Ambient Contamination Research Articles

Impact of Ambient Air Contamination on the Performance of Argyrodite-Based All-Solid-State Lithium–Sulfur Batteries

Impact of Ambient Air Contamination on the Performance of Argyrodite-Based All-Solid-State Lithium–Sulfur Batteries

Interpretable single-cell factor decomposition using sciRED.

Single-cell RNA sequencing (scRNA-seq) maps gene expression heterogeneity within a tissue. However, identifying biological signals in this data is challenging due to confounding technical factors, sparsity, and high dimensionality. Data factorization methods address this by separating and identifying signals in the data, such as gene expression programs, but the resulting factors must be manually interpreted. We developed Single-Cell Interpretable Residual Decomposition (sciRED) to improve the interpretation of scRNA-seq factor analysis. sciRED removes known confounding effects, uses rotations to improve factor interpretability, maps factors to known covariates, identifies unexplained factors that may capture hidden biological phenomena and determines the genes and biological processes represented by the resulting factors. We apply sciRED to multiple scRNA-seq datasets and identify sex-specific variation in a kidney map, discern strong and weak immune stimulation signals in a PBMC dataset, reduce ambient RNA contamination in a rat liver atlas to help identify strain variation, and reveal rare cell type signatures and anatomical zonation gene programs in a healthy human liver map. These demonstrate that sciRED is useful in characterizing diverse biological signals within scRNA-seq data.

Interpretable single-cell factor decomposition using sciRED.

Single-cell RNA sequencing (scRNA-seq) maps gene expression heterogeneity within a tissue. However, identifying biological signals in this data is challenging due to confounding technical factors, sparsity, and high dimensionality. Data factorization methods address this by separating and identifying signals in the data, such as gene expression programs, but the resulting factors must be manually interpreted. We developed Single-Cell Interpretable Residual Decomposition (sciRED) to improve the interpretation of scRNA-seq factor analysis. sciRED removes known confounding effects, uses rotations to improve factor interpretability, maps factors to known covariates, identifies unexplained factors that may capture hidden biological phenomena and determines the genes and biological processes represented by the resulting factors. We apply sciRED to multiple scRNA-seq datasets and identify sex-specific variation in a kidney map, discern strong and weak immune stimulation signals in a PBMC dataset, reduce ambient RNA contamination in a rat liver atlas to help identify strain variation, and reveal rare cell type signatures and anatomical zonation gene programs in a healthy human liver map. These demonstrate that sciRED is useful in characterizing diverse biological signals within scRNA-seq data.

Per- and polyfluoroalkyl substances (PFAS) in paired tap water and house dust from United States homes

Most people in the United States have been exposed to per- and polyfluoroalkyl substances (PFAS) which have been linked to a wide array of adverse health conditions in adults and children. The consumption of contaminated drinking water is an important human exposure pathway to PFAS. Residential sources also contribute to PFAS exposure through dermal contact and ingestion of house dust, which acts as an aggregate of chemicals from sources like furnishing materials and consumer products. The U.S. Department of Housing and Urban Development (HUD) conducted the first nationwide survey of residential hazards called the American Healthy Homes Survey (AHHS) in 2005, followed by a second survey (AHHS II) in 2017. The U.S. Environmental Protection Agency (EPA) collaborated with HUD on both efforts and subsequently analyzed PFAS in household tap water and house dust collected from the same homes during the AHHS II study. This study leverages these paired samples to investigate potentially important exposure sources and pathways in the residential environment. Here we report results for paired household tap water and house dust samples from 241 homes for 13 and 16 PFAS chemicals, respectively. All 13 targeted chemicals were detected in the household tap water samples with detections ranging from 100 % for PFBS to 1 % for PFNS, and all 16 targeted chemicals were detected in the house dust samples with detections ranging from 97 % for PFOA to 9 % for PFNS. Four chemicals (PFOA, PFOS, PFHxS, and PFHpA) were measured above the limit of detection in at least 50 % of the samples in both media. All households had at least one of the targeted PFAS detected in both their tap water and house dust. Results provided evidence that geographical factors, such as proximity to ambient contamination sources, were main drivers of PFAS contamination in tap water, while PFAS contamination in house dust was driven mainly by within-home sources. Exposure estimates calculated from the measured PFAS concentrations highlight the importance of addressing potential sources of exposure to PFAS within homes in addition to ambient sources affecting communities’ drinking water, particularly to reduce children’s exposure to these chemicals.

