to specific antimicrobials. However, diagnostic devices that meet all of these criteria have proven elusive thus far. Graphene field effect transistors (G-FET) are a promising solution, since they are highly sensitive to chemical/biological modification, can have fast detection times and can be placed on different substrates. Here, by integrating specific peptide probes over G-FETs, we present a proof-of-concept study for species and strain specific label-free detection of clinical strains of pathogenic bacteria with high specificity and sensitivity. We found that pyrene-conjugated peptides immobilized on G-FETs were capable of detecting pathogenic Staphylococcus aureus at the single-cell level and discriminate against other gram-positive and gram-negative bacterial pathogens. A similar device was able to discriminate between antibiotic resistant and sensitive strains of Acinetobacter baumannii , suggesting that these devices can also be used for detecting antibiotic resistive pathogens. Furthermore, a new means of enhancing attachment, electric-field assisted binding, reduced the detection limit to 104 cells/ml and the detection time to below 5 minutes. Here, the combination of single step attachment, inexpensive production, rapid, selective and sensitive detection suggest G-FETs plus pyrene-conjugated peptides are a new platform for solving major challenges faced in point of care diagnostics to fight infectious diseases and antimicrobial resistance.
Implementation of rapid diagnostics assays for detection of histoplasmosis and cryptococcosis in central american people living with HIV
Abstract Objectives Histoplasmosis and cryptococcosis are important public health problems in people living with HIV (PLHIV) in Central America. Conventional laboratory assays, based on microscopy and culture, are not optimal for the diagnosis of either disease. However, antigen (Ag) assays are rapid and highly accurate for the diagnosis of these infections. Methods Laboratory surveillance of PLHIV was carried out in four hospitals in Panama, Honduras and Nicaragua, between 2015 and 2019. Detection of Histoplasma antigens in urine was performed by enzyme immunoassay (EIA), and Cryptococcus antigen detection in sera and cerebrospinal fluid specimens was performed by lateral flow assay (LFA). Results A total of 4,453 PLHIV with clinical suspicion of histoplasmosis ( n = 1,343) or cryptococcosis ( n = 3,110; 2,721 sera and 389 CSF) were tested. Of 1,343 patients suspected of having histoplasmosis, 269 (20%) were Histoplasma Ag positive. Of 3,110 patients tested using the Cryptococcus Ag assay, 329 (11%) were positive. Honduras reported the highest positivity rates (32% for Histoplasma Ag, and 16% for Cryptococcus Ag); Panama reported the largest number of patients testing positive using the Histoplasma Ag assay ( n = 201); and Nicaragua reported the largest number of patients testing positive using the Cryptococcus Ag assay ( n = 170). Conclusion Here, we show how the implementation of rapid diagnostics assays impacted case detection and was useful for the care of people with advanced HIV. Rapid and accurate diagnosis could reduce mortality associated with histoplasmosis and cryptococcosis in PLHIV.
Rapid, Sensitive, Label-Free Electrical Detection of SARS-CoV-2 in Nasal Swab Samples
Rapid diagnosis of coronavirus disease 2019 (COVID-19) is key for the long-term control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) amid renewed threats of mutated SARS-CoV-2 around the world. Here, we report on an electrical label-free detection of SARS-CoV-2 in nasopharyngeal swab samples directly collected from outpatients or in saliva-relevant conditions by using a remote floating-gate field-effect transistor (RFGFET) with a 2-dimensional reduced graphene oxide (rGO) sensing membrane. RFGFET sensors demonstrate rapid detection (<5 min), a 90.6% accuracy from 8 nasal swab samples measured by 4 different devices for each sample, and a coefficient of variation (CV) < 6%. Also, RFGFET sensors display a limit of detection (LOD) of pseudo-SARS-CoV-2 that is 10 000-fold lower than enzyme-linked immunosorbent assays, with a comparable LOD to that of reverse transcriptionpolymerase chain reaction (RT-PCR) for patient samples. To achieve this, comprehensive systematic studies were performed regarding interactions between SARS-CoV-2 and spike proteins, neutralizing antibodies, and angiotensin-converting enzyme 2, as either a biomarker (detection target) or a sensing probe (receptor) functionalized on the rGO sensing membrane. Finally, taken together, this work may have an immense effect on positioning FET bioelectronics for rapid SARS-CoV-2 diagnostics.
