THC and CBD Fingerprinting of an Elite Cannabis Collection from Iran: Quantifying Diversity to Underpin Future Cannabis Breeding

Cannabis (Cannabis sativa L.) has a rich history of human use, and the therapeutic importance of compounds produced by this species is recognized by the medical community. The active constituents of cannabis, collectively called cannabinoids, encompass hundreds of distinct molecules, the most well-characterized of which are tetrahydrocannabinol (THC) and cannabidiol (CBD), which have been used for centuries as recreational drugs and medicinal agents. As a first step to establish a cannabis breeding program, we initiated this study to describe the HPLC-measured quantity of THC and CBD biochemistry profiles of 161 feral pistillate cannabis plants from 20 geographical regions of Iran. Our data showed that Iran can be considered a new region of high potential for distribution of cannabis landraces with diverse THC and CBD content, predominantly falling into three groups, as Type I = THC-predominant, Type II = approximately equal proportions of THC and CBD (both CBD and THC in a ratio close to the unity), and Type III = CBD-predominant. Correlation analysis among two target cannabinoids and environmental and geographical variables indicated that both THC and CBD contents were strongly influenced by several environmental–geographical factors, such that THC and CBD contents were positively correlated with mean, min and max annual temperature and negatively correlated with latitude, elevation, and humidity. Additionally, a negative correlation was observed between THC and CBD concentrations, suggesting that further studies to unravel these genotype × environment interactions (G × E interactions) are warranted. The results of this study provide important pre-breeding information on a collection of cannabis that will underpin future breeding programs.

Comparative Study of the Electrical, Thermal and Mechanical properties of Polypyrrole/CB/and Copper nano powder reinforced Polyester Hybrid Composites

The present research work based on Synthesis and characterization of Polypyrrole coated CB (carbon black), Copper, and VGCNF (vapor grown carbon nanofibers) hybrid composite. Two approaches were used comprising in situ polymerization of Polypyrrole/CB composite. The resulting composite was dispersed in with the measured quantity of Cu nano Powder and VGCNF in polyester at very high rate of dispersion to produced hybrid composite. The resulting composites were characterized by FTIR, electrical conductivity, mechanical properties, thermal analysis and UV visible spectroscopy.

Response time correction of slow response sensor data by deconvolution of the growth-law equation

Accurate, high resolution measurements are essential to improve our understanding of environmental processes. Several chemical sensors relying on membrane separation extraction techniques have slow response times due to a dependence on equilibrium partitioning across the membrane separating the measured medium (i.e., a measuring chamber) and the medium of interest (i.e., a solvent). We present a new technique for deconvolving slow sensor response signals using statistical inverse theory; applying a weighted linear least squares estimator with the growth-law as measurement model. The solution is regularized using model sparsity, assuming changes in the measured quantity occurs with a certain time-step, which can be selected based on domain-specific knowledge or L-curve analysis. The advantage of this method is that it: 1) models error propagation, providing an explicit uncertainty estimate of the response time corrected signal, 2) enables evaluation of the solutions self consistency, and 3) only requires instrument accuracy, response time, and data as input parameters. Functionality of the technique is demonstrated using simulated, laboratory, and field measurements. In the field experiment, the coefficient of determination (R2) of a slow response methane sensor in comparison with an alternative, fast response sensor, significantly improved from 0.18 to 0.91 after signal deconvolution. This shows how the proposed method can open up a considerably wider set of applications for sensors and methods suffering from slow response times due to a reliance on the efficacy of diffusion processes.

Antimicrobial Efficacy of a Novel Root Canal Irrigant Made from Coconut and Bromelain Extract against Biofilm Forming Pathogens– An In vitro Evaluation

Objective: Sodium hypochlorite is shown to be a gold standard intracanal irrigant which has shown to have adequate antimicrobial properties and tissue dissolving properties. The toxicity of these irrigants are seen to be high towards various cells. Natural irrigants provide an alternative to show adequate antimicrobial activity and lesser cytotoxicity potential. The current study proposes a novel intracanal irrigant made from coconut and bromelain extract. Material and Methods: 10grams of sodium hydroxide was dissolved in deionized water followed by which 60ml of coconut oil was added to the warm water bath (40C). The final product was left to dry and crushed manually to powder. This powder was then taken in measured quantity to make a final product containing 20% of coconut and 4% of bromelain. The obtained irrigant was then evaluated against Enterococcus faecalis using Agar well diffusion method. Results: For the natural irrigant, the maximum zone of inhibition was seen highest at 22mm against Enterococcus faecalis and 25mm against Candida Albicans. For 3% sodium hypochlorite when compared against Enterococcus faecalis and Candida Albicans showed a maximum zone of inhibition at 33mm against Enterococcus faecalis and 35mm against Candida Albicans. Conclusion: The study shows that the novel irrigant derived from coconut and bromelain extract has a good antimicrobial efficacy against Enterococcus faecalis and Candida albicans. It can be concluded that it has a potential application as a root canal irrigant for root canal disinfection.