Bayesian time domain approach for damping identification and uncertainty quantification in stay cables using free vibration response

The dynamic characteristics, particularly damping, play crucial roles in the design, monitoring, and vibration control of stay cables. The free vibration test, commonly used for damping identification of stay cables, demonstrates notable technical advantages in specific mode excitation and improving the signal-to-noise ratio. Nevertheless, challenges arise from uncertainties associated with ineluctable ambient vibration influences and noise contamination in measured responses. In recent years, there has been a growing interest in Bayesian modal identification methods due to their remarkable ability to quantify uncertainties. However, further advancements are needed in the time domain, particularly when addressing the relatively short duration of free vibration response data. This is essential to minimize the impact of background ambient vibration and enhance the accuracy of modal identification. This paper proposes a novel Bayesian modal identification approach specifically crafted to address free vibration data affected by ambient vibrations, aiming to achieve high-precision modal identification and effective uncertainty quantification from free vibration response of stay cables. Additionally, a speedup algorithm is used for determining the most probable values (MPVs) to enhance computational efficiency. The efficacy of the proposed approach is validated through simulated scenarios, encompassing both a single-degree-of-freedom structure and a finite element model of a stay cable. Furthermore, the effectiveness of the proposed method is validated through its application in a laboratory test involving a scale model of the stay cable, as well as in a field test of actual stay cables of Sutong Bridge. The results demonstrate that the proposed method achieves high accuracy in identifying modal damping ratios, and effectively quantifies uncertainties in the identification results.

ToF-SIMS analysis of ultrathin films and their fragmentation patterns.

Organic thin films are of great interest due to their intriguing interfacial and functional properties, especially for device applications such as thin-film transistors and sensors. As their thickness approaches single nanometer thickness, characterization and interpretation of the extracted data become increasingly complex. In this study, plasma polymerization is used to construct ultrathin films that range in thickness from 1 to 20 nm, and time-of-flight secondary ion mass spectrometry coupled with principal component analysis is used to investigate the effects of film thickness on the resulting spectra. We demonstrate that for these cross-linked plasma polymers, at these thicknesses, the observed trends are different from those obtained from thicker films with lower degrees of cross-linking: contributions from ambient carbon contamination start to dominate the mass spectrum; cluster-induced nonlinear enhancement in secondary ion yield is no longer observed; extent of fragmentation is higher due to confinement of the primary ion energy; and the size of the primary ion source also affects fragmentation (e.g., Bi1 versus Bi5). These differences illustrate that care must be taken in choosing the correct primary ion source as well as in interpreting the data.

FastCAR: fast correction for ambient RNA to facilitate differential gene expression analysis in single-cell RNA-sequencing datasets

Cell type-specific differential gene expression analyses based on single-cell transcriptome datasets are sensitive to the presence of cell-free mRNA in the droplets containing single cells. This so-called ambient RNA contamination may differ between samples obtained from patients and healthy controls. Current ambient RNA correction methods were not developed specifically for single-cell differential gene expression (sc-DGE) analyses and might therefore not sufficiently correct for ambient RNA-derived signals. Here, we show that ambient RNA levels are highly sample-specific. We found that without ambient RNA correction, sc-DGE analyses erroneously identify transcripts originating from ambient RNA as cell type-specific disease-associated genes. We therefore developed a computationally lean and intuitive correction method, Fast Correction for Ambient RNA (FastCAR), optimized for sc-DGE analysis of scRNA-Seq datasets generated by droplet-based methods including the 10XGenomics Chromium platform. FastCAR uses the profile of transcripts observed in libraries that likely represent empty droplets to determine the level of ambient RNA in each individual sample, and then corrects for these ambient RNA gene expression values. FastCAR can be applied as part of the data pre-processing and QC in sc-DGE workflows comparing scRNA-Seq data in a health versus disease experimental design. We compared FastCAR with two methods previously developed to remove ambient RNA, SoupX and CellBender. All three methods identified additional genes in sc-DGE analyses that were not identified in the absence of ambient RNA correction. However, we show that FastCAR performs better at correcting gene expression values attributed to ambient RNA, resulting in a lower frequency of false-positive observations. Moreover, the use of FastCAR in a sc-DGE workflow increases the cell-type specificity of sc-DGE analyses across disease conditions.

