Validation of an ultra performance liquid chromatography tandem mass spectrometry (UPLC™/MS/MS) method for forensic toxicological analysis : Confirmation and quantitation of lysergic acid diethylamide (LSD) and its congeners in forensic samples

The Royal Canadian Mounted Police (RCMP) Forensic Laboratory Services (FLS) needed a method to confirm positive lysergic acid diethylamide (LSD) immunoassay screening results. As a result, an ultra performance liquid chromatography tandem mass spectrometry (UPLC™/MS/MS) method was validated for the confirmation and quantitation of LSD, iso-LSD, N-demethyl-LSD (nor-LSD), and 2-oxo-3-hydroxy-LSD (O-H-LSD). The method was validated in urine and whole blood, where linearity, accuracy, precision, sensitivity, stability, selectivity, recovery, matrix effects, and reproducibility were evaluated. The method involved a liquid-liquid extraction (LLE) of the analytes and the deuterated internal standard from 1 mL of urine or whole blood with dichloromethane:isopropyl alcohol after being basified. The average recovery for all analytes was ≥ 62%, and the matrix effect was found to be insignificant. MS/MS analysis was conducted with a triple quadrupole mass spectrometer by positive electrospray ionization (ESI+) in multiple reaction monitoring (MRM) mode. The lowest limit of quantitation (LLOQ) was 20 pg/mL for LSD and iso-LSD, and 50 pg/mL for nor-LSD and O-H-LSD. The method was linear, accurate, precise, selective, and reproducible from 20 to 2000 pg/mL for LSD and iso-LSD, and from 50 to 2000 pg/mL for nor-LSD and O-H-LSD with an r² ≥ 0.99. The refrigerated and frozen long term stability was investigated for 90 days. LSD was stable at all temperatures for 90 days. Iso-LSD in blood was also stable at all temperatures for 90 days, but iso-LSD in urine showed an initial decrease followed by a gradual increase back to day 0 concentrations. Nor-LSD was stable at all temperatures up to day 14, with >43% decrease by day 30, with no additional decrease for the next 60 days. O-H-LSD in urine was stable at all temperatures for 90 days, but by day 90 O-H-LSD in whole blood stored refrigerated decreased in concentration by >37%. Additionally, a case sample that was stored at -50°C for ten years was found to still contain measurable amounts of each compound. The method was applied to blind samples and a case that screened positive with immunoassay. Retention time, relative retention time, and ion ratios were used as identification parameters and found to correctly identify the analytes 100% of the time with no false positives. The case sample showed that the concentration of O-H-LSD was 4 times greater than LSD in urine. Furthermore, both the detection of O-H-LSD in a blood case sample, and LSD in a vitreous humor case sample were the first to be documented

NASA Global Satellite and Model Data Products and Services for Tropical Cyclone Research

The lack of observations over vast tropical oceans is a major challenge for tropical cyclone research. Satellite observations and model reanalysis data play an important role in filling these gaps. Established in the mid-1980s, the Goddard Earth Sciences Data and Information Services Center (GES DISC), as one of the 12 NASA data centers, archives and distributes data from several Earth science disciplines such as precipitation, atmospheric dynamics, atmospheric composition, and hydrology, including well-known NASA satellite missions (e.g., TRMM, GPM) and model assimilation projects (MERRA-2). Acquiring datasets suitable for tropical cyclone research in a large data archive is a challenge for many, especially for those who are not familiar with satellite or model data. Over the years, the GES DISC has developed user-friendly data services. For example, Giovanni is an online visualization and analysis tool, allowing users to visualize and analyze over 2000 satellite- and model-based variables with a Web browser, without downloading data and software. In this chapter, we will describe data and services at the GES DISC with emphasis on tropical cyclone research. We will also present two case studies and discuss future plans

Impulse Response of Civil Structures from Ambient Noise Analysis

Increased monitoring of civil structures for response to earthquake motions is fundamental to reducing seismic risk. Seismic monitoring is difficult because typically only a few useful, intermediate to large earthquakes occur per decade near instrumented structures. Here, we demonstrate that the impulse response function (IRF) of a multistory building can be generated from ambient noise. Estimated shear-wave velocity, attenuation values, and resonance frequencies from the IRF agree with previous estimates for the instrumented University of California, Los Angeles, Factor building. The accuracy of the approach is demonstrated by predicting the Factor building’s response to an M 4.2 earthquake. The methodology described here allows for rapid, noninvasive determination of structural parameters from the IRFs within days and could be used for state-of-health monitoring of civil structures (buildings, bridges, etc.) before and/or after major earthquakes

A REINVESTIGATION OF THE ELECTRONIC PROPERTIES OF 2-BROMOPYRIDINE WITH HIGH-RESOLUTION MICROWAVE SPECTROSCOPY

The rotational spectrum of 2-bromopyridine (ce{C5H4BrN}) was reinvestigated in the frequency range of 10-15.5 GHz by high-resolution Fourier transform microwave (FTMW) spectroscopy. The new observations of $^{14}$ce{N} hyperfine splittings in previously studied transitionsfootnote{Caminati, W.; Forti, P. textit{Chemical Physics Letters} textbf{1972}, textit{15}(3), 343–349.} belonging to both bromine isotopologues (ce{C5H4}$^{79}$ce{BrN} and ce{C5H4}$^{81}$ce{BrN}) led to improved measurements of the rotational constants and bromine nuclear quadrupole coupling constants. The full nuclear quadrupole coupling (NQC) tensor of $^{14}$ce{N} was resolved for the first time, in addition to five centrifugal distortion constants. A comparison of the two $^{14}$ce{N} NQC tensors of ce{C5H4}$^{79}$ce{BrN} and ce{C5H4}$^{81}$ce{BrN} will be presented. _x000d_ _x000d_ _x000d