Facile All-Optical Method for In Situ Detection of Low Amounts of Ammonia
As a key precursor for nitrogenous compounds and fertilizer, ammonia affects our lives in numerous ways. Rapid and sensitive detection of ammonia is essential, both in environmental monitoring and in process control for industrial production. Here we report a novel and nonperturbative method that allows rapid detection of ammonia at low concentrations, based on the all-optical detection of surface-enhanced Raman signals. We show that this simple and affordable approach enables ammonia probing at selected regions of interest with high spatial resolution, making in situ and operando observations possible.
All-aerosol-jet-printed highly sensitive and selective polyaniline-based ammonia sensors: a route toward low-cost, low-power gas detection
In this work, we report the design and scalable fabrication of a low-cost and low-power polyaniline-based (PANI) ammonia (NH3) gas sensor on polyimide (PI) substrates using additive manufacturing techniques. The silver interdigitated electrode (IDE) arrays and conducting polymer films are printed onto PI using a direct-write technology of aerosol-jet printing. Morphological characteristics are examined by scanning electron microscopy and energy-dispersive X-ray analysis which reveal homogeneously printed PANI film on the IDE platform. The gas sensing performance is evaluated in the analytical early leak detection range of 5–1000 ppm NH3 in air as a function of both thermal (23 °C, 50 °C, 80 °C) and relative humidity (RH = 0%, 30%, 50%) exposures. The sensor exhibits sensitivity down to 5 ppm NH3 with a sub-ppm detection limit and good repeatability. We observe rapid NH3 detection at 0% RH with very extended times for equilibration and recovery. However, at both 30 and 50% RH, the room temperature response and recovery times are reduced to only about 1 min and 5 min, respectively. Experiments also reveal good sensitivity toward the analyte even at higher operating temperatures. Present results merit the practical application of aerosol-jet-printed, low-power sensors for industrial applications where low-level hazardous gas detection is essential.
Atomically Precise Hexanuclear Ce(IV) Clusters as Functional Fluorescent Nanosensors for Rapid One-Step Detection of PFAS
Here, the presence of poly- and perfluoroalkyl substances (PFAS) in the environment is associated with adverse health effects but measuring PFAS is challenging due to the associated high cost and technical complexities of the analysis. Here, the reactivity of atomically precise metal-oxo clusters is reported and the foundation for their use is provided as fluorescent nanosensors for PFAS detection. The material comprises crystalline, water soluble, hexanuclear cerium-oxo clusters [Ce 6 (µ 3 -O) 4 (µ 3 -OH) 4 ] 12+ decorated with glycine molecules (Ce-Gly) characterized by fluorescence emission at 353 nm. The Ce-Gly fluorescence is found sensitive to long chain carboxylated PFAS of CF 3 –(CF 2 ) n –, where n ≥ 6, such as perfluorooctanoic, perfluorononanoic and perfluorodecanoic acids. This unique reactivity leads to a change in the emission spectra in a concentration dependent manner, enabling PFAS detection through ligand exchange and aggregation-induced emission (AIE) enhancement. No significant cross-reactivity from potentially co-existing species, including sulfonated PFAS, octanoic and dodecanoic acids, humic acid, and inorganic ions is observed. With an optimal concentration of 3.3 µg mL -1 Ce-Gly, the method demonstrated detection limits of 0.24 ppb for PFOA and 0.4 ppb for PFNA. These findings highlight the potential of fluorescence-based detection strategies utilizing nanoscale probes such as Ce-Gly as fluorescent probes and nanosensors for PFAS.
Wide-Area, Rapid Vacuum Bag Leak Detection for Composite Wind Turbine Blade Fabrication
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Early detection and uncertainty quantification of rapid sea-level rise from Antarctica
Focal Areas: (i) classification and/or anomaly detection methods applied towards identifying critical climate system thresholds; improved emulator design for (ii) reducing computational costs relative to full-physics models and (iii) improved uncertainty quantification workflows. Rationale: The evolution of the Antarctic ice sheet in response to climate change remains the single largest uncertainty in projecting future sea-level rise (SLR), with risk-averse projections for 2100 spanning between zero and a half meter. During the past decade, DOE has made substantial investments in new ice sheet and Earth system models needed to improve both understanding and predictive capability in this area. Yet major challenges remain, including better understanding when and under what circumstances significant increases in SLR from Antarctica may be initiated and better quantifying uncertainties in model-based SLR projections. Here, we discuss the potential for transformative advances in these areas through the application of machine learning and artificial intelligence (ML and AI, respectively).