Explantation of a light-adjustable intraocular lens: case report with laboratorial analyses

Introduction: A case in which a light-adjustable lens (LAL) underwent explantation and extensive laboratory analyses is reported. Patient and Clinical Findings: A 61-year-old man underwent uneventful cataract surgery with in-the-bag implantation of a first-generation LAL in the right eye. Examination on the second postoperative day revealed limbus-to-limbus corneal edema, moderate anterior chamber cells, and a mid-dilated, minimally responsive pupil, suggesting toxic anterior segment syndrome (TASS). Diagnosis, Intervention, and Outcomes: Endothelial keratoplasty was performed 2 months after LAL implantation. The patient reported noncompliance with required UV-protective eyewear, and an attempted light adjustment confirmed macromer reserve depletion, likely secondary to ambient UV contamination. Gross and microscopic examinations of the explanted LAL showed a decentered round elevation on the optic. The light transmittance (%T) curve was normal, with 95.9%T on average in the visible spectrum. Optical coherence tomography revealed irregular curvatures of the anterior and posterior optic surfaces. Wavefront analysis displayed aberrations and large power variations, which corresponded to decreased focus and contrast through the optic. Conclusions: To the authors' knowledge, this is the first reported case of LAL implantation complicated by TASS, leading to a prolonged clinical course and nonadherence to proprietary UV-protective spectacles. Extensive laboratory analyses of the explanted LAL demonstrated findings that can be expected with uncontrolled polymerization of the LAL.

A-327 Pre-analytical and Analytical Modifications to Improve the Quality of Pediatric Lead Tests

Abstract Background The recent decrease in the CDC Blood Lead Reference Value (BLRV) to 3.5 ug/dL has highlighted the need for systematic changes that some clinicians and laboratories need to implement to assure the quality of reported pediatric lead results. Building upon the recommendations of the Blood Lead Reference Value Workgroup, APHL has developed specific recommendations and resources designed to assist medical professionals and laboratory scientists in minimizing the likelihood of contamination when collecting and testing blood specimens. Also included are analytical practices that can improve precision, accuracy, and sensitivity of pediatric lead assays. Methods Evaluation of existing protocols and practices to identify potential sources of contamination and opportunities for process improvement. Results APHL will provide practical recommendations to systematically improve point of care and fixed laboratory testing to improve confidence in reported pediatric lead concentrations. These improved measurements will improve environmental health surveillance and inform public health intervention and patient care. Conclusion Rigorous pre-analytical practices including education, updated specimen collection guidance, pre-screening of collection materials, improvement of point of care technology and refinement of spectroscopic analytical methods result in less ambient contamination, improved sensitivity, precision and accuracy of pediatric lead testing. Clinician office practices, public health and commercial clinical laboratories will all benefit from implementing these strategies.

Toward high-quality X-59 sonic thump measurements

Brigham Young University has been investigating best practices for recommendation to NASA in upcoming X-59 sonic thump measurements. This preparatory work has focused both on obtaining high-fidelity data and standardizing signal analysis techniques for sonic thumps. Included in the research are topics such as whether to use a ground-based or elevated microphone, how to use low-noise microphones and still recover high-fidelity data at low frequencies, and estimating the uncertainty in a given measurement due to local atmospheric turbulence effects. Also included is a study of windowing techniques, zero padding, and the removal of high-frequency ambient noise contamination.