SYSTEM-INFORMATION APPROACH TO UNCERTAINTY OF PROCESS AND SYSTEM PARAMETERS

The subject matter of research in the article is a system-information approach to the uncertainty of the parameters of processes and systems of the technosphere as one of the scientific directions of using information theory in metrology and other scientific areas. The system-information approach is based on the definition of the term "information" of the properties of the system, its content and meaning. The solution of the basic problem in metrology, obtaining "information" of the quantitative characteristics of the true value of the properties of objects and phenomena that reveal the regularities of the environment, is a complex scientific problem. The instrument for obtaining information about the properties of the system is the measurement process. One of the directions in the development of measurement theory is the concept of uncertainty. The goal of the work is to research of non-traditional solutions to problems of technical-cybernetic systems based on the system-information approach to the uncertainty of the parameters of processes and systems. The article solves the following tasks: to analyze the assessment of the parameters of technological processes and systems based on the system-information approach; to develop system-information methods and algorithms for the effective use of discrete-probabilistic information in technical-cybernetic systems; to develop principles and approaches for using the system-information assessment of the uncertainty of the Planck units, use of system-information modeling in various scientific directions. The following methods are used: system-information approach to processes and systems, methodology of system-information modeling of the measured value; system information methodology for the assessment of the measured quantity and uncertainty. The following results were obtained: developed a system-information methodology for assessing the nominal parameter has been developed, which provides indirect control over the independent parameters associated with it; systemic and information methods for the effective use of discrete-probabilistic information in technical and cybernetic systems have been developed; a system-information methodology for calculating the energy equivalent of product performance indicators has been developed; the principle of calculating the efficiency of manufacturing a product based on the energy equivalent of Planck units is formulated. Conclusions: The solution of the set tasks on the basis of the system-information approach to the uncertainty of the parameters of processes and systems makes it possible, from the system-information point of view, to study the regularities of the stages of the life cycle of technical-cybernetic systems and conservation laws.

The Selectivity of Immunoassays and of Biomimetic Binding Assays with Imprinted Polymers

Molecularly imprinted polymers have been shown to be useful in competitive biomimetic binding assays. Recent developments in materials science have further enhanced the capabilities of imprinted polymers. Binding assays, biological and biomimetic alike, owe their usefulness to their selectivity. The selectivity of competitive binding assays has been characterized with the cross-reactivity, which is usually expressed as the ratio of the measured IC50 concentration values of the interferent and the analyte, respectively. Yet this cross-reactivity is only a rough estimate of analytical selectivity. The relationship between cross-reactivity and analytical selectivity has apparently not been thoroughly investigated. The present work shows that this relationship depends on the underlying model of the competitive binding assay. For the simple but widely adopted model, where analyte and interferent compete for a single kind of binding site, we provide a simple formula for analytical selectivity. For reasons of an apparent mathematical problem, this formula had not been found before. We also show the relationship between analytical selectivity and cross-reactivity. Selectivity is also shown to depend on the directly measured quantity, e.g., the bound fraction of the tracer. For those cases where the one-site competitive model is not valid, a practical procedure is adopted to estimate the analytical selectivity. This procedure is then used to analyze the example of the competitive two-site binding model, which has been the main model for describing molecularly imprinted polymer behavior. The results of this work provide a solid foundation for assay development.

Changes in Alcohol Use during the COVID-19 Pandemic among Young Adults: The Prospective Effect of Anxiety and Depression

Health measures instantiated to reduce the spread of COVID-19 have imposed significant constraints for the population and impacted on drinking habits and mental health. This study longitudinally compared changes in alcohol consumption before and after the COVID-19 outbreak and the impact of sociodemographic and mental health variables on such changes among a community sample of young adults. Data were collected in the context of a larger, ongoing longitudinal study. The sample consisted of 305 young adults from Spain aged between 18 and 26 years (mean age = 21.27, (SD = 2.21), female = 53.4%; college students = 61.6%) who completed first (November-2019 and February-2020; i.e., before the outbreak of COVID-19) and second follow-up questionnaires (March 2021, a year after the COVID-19 outbreak). Alcohol use (quantity and drinking frequency), depression and anxiety symptoms were measured. Quantity and frequency of alcohol use decreased from the pre- to post-COVID-19 period. A decrease in drinking frequency was observed among college students, but not in noncollege peers. Although we found no effect of pre-COVID-19 anxiety on alcohol use changes, those with more depressive symptoms at the pre-COVID assessment were more resistant to decreasing their drinking quantity and frequency after the COVID-19 outbreak. This information will be of value when designing interventions aimed at reducing harmful alcohol use and highlights the role of mental health status when identifying high risk populations of young-adults during this, and future, public health crises.

