Extrapolation Research Articles

Methodological Considerations Regarding the Quantification of DNA Impurities in the COVID-19 mRNA Vaccine Comirnaty®.

DNA impurities can impact the safety of genetically engineered pharmaceuticals; thus, a specific limit value must be set for them during marketing authorisation. This particularly applies to mRNA vaccines, as large quantities of DNA templates are used for their production. Furthermore, when quantifying the total DNA content in the final product, we must observe that, in addition to the mRNA active ingredient, DNA impurities are also encased in lipid nanoparticles and are therefore difficult to quantify. In fact, the manufacturer of the mRNA vaccine Comirnaty (BioNTech/Pfizer) only measures DNA impurities in the active substance by means of a quantitative polymerase chain reaction (qPCR), whose DNA target sequence is less than just 1% of the originally added DNA template. This means that no direct DNA quantification takes place, and compliance with the limit value for DNA contamination is only estimated from the qPCR data using mathematical extrapolation methods. However, it is also possible to dissolve the lipid nanoparticles with a detergent to directly measure DNA contamination in the final product by using fluorescence spectroscopic methods. Experimental testing of this approach confirms that reliable values can be obtained in this way.

The Role of Forecasts in Planning for Energy Infrastructure: A Historical Look at Past Futures in Postwar Quebec

The Role of Forecasts in Planning for Energy Infrastructure: A Historical Look at Past Futures in Postwar Quebec

Моделирование ожидаемого предотвращенного ущерба в энергетике. Часть 1. Детерминированный подход

Inspection control and supervisory activities are one of the important mechanisms of proactive industrial safety. Corporate control ensures early detection of security violations and their prompt elimination to prevent accidents. The expected prevented damage at hazardous production facilities is considered one of the efficiency factors of inspection activities. In order to assess the expected prevented damage (direct or indirect), the number of expected incidents and damage for each event must be calculated. An approach to the assessment of the number of prevented events based on the pyramid of incidents (Heinrich’s pyramid, Berd’s pyramid) by supplementing it with the level of detected violations has been proposed. The number of prevented incidents can be assessed within the framework of deterministic and scholastic approaches. The study focuses mainly on building and analysis of the ratio of the number of incidents between different levels of the pyramid within the framework of the deterministic approach. The accident statistics at oil and gas industry facilities has been analyzed; Heinrich’s hypothesis regarding the type of dependence between the pyramid levels has been tested; and coefficients of the injury rate pyramid have been determined. To find the final coefficients of the improved pyramid of an oil and gas company, the method of coefficient calculation with accumulations for each year has been chosen. It has been demonstrated that traditional values of coefficients of Heinrich’s pyramid and those obtained as a result of calculations do not comply, which can be explained by the significant difference in industrial technologies and efficiency of occupational safety measures as of today and at the moment of initial building of Heinrich’s pyramid. Based on the regression analysis and other forecasting methods (the Holt method, the Brown exponential smoothing method, the ARIMA model, and the moving average extrapolation method), modeling and forecasting injury rate factors have been conducted. The comparative analysis of methods to forecast the number of accidents has been carried out. It has been shown that it is advisable to apply the linear regression model to predict injury rates.

Spatially explicit downscaling and projection of population in mainland China

Spatially explicit population data is critical to investigating human-nature interactions, identifying at-risk populations, and informing sustainable management and policy decisions. Most long-term global population data have three main limitations: 1) they were estimated with simple scaling or trend extrapolation methods which are not able to capture detailed population variation spatially and temporally; 2) the rate of urbanization and the spatial patterns of settlement changes were not fully considered; and 3) the spatial resolution is generally coarse. To address these limitations, we proposed a framework for large-scale spatially explicit downscaling of populations from census data and projecting future population distributions under different Shared Socio-economic Pathways (SSP) scenarios with the consideration of distinctive changes in urban extent. We downscaled urban and rural population separately and considered urban spatial sprawl in downscaling and projection. Treating urban and rural populations as distinct but interconnected entities, we constructed a random forest model to downscale historical populations and designed a gravity-based population potential model to project future population changes at the grid level. This work built a new capacity for understanding spatially explicit demographic change with a combination of temporal, spatial, and SSP scenario dimensions, paving the way for cross-disciplinary studies on long-term socio-environmental interactions.