A contamination focused approach for optimizing the single-cell RNA-seq experiment

Droplet-based single-cell RNA-seq (scRNA-seq) data are plagued by ambient contaminations caused by nucleic acid material released by dead and dying cells. This material is mixed into the buffer and is co-encapsulated with cells, leading to a lower signal-to-noise ratio. Although there exist computational methods to remove ambient contaminations post-hoc, the reliability of algorithms in generating high-quality data from low-quality sources remains uncertain. Here, we assess data quality before data filtering by a set of quantitative, contamination-based metrics that assess data quality more effectively than standard metrics. Through a series of controlled experiments, we report improvements that can minimize ambient contamination outside of tissue dissociation, via cell fixation, improved cell loading, microfluidic dilution, and nuclei versus cell preparation; many of these parameters are inaccessible on commercial platforms. We provide end-users with insights on factors that can guide their decision-making regarding optimizations that minimize ambient contamination, and metrics to assess data quality.

Ambient RNAs removal of cortex-specific snRNA-seq reveals Apoe+ microglia/macrophage after deeper cerebral hypoperfusion in mice

BackgroundAmbient RNAs contamination in single-nuclei RNA sequencing (snRNA-seq) is a challenging problem, but the consequences of ambient RNAs contamination of damaged and/or diseased tissues are poorly understood. Cognitive impairments and white/gray matter injuries are characteristic of deeper cerebral hypoperfusion mouse models induced by bilateral carotid artery stenosis (BCAS), but the molecular mechanisms still need to be further explored. More importantly, the BCAS mice can also offer an excellent model to examine the signatures of ambient RNAs contamination in damaged tissues when performing snRNA-seq.MethodsAfter the sham and BCAS mice were established, cortex-specific single-nuclei libraries were constructed. Single-nuclei transcriptomes were described informatically by the R package Seurat, and ambient RNA markers of were identified in each library. Then, after removing ambient RNAs in each sample using the in silico approaches, the combination of CellBender and subcluster cleaning, single-nuclei transcriptomes were reconstructed. Next, the comparison of ambient RNA contamination was performed using irGSEA analysis before and after the in silico approaches. Finally, further bioinformatic analyses were performed.ResultsThe ambient RNAs are more predominant in the BCAS group than the sham group. The contamination mainly originated from damaged neuronal nuclei, but could be reduced largely using the in silico approaches. The integrative analysis of cortex-specific snRNA-seq data and the published bulk transcriptome revealed that microglia and other immune cells were the primary effectors. In the sequential microglia/immune subgroups analysis, the subgroup of Apoe+ MG/Mac (microglia/macrophages) was identified. Interestingly, this subgroup mainly participated in the pathways of lipid metabolism, associated with the phagocytosis of cell debris.ConclusionsTaken together, our current study unravels the features of ambient RNAs in snRNA-seq datasets under diseased conditions, and the in silico approaches can effectively eliminate the incorrected cell annotation and following misleading analysis. In the future, snRNA-seq data analysis should be carefully revisited, and ambient RNAs removal needs to be taken into consideration, especially for those diseased tissues. To our best knowledge, our study also offers the first cortex-specific snRNA-seq data of deeper cerebral hypoperfusion, which provides with novel therapeutic targets.

Towards high-quality X-59 sonic thump measurements

Brigham Young University has been studying questions related to NASA X-59 community noise testing. A summary of the key findings and recommendations to date are presented. Among these are weather-resistant ground microphone setups that reduce wind noise, methods for treating the problem of ambient noise contamination on sonic boom metrics and spectra, and the turbulence-induced variability seen over relatively small-aperture arrays. Also discussed are recommendations for data post-processing, e.g., employing a digital pole-shifting filter and zero-padding to improve the fidelity and smoothness of low-frequency spectral data. Finally, the relative merits of various sonic boom metrics are considered. Although Perceived Level has been the most widely-used metric, it is relatively sensitive to ambient noise contamination and turbulence-induced variability. [Work supported by NASA Langley Research Center through the National Institute of Aerospace.]

Camera-based radiotherapy dosimetry using dual-material 3D printed scintillator arrays.