On incoherent diffractive imaging

Incoherent diffractive imaging (IDI) promises structural analysis with atomic resolution based on intensity interferometry of pulsed X-ray fluorescence emission. However, its experimental realization is still pending and a comprehensive theory of contrast formation has not been established to date. Explicit expressions are derived for the equal-pulse two-point intensity correlations, as the principal measured quantity of IDI, with full control of the prefactors, based on a simple model of stochastic fluorescence emission. The model considers the photon detection statistics, the finite temporal coherence of the individual emissions, as well as the geometry of the scattering volume. The implications are interpreted in view of the most relevant quantities, including the fluorescence lifetime, the excitation pulse, as well as the extent of the scattering volume and pixel size. Importantly, the spatiotemporal overlap between any two emissions in the sample can be identified as a crucial factor limiting the contrast and its dependency on the sample size can be derived. The paper gives rigorous estimates for the optimum sample size, the maximum photon yield and the expected signal-to-noise ratio under optimal conditions. Based on these estimates, the feasibility of IDI experiments for plausible experimental parameters is discussed. It is shown in particular that the mean number of photons per detector pixel which can be achieved with X-ray fluorescence is severely limited and as a consequence imposes restrictive constraints on possible applications.

Design of experiments: a statistical tool for PIV uncertainty quantification

A statistical tool called Design of Experiments (DOE) is introduced for uncertainty quantification in particle image velocimetry (PIV). DOE allows to quantify the total uncertainty as well as the systematic uncertainties arising from various experimental factors. The approach is based on measuring a quantity (e.g. time-averaged velocity from PIV) several times by varying the levels of the experimental factors which are known to affect the value of the measured quantity. In this way, using Analysis of Variances (ANOVA), the total variance in the measured quantity can be computed and hence the total uncertainty. Moreover, the analysis provides the individual variances for each of the experimental factors leading to the estimation of the systematic uncertainties from each factor and their contribution to the total uncertainty. The methodology is assessed for an experimental test case of the flow at the outlet of a ducted Boundary Layer Ingesting (BLI) propulsor to quantify the total uncertainty in time-averaged velocity from stereoscopic PIV measurements as well as the constituent systematic uncertainties due to the experimental factors, namely, camera aperture, inter-frame time separation, interrogation window size and stereoscopic camera angle.

Influence of the Dista nce of Transportation of Goods on Operating Costs of a Motor Transport Enterprise

The object of research is the transportation process. The subject of research is dependence of influence of the distance of transportation of goods on the cost of transportation of goods. Since no studied literary sources have revealed reliable dependences of influence of the distance of transportation on the cost of transportation of goods in specific conditions for a single enterprise, the research task considered in the article seems to be relevant.The objective of this article is so to study the impact of distance of transportation of construction goods by dump trucks of Volgograd motor transport enterprise on operating costs. The solution to the problem is considered at the example of transportation of bulk cargo by MAN and Mercedes-Benz dump trucks with equal mileage. Several empirical research methods were used: observation (by means of purposeful perception of an object determined by the task of activity), comparison (by establishing similarity and difference between objects and phenomena of reality), measurement (by means of actions performed using measuring instruments to find the numerical value of the measured quantity in the adopted measurement units). To calculate the cost of transportation, the methodology for determining costs for transporting goods by road transport is used. To obtain experimental data, an analysis of the work of fleet of a motor transport enterprise is carried out using waybills with confirmed data. The process of obtaining actual data is carried out by means of calculations according to the given formulas. The research tool is calculation of the cost of transportation of goods according to the data obtained as a result of activities of the enterprise.Regression dependences of influence of the distance of transportation of goods on the cost of operation of dump trucks with different carrying capacity were obtained to determine the type of the regression equation, construct estimates of unknown parameters included in the regression equation, and test statistical hypotheses about regression. The verification of the adequacy of obtained models was performed by calculating the correlation coefficient to establish the presence of a connection between random variables.