Physiochemical study of 1-methyl imidazole trifluoro methane sulfonate ionic liquid in aqueous and aqueous amino acid solutions at different temperatures

The experimental density and speed of sound of 1-methyl imidazole trifluoro methane sulfonate ionic liquid in aqueous binary ([MIm][OTf]+H2O) solution and aqueous ternary ([MIm][OTf] + 0.05 mol.kg−1 aqueous glycine) solution are reported in the dilute concentration range (0.06 to 0.16 mol.kg−1) at the temperature between 288.15 and 318.15 K with 5K interval and at atmospheric pressure. These density (ρ) and speed of sound (u) data are utilized to derive various significant thermophysical parameters namely apparent molar volume of solute (Vϕ), isentropic compressibility of solution (κs) and apparent molar isentropic compressibility of solute (KS,ϕ). The limiting apparent molar volume (Vϕ0) and limiting apparent molar isentropic compressibility (KS,ϕ0) of [MIm][OTf] are estimated by extrapolation methods. By using Vϕ0and KS,ϕ0data of the studied binary and ternary systems, the values of transfer volumes i.e. volume changes due to transfer (ΔtrVϕ0)and transfer compressibility i.e. compressibility changes due to transfer(ΔtrKsϕ0) from aqueous to aqueous amino acid solution are estimated. The observed ΔtrVϕ0and ΔtrKsϕ0values are temperature dependent. The outcomes of this investigation are framed within the context of solute-solute and solute-solvent interactions.

Negative Impacts of the High-Tech Implementation in the Russian Higher Education Sector

Introduction. The institute of education in modern society is currently in the process of serious transformation associated with the large-scale introduction of high technologies, which is due to a similar process in post-industrial society as a whole. There is a growing understanding of the negative consequences of digitalization of society and education along with the understanding of the objective necessity of such transformation. The article contains an analysis of the negative consequences and problems arising in the course of the spread of digitalization of higher education in Russia. Methodology and sources. The methodology of the research is based on the methods of comparative analysis and extrapolation of transformations of social environment and anthropological factors under the influence of technological progress in the field of higher education. The signs of “high technology poisoning” considered by J. Naisbitt in his book “High Tech – High Touch: Technology and Our Search for Meaning” and the concept of extensive and intensive types of creativity formulated by A.I. Stoletov are a conceptual basis for analyzing the impact of high technology on education. Results and Discussion. Seven symptoms of technological poisoning in higher education, representing the main risks of the modern educational system, their manifestations in the educational process and prospects in case the existing trend persists, have been considered. One of the sources of manifestation of these symptoms is the extensive character of creativity inherent in scientific and technological activity of the society, which stakes on innovative development and mastering of material aspects of nature. The technogenic character of the emerging innovation process levels out the activities associated with the intensive type of creativity, aimed at the meaning-creating and existential aspects of human existence. Conclusion. Minimization of negative consequences presupposes the strengthening of the humanitarian component in education, allowing to form a culture of “pause of contemplation” (Grigory Pomerantz), in which technology will acquire, as it was suggested by J. Naisbitt himself, a fullness of meaning that goes beyond instrumental values into the realm of ethical and existential ones.

Use of quantitative in vitro to in vivo extrapolation (QIVIVE) for the assessment of non-combustible next-generation product aerosols.