To describe a methodology for the dual-material fused deposition modeling (FDM) 3D printing of plastic scintillator arrays, to characterize their light output under irradiation using an sCMOS camera, and to establish a methodology for the dosimetric calibration of planar array geometries. We have published an investigation into the fabrication and characterization of single element FDM printed scintillators intending to produce customizable dosimeters for radiation therapy applications. 1 This work builds on previous investigations by extending the concept to the production of a high-resolution (scintillating element size 3×3×3mm3 ) planar scintillator array. The array was fabricated using a BCN3D Epsilon W27 3D printer and composed of polylactic acid (PLA) filament and BCF-10 plastic scintillator. The array's response was initially characterized using a 20×20cm2 6 MV photon field with a source-to-surface (SSD) distance of 100cm and the beam incident on the top of the array. The light signals emitted under irradiation were imaged using 200ms exposures from a sCMOS camera positioned at the foot of the treatment couch (210cm from the array). The collected images were then processed using a purpose-built software to correct known optical artefacts and determine the light output for each scintillating element. The light output was then corrected for element sensitivity and calibrated to dose using Monte Carlo simulations of the array and irradiation geometry based on the array's digital 3D print model. To assess the accuracy of the array calibration both a 3D beam and a clinical VMAT plan were delivered. Dose measurements using the calibrated array were then compared to EBT3 GAFChromic film and OSLD measurements, as well as Monte Carlo simulations and TPS calculations. Our results establish the feasibility of dual-material 3D printing for the fabrication of custom plastic scintillator arrays. Assessment of the 3D printed scintillators response across each row of the array demonstrated a nonuniform response with an average percentage deviation from the mean of 2.1%±2.8%. This remains consistent with our previous work on individual 3D printed scintillators which showed an average difference of 2.3% and a maximum of 4.0% between identically printed scintillators.1 Array dose measurements performed following calibration indicate difficulty in differentiating the scintillator response from ambient background light contamination at low doses (<20-25cGy) and dose rates (≤100 MU/min). However, when analysis was restricted to exclude dose values less than 10% of the Monte Carlo simulated max dose the average absolute percentage dose difference between Monte Carlo simulation and array measurement was 5.3%±4.8% for the fixed beam delivery and 5.4%±5.2% for the VMAT delivery CONCLUSION: In this study, we developed and characterized a 3D printed array of plastic scintillators and demonstrated a methodology for the dosimetric calibration of a simple array geometry.

Abstract B031: The effects of tissue processing and microfluidic factors on single-cell RNA-sequencing data quality in colorectal tissues

Abstract Our HTAN (Human Tumor Atlas Network) study presented in Chen et al. documented single-cell RNA-sequencing (scRNA-seq) data on 128 human colonic specimens for mapping out distinct paths for polyp to cancer transformations. What we have not detailed is our optimizations on the droplet-based scRNA-seq approach that generate high quality data from challenging tissues such as the colonic epithelium. In this work, we provide a systematic dissection of tissue processing and microfluidic encapsulation factors that affect data quality generated on colonic epithelial cells using an open droplet-based scRNA-seq platform (inDrops). We optimized our process based on these factors to significantly decrease dying cell bodies and ambient RNA from being co-encapsulated with true cells, which led to the development of the current scRNA-seq protocol used for human specimens. We have also developed pre-filtering data metrics to score data quality stemming from degree of ambient contamination. We envision that these experimental optimizations reduce the amount of introduced artifacts, leading to more rigorous biological interpretations. Citation Format: Deronisha L. Arceneaux, Zhengyi Chen, Joey Simmons, Bob Chen, Cody Heiser, Yanwen Xu. The effects of tissue processing and microfluidic factors on single-cell RNA-sequencing data quality in colorectal tissues [abstract]. In: Proceedings of the AACR Special Conference on Colorectal Cancer; 2022 Oct 1-4; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_1):Abstract nr B031.

The composition and structure of the ubiquitous hydrocarbon contamination on van der Waals materials

The behavior of single layer van der Waals (vdW) materials is profoundly influenced by the immediate atomic environment at their surface, a prime example being the myriad of emergent properties in artificial heterostructures. Equally significant are adsorbates deposited onto their surface from ambient. While vdW interfaces are well understood, our knowledge regarding atmospheric contamination is severely limited. Here we show that the common ambient contamination on the surface of: graphene, graphite, hBN and MoS2 is composed of a self-organized molecular layer, which forms during a few days of ambient exposure. Using low-temperature STM measurements we image the atomic structure of this adlayer and in combination with infrared spectroscopy identify the contaminant molecules as normal alkanes with lengths of 20-26 carbon atoms. Through its ability to self-organize, the alkane layer displaces the manifold other airborne contaminant species, capping the surface of vdW materials and possibly dominating their interaction with the environment.

Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets

Ambient RNA contamination in single-cell and single-nuclei RNA sequencing (snRNA-seq) is a significant problem, but its consequences are poorly understood. Here, we show that ambient RNAs in brain snRNA-seq datasets have a nuclear or non-nuclear origin with distinct gene set signatures. Both ambient RNA signatures are predominantly neuronal, and we find that some previously annotated neuronal cell types are distinguished by ambient RNA contamination. We detect pervasive neuronal ambient RNA contamination in all glial cell types unless glia and neurons are physically separated prior to sequencing. We demonstrate that this contamination can be removed in silico and show that previous single-nuclei RNA-seq-based annotations of immature oligodendrocytes are glial nuclei contaminated with ambient RNAs. After ambient RNA removal, we detect rare, committed oligodendrocyte progenitor cells not annotated in most previous adult human brain datasets. Together, these results provide an in-depth analysis of ambient RNA contamination in brain single-nuclei datasets.

(Digital Presentation) Where Are We in Terms of Energy Efficiency to Produce Green Ammonia – Electrochemical Synthesis of Ammonia Compared to Haber-Bosch Process

The electrochemical synthesis of ammonia, in the literature often found under the name Electrochemical Nitrogen Reduction Reaction (ENRR), might arise as an alternative to the green Haber-Bosch process in some market applications. In this work, we compare electrical energy efficiency (power-to-fuel efficiency) of the ENRR and the Haber-Bosch process.Not so long time ago, the ENRR was considered hardly possible to conduct, because there arose a doubt the literature is plagued by false-positive measurements. In ENRR measured ammonia concentrations were often within the range of ambient ammonia contamination. Some ENRR works produced ammonia by (unintentionally) reducing other, more reactive forms of nitrogen (NOx, nitrates, nitrites) or getting ammonia from a decomposition of the catalyst, while reporting reduction of inert dinitrogen to ammonia. Several rigorous experimental protocols were published during the last couple of years (from 2018), 1 , 2 , 3 , 4 , 5 and these made it easier to distinguish reliable results from the false-positive ones. In general, the ENRR reports that follow the rigorous synthesis protocols are considered valid. If they do not follow the protocols, but still produce ammonia concentrations which are far above contamination levels, the works are also considered valid.Taking a starting point in the reasoning above, we evaluated 120 articles and found out about 20% of ENRR works in the last three years are reliable. The result of this evaluation emphasizes that researchers should consider rigorous experimental protocols more seriously if they wish to stimulate progress in the field. We took the reliable works and evaluated them for power-to-fuel efficiency, by relating the low heating value of ammonia and total energy input to produce ammonia using ENRR.Our analysis shows that some of the reliable ENRR reports have power-to-fuel efficiency of a maximum 40% which is comparable to the current Haber-Bosch ammonia plants which are often in the range of 35-60%.6 Although energy efficiency of ENRR (40%) is lower than that of the modern Haber-Bosch plant (60%), such process would be probably relevant for the market where lower capital costs are more important than higher operating costs. About a third of the mostly reliable ENRR reports have energy efficiency between 20-35%. The others have less than 20% energy efficiency and need more improvements to be comparable with the Haber-Bosch process in terms of power-to-fuel efficiency. The results are surprising and show electrochemical synthesis of ammonia is maturing and can compete with the Haber-Bosch process, however, improvements are needed to bring the energy efficiency higher up. References (1) Suryanto, B. H. R.; Du, H.-L.; Wang, D.; Chen, J.; Simonov, A. N.; MacFarlane, D. R. Challenges and Prospects in the Catalysis of Electroreduction of Nitrogen to Ammonia. Nat. Catal. 2019, 2 (4), 290–296. https://doi.org/10.1038/s41929-019-0252-4.(2) Andersen, S. Z.; Čolić, V.; Yang, S.; Schwalbe, J. A.; Nielander, A. C.; McEnaney, J. M.; Enemark-Rasmussen, K.; Baker, J. G.; Singh, A. R.; Rohr, B. A.; Statt, M. J.; Blair, S. J.; Mezzavilla, S.; Kibsgaard, J.; Vesborg, P. C. K.; Cargnello, M.; Bent, S. F.; Jaramillo, T. F.; Stephens, I. E. L.; Nørskov, J. K.; Chorkendorff, I. A Rigorous Electrochemical Ammonia Synthesis Protocol with Quantitative Isotope Measurements. Nature 2019, 570 (7762), 504–508. https://doi.org/10.1038/s41586-019-1260-x.(3) Tang, C.; Qiao, S.-Z. How to Explore Ambient Electrocatalytic Nitrogen Reduction Reliably and Insightfully. Chem. Soc. Rev. 2019, 48 (12), 3166–3180. https://doi.org/10.1039/C9CS00280D.(4) Du, H.-L.; Gengenbach, T. R.; Hodgetts, R.; MacFarlane, D. R.; Simonov, A. N. Critical Assessment of the Electrocatalytic Activity of Vanadium and Niobium Nitrides toward Dinitrogen Reduction to Ammonia. ACS Sustain. Chem. Eng. 2019, 7 (7), 6839–6850. https://doi.org/10.1021/acssuschemeng.8b06163.(5) Greenlee, L. F.; Renner, J. N.; Foster, S. L. The Use of Controls for Consistent and Accurate Measurements of Electrocatalytic Ammonia Synthesis from Dinitrogen. ACS Catal. 2018, 8 (9), 7820–7827. https://doi.org/10.1021/acscatal.8b02120.(6) Smith, C.; K. Hill, A.; Torrente-Murciano, L. Current and Future Role of Haber–Bosch Ammonia in a Carbon-Free Energy Landscape. Energy Environ. Sci. 2020, 13 (2), 331–344. https://doi.org/10.1039/C9EE02873K.