Post Traumatic Stress and Externalizing Behaviors in At Risk Urban Adolescents: A Prospective Study

Adolescents in in urban areas are at a higher risk for experiencing direct victimization as well as witnessing violence directed towards others, which increases the amount of post-traumatic stress (PTS) they face (Joseph, S., Mynard, H., & Mayall, M. 2000). Experiencing Post Traumatic Stress Disorder (PTSD) has been associated with a number of negative externalizing behaviors, such as increased delinquency, drug use and aggressive behavior in adolescents (Dierkhising, C. B., Ko, S. J., Woods-Jaeger, B., Briggs, E. C., Lee, R., & Pynoos, R. S. 2013). This association is especially relevant, as adolescence is a stage where youth are beginning to experiment and form life-long habits to manage life stressors. However, previous research has been limited regarding gender differences in PTS as males and females often have different ways of coping with traumatic events (Stevens, Murphy, & McKnight, 2003). This study closes this gap by investigating the connection between PTS and externalizing behaviors in the form of delinquency, drug use, and aggression in a sample of urban, predominantly African American adolescents. Data for this study comes from the first two waves of Project COPE, a four-year longitudinal study on violence exposure, stress responses and adjustment who were recruited from low SES neighborhoods in Richmond, Virginia. The sample included 166 males (46.4%) and 192 females (53.6%), all of whom were in grades five or eight and between the ages of nine and sixteen (M=12.13, SD=1.62) at wave 1 of the study. The participants consisted primarily of African Americans (91%). During annual in home interviews, participants provided assessments of PTS using the Trauma Symptom Checklist for Children (TSCC) scale, and delinquency, aggressive behavior and drug use were assessed using the Problem Behavior Frequency Scales (PBFS). Linear regression analyses were conducted with and without gender as moderator. Results from this sample found no significant relationship between PTS and Delinquency (Beta=.074, p\u3e.05) or Drug use (Beta=.035, p\u3e.05) one year later. However, a significant relationship was found between PTS and aggressive behavior at year two (Beta=.185, p\u3c.05). Interactions with gender revealed that the patterns of association between PTS and aggressive behavior were similar for males and females. Contrary to previous research, our results show no increased risk of drug use or rule-breaking behavior in this sample of adolescents from high violence neighborhoods, for either males or females. It is possible that the effects were short-term in this case rather than lasting. However, the significant relationship of PTS with increased physical aggression for all youth sheds light on possible long-term consequences of PTS and underscores a need to address this specific risk in low SES, urban samples with high prevalence of PTS. The data from our research further adds to the existing consensus suggesting that low SES, urban adolescents, due to unavailable resources, has the possibility of behaviors reemerging as delinquent behaviors.https://scholarscompass.vcu.edu/uresposters/1179/thumbnail.jp

Efficient and Accurate CORDIC Pipelined Architecture Chip Design Based on Binomial Approximation for Biped Robot

Recently, much research has focused on the design of biped robots with stable and smooth walking ability, identical to human beings, and thus, in the coming years, biped robots will accomplish rescue or exploration tasks in challenging environments. To achieve this goal, one of the important problems is to design a chip for real-time calculation of moving length and rotation angle of the biped robot. This paper presents an efficient and accurate coordinate rotation digital computer (CORDIC)-based efficient chip design to calculate the moving length and rotation angle for each step of the biped robot. In a previous work, the hardware cost of the accurate CORDIC-based algorithm of biped robots was primarily limited by the scale-factor architecture. To solve this problem, a binomial approximation was carefully employed for computing the scale-factor. In doing so, the CORDIC-based architecture can achieve similar accuracy but with fewer iterations, thus reducing hardware cost. Hence, incorporating CORDIC-based architecture with binomial approximation, pipelined architecture, and hardware sharing machines, this paper proposes a novel efficient and accurate CORDIC-based chip design by using an iterative pipelining architecture for biped robots. In this design, only low-complexity shift and add operators were used for realizing efficient hardware architecture and achieving the real-time computation of lengths and angles for biped robots. Compared with current designs, this work reduced hardware cost by 7.2%, decreased average errors by 94.5%, and improved average executing performance by 31.5%, when computing ten angles of biped robots

Customer Churn Prediction of Telecom Company Using Machine Learning Algorithms

We can’t escape the fact that using telecommunications has become a significant part of our everyday lives. Since the Covid-19 pandemic, the telecommunication industry has become crucial.  Hence, the industry now enjoys growth opportunities. In this study, KNN, Random Forest (RF), AdaBoost, Logistic Regression (LR), XGBoost, and Support Vector Machine (SVM) are 6 supervised machine learning algorithms that will be used in this study to predict the customer churn of a telecom company in California. The goal of this study is to identify the classifier that predicts customer churn the most effectively. As evidenced by its accuracy of 79.67%, precision of 64.67%, recall of 51.87%, and F1-score of 57.57%, XGBoost is the overall most effective classifier in this study. Next, the purpose of this study is to identify the characteristics of customers who are most likely to leave the telecom company. These characteristics were discovered based on customers’ demographics and account information. Lastly, this study also provides the company with advice on how to retain customers. The study advises company to personalize the customer experience, implement a customer loyalty program, and apply AI in customer relationship management in retaining customers