With the use of in vitro new approach methodologies (NAMs) for the assessment of non-combustible next-generation nicotine delivery products, new extrapolation methods will also be required to interpret and contextualize the physiological relevance of these results. Quantitative in vitro to in vivo extrapolation (QIVIVE) can translate in vitro concentrations into in-life exposures with physiologically-based pharmacokinetic (PBPK) modelling and provide estimates of the likelihood of harmful effects from expected exposures. A major challenge for evaluating inhalation toxicology is an accurate assessment of the delivered dose to the surface of the cells and the internalized dose. To estimate this, we ran the multiple-path particle dosimetry (MPPD) model to characterize particle deposition in the respiratory tract and developed a PBPK model for nicotine that was validated with human clinical trial data for cigarettes. Finally, we estimated a Human Equivalent Concentration (HEC) and predicted plasma concentrations based on the minimum effective concentration (MEC) derived after acute exposure of BEAS-2B cells to cigarette smoke (1R6F), or heated tobacco product (HTP) aerosol at the air liquid interface (ALI). The MPPD-PBPK model predicted the in vivo data from clinical studies within a factor of two, indicating good agreement as noted by WHO International Programme on Chemical Safety (2010) guidance. We then used QIVIVE to derive the exposure concentration (HEC) that matched the estimated in vitro deposition point of departure (POD) (MEC cigarette = 0.38 puffs or 11.6µg nicotine, HTP = 22.9 puffs or 125.6µg nicotine) and subsequently derived the equivalent human plasma concentrations. Results indicate that for the 1R6F cigarette, inhaling 1/6th of a stick would be required to induce the same effects observed in vitro, in vivo. Whereas, for HTP it would be necessary to consume 3 sticks simultaneously to induce in vivo the effects observed in vitro. This data further demonstrates the reduced physiological potency potential of HTP aerosol compared to cigarette smoke. The QIVIVE approach demonstrates great promise in assisting human health risk assessments, however, further optimization and standardization are required for the substantiation of a meaningful contribution to tobacco harm reduction by alternative nicotine delivery products.

Masses of the conjectured H-dibaryon at different temperatures*

Abstract We present a lattice QCD determination of masses of the conjectured H-dibaryon, denoted as , at nine different temperatures: 0.24, 0.63, 0.76, 0.84, 0.95, 1.09, 1.27, 1.52, and 1.90. The masses of baryons N, Σ, Ξ, and Λ at different temperatures were also computed. The simulations were performed on an anisotropic lattice with flavours of clover fermion at a quark mass corresponding to . The thermal ensembles were provided by the FASTSUM collaboration, whereas the zero temperature ensembles were provided by the Hadspec collaboration. We also calculated the spectral density of the correlation function of those particles. The spectral density distributions show a rich peak structure at the lowest temperature; at intermediate temperatures, the mass values of those particles obtained by the extrapolation method reflect a two-peak structure. While the spectral density for the octet baryon becomes smooth at 1.27, 1.52, and 1.90, the spectral density for the H-dibaryon becomes smooth at . At , the mass difference of the H-dibaryon and Λ pair, expressed as , was estimated to be MeV, which suggests the existence of a bound H-dibaryon state.

Краткосрочное и среднесрочное прогнозирование стока рек бассейна Дона

For the rivers of the Don basin, the Hydrometcentre of Russia has developed a methodology for daily short- and medium-range forecasting of streamflow and water levels. Average daily discharges and water levels are predicted throughout the year with a lead time of 1 to 10 days based on the hydrograph extrapolation method, which takes into account their values for the date of the forecast and for the previous 5 days. To estimate the parameters of the forecasting scheme, hydrological observation data for each river section are used. The technique gives satisfactory results and can be used within the framework of an automated system for preparing and issuing forecasts in order to provide necessary forecast information for making operational decisions on the use of water resources of the Don basin rivers and protecting the population from dangerous floods.

Further insights into steady three-dimensional MHD Sakiadis flows of radiating-reacting viscoelastic nanofluids via Wakif’s-Buongiorno and Maxwell’s models

AbstractKeeping in mind the stress relaxation tendency of many viscoelastic multi-phase flows (e.g., polymer solution flows and transport phenomena of red cell suspensions within blood media), the present research investigation intends principally to develop a realistic model for revealing properly the aspects of reacting-radiating Maxwell nanofluids during their laminar boundary layer flows in the steady regime over a horizontal impermeable surface under a transversal magnetic influence. For this purpose, the principal