The Gamow Explorer: a Gamma-Ray Burst Observatory to study the high redshift universe and enable multi-messenger astrophysics
The Gamow Explorer will use Gamma Ray Bursts (GRBs) to: 1) probe the high redshift universe (z < 6) when the first stars were born, galaxies formed and Hydrogen was reionized; and 2) enable multi-messenger astrophysics by rapidly identifying Electro-Magnetic (IR/Optical/X-ray) counterparts to Gravitational Wave (GW) events. GRBs have been detected out to z ~ 9 and their afterglows are a bright beacon lasting a few days that can be used to observe the spectral fingerprints of the host galaxy and intergalactic medium to map the period of reionization and early metal enrichment. Gamow Explorer is optimized to quickly identify high-z events to trigger follow-up observations with JWST and large ground-based telescopes. A wide field of view Lobster Eye X-ray Telescope (LEXT) will search for GRBs and locate them with arc-minute precision. When a GRB is detected, the rapidly slewing spacecraft will point the 5 photometric channel Photo-z Infra-Red Telescope (PIRT) to identify high redshift (z < 6) long GRBs within 100s and send an alert within 1000s of the GRB trigger. An L2 orbit provides < 95% observing efficiency with pointing optimized for follow up by the James Webb Space Telescope (JWST) and ground observatories. The predicted Gamow Explorer high-z rate is <10 times that of the Neil Gehrels Swift Observatory. The instrument and mission capabilities also enable rapid identification of short GRBs and their afterglows associated with GW events. The Gamow Explorer will be proposed to the 2021 NASA MIDEX call and if approved, launched in 2028.
Rare Earth Element Detection and Quantification in Coal and Rock Mineral Matrices
As global demand for rare earth elements (REEs) increases, maintaining the production and supply chain is critical. Technologies capable of being used in the field and in situ in the subsurface for rapid REE detection and quantification facilitates the efficient mining of known resources and exploration of new and unconventional resources. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for rapid elemental analysis both in the laboratory and in the field. Multiple articles have been published evaluating LIBS for detection and quantification of REEs; however, REEs in their natural deposits have not been adequately studied. In this work, detection and quantification of two REEs, La and Nd, have been studied in both synthetic and natural mineral matrices at concentrations relevant to REE extraction. Measurements were performed on REE-containing rock and coal samples (natural and synthetic) utilizing different LIBS instruments and techniques, specifically a commercial benchtop instrument, a custom benchtop instrument (single- and double-pulse modes), and a custom LIBS probe currently being developed for in situ, subsurface, borehole wall detection and quantification of REEs. Plasma expansion, emission intensity, detection limits, and double-pulse signal enhancement were studied. The limits of detection (LOD) were found to be 10/14 ppm for La and 15/25 ppm for Nd in simulated coal/rock matrices in single-pulse mode. Signal enhancement of 3.5 to 6-fold was obtained with double-pulse mode as compared to single-pulse operation.
Why would you put a flashlight in a dark matter detector?
Silicon photomultipliers (SiPMs) are solid-state, single-photon sensitive, pixelated sensors whose usage for scintillation detection has rapidly increased over the past decade. It is known that the avalanche process within the device, which renders a single photon detectable, can also generate secondary photons which may be detected by a separate device. This effect, known as external crosstalk, could potentially degrade the science goals of future xenon dark matter experiments. In this article, we measure the effect of external crosstalk in a dual-phase, liquid xenon time projection chamber fully instrumented with SiPMs. We then consider the implications for a future xenon dark matter experiment utilizing SiPMs and discuss possible solutions.
CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks
Rapid and accurate detection and localization of electronic disturbances simultaneously are important for preventing its potential damages and determining potential remedies. Existing anomaly detection methods are severely limited by the low accuracy, the expensive computational cost and the need for highly trained personnel. There is an urgent need for a scalable online algorithm for in-field analysis of large-scale power electronics networks. Here in this paper, we propose a fast and accurate algorithm for anomaly detection and localization of power electronics networks: stratified colored-node graph (CONGO2). This algorithm hierarchically models the change of correlated waveforms and then correlated sensors using the colored-node graph. By aggregating the change of each sensor with its neighbors’ inputs, we can spontaneously identify and localize the anomaly that cannot be detected by data collected from a single sensor. As our proposed method only focuses on the changes within a short time frame, it is highly computational efficient and only needs small data storage. Thus, our method is ideal for online and reliable anomaly detection and localization of large-scale power electronic networks. Compared to existing anomaly detection methods, our method is entirely data-driven without training data, highly accurate and reliable for wide-spectrum anomalies detection, and more importantly, capable of both detection and localization. Thus, it is ideal for infield deployment for large-scale power electronic networks. As illustrated by a distributed energy resources (DERs) power grid with 37-node, our method can effectively detect and localize various cyber and physical attacks.
Automatic Detection and Classification of Radio Galaxy Images by Deep Learning
Abstract Surveys conducted by radio astronomy observatories, such as SKA, MeerKAT, Very Large Array, and ASKAP, have generated massive astronomical images containing radio galaxies (RGs). This generation of massive RG images has imposed strict requirements on the detection and classification of RGs and makes manual classification and detection increasingly difficult, even impossible. Rapid classification and detection of images of different types of RGs help astronomers make full use of the observed astronomical image data for further processing and analysis. The classification of FRI and FRII is relatively easy, and there are more studies and literature on them at present, but FR0 and FRI are similar, so it is difficult to distinguish them. It poses a greater challenge to image processing. At present, deep learning has made breakthrough progress in the field of image analysis and processing and has preliminary applications in astronomical data processing. Compared with classification algorithms that can only classify galaxies, object detection algorithms that can locate and classify RGs simultaneously are preferred. In target detection algorithms, YOLOv5 has outstanding advantages in the classification and positioning of small targets. Therefore, we propose a deep-learning method based on an improved YOLOv5 object detection model that makes full use of multisource data, combining FIRST radio with SDSS optical image data, and realizes the automatic detection of FR0, FRI, and FRII RGs. The innovation of our work is that on the basis of the original YOLOv5 object detection model, we introduce the SE Net attention mechanism, increase the number of preset anchors, adjust the network structure of the feature pyramid, and modify the network structure, thereby allowing our model to demonstrate galaxy classification and position detection effects. Our improved model produces satisfactory results, as evidenced by experiments. Overall, the mean average precision (mAP@0.5) of our improved model on the test set reaches 89.4%, which can determine the position (R.A. and decl.) and automatically detect and classify FR0s, FRIs, and FRIIs. Our work contributes to astronomy because it allows astronomers to locate FR0, FRI, and FRII galaxies in a relatively short time and can be further combined with other astronomically generated data to study the properties of these galaxies. The target detection model can also help astronomers find FR0s, FRIs, and FRIIs in future surveys and build a large-scale star RG catalog. Moreover, our work is also useful for the detection of other types of galaxies.
Smartphone-Based Device for Colorimetric Detection of MicroRNA Biomarkers Using Nanoparticle-Based Assay
The detection of microRNAs (miRNAs) is emerging as a clinically important tool for the non-invasive detection of a wide variety of diseases ranging from cancers and cardiovascular illnesses to infectious diseases. Over the years, miRNA detection schemes have become accessible to clinicians, but they still require sophisticated and bulky laboratory equipment and trained personnel to operate. The exceptional computing ability and ease of use of modern smartphones coupled with fieldable optical detection technologies can provide a useful and portable alternative to these laboratory systems. Herein, we present the development of a smartphone-based device called Krometriks, which is capable of simple and rapid colorimetric detection of microRNA (miRNAs) using a nanoparticle-based assay. The device consists of a smartphone, a 3D printed accessory, and a custom-built dedicated mobile app. We illustrate the utility of Krometriks for the detection of an important miRNA disease biomarker, miR-21, using a nanoplasmonics-based assay developed by our group. We show that Krometriks can detect miRNA down to nanomolar concentrations with detection results comparable to a laboratory-based benchtop spectrophotometer. With slight changes to the accessory design, Krometriks can be made compatible with different types of smartphone models and specifications. Thus, the Krometriks device offers a practical colorimetric platform that has the potential to provide accessible and affordable miRNA diagnostics for point-of-care and field applications in low-resource settings.