Overview of research-based community noise testing recommendations from Brigham Young University

Brigham Young University has been studying questions related to NASA X-59 community noise testing. A summary of the key findings and recommendations to date are presented. Among these are weather-resistant ground microphone setups that reduce wind noise, methods for treating the problem of ambient noise contamination on sonic boom metrics and spectra, and the turbulence-induced variability seen over relatively small-aperture arrays. Also discussed are recommendations for data post-processing, e.g., employing a digital pole-shifting filter and zero-padding to improve the fidelity and smoothness of low-frequency spectral data. Finally, the relative merits of various sonic boom metrics are considered. Although Perceived Level has been the most widely-used metric, it is relatively sensitive to ambient noise contamination and turbulence-induced variability. [Work supported by NASA Langley Research Center through the National Institute of Aerospace.]

Contribution estimation of suspended particulate material levels in Ambient Air contamination

Abstract: This investigation has been carried out for evaluating the element's effect significance in ambient air and the environment distribution. The outdoor air measures were performed in winter for investigating probable sufficient particulate material PM exposure of various size aerosol RSPM and SPM. The element contamination measures were carried out at the Indian Institute of Technology campus in New Delhi regarded as a potential reference site for contamination investigation. The specimens have been accumulated outdoor on the third floor fifteen meters above the street for a twenty-one h period and the factors of Cr, Mn, Fe, Cu, Ni, Zn, and Pb have been calculated utilizing atomic adsorption spectroscopy analysis. The outcomes demonstrate that the RSPM and SPM fine mode or coarse mode ratio is 52.7 percent. The component concentration contribution in the site air contaminant is indicated fairly by the anthropogenic distribution in ambient air. The enrichment factors value for components Cr, Fe, Cu, Ni, Zn, and Pb probably derived from the anthropogenic emission resource, when the low enrichment element of Mn amount contributed to soil features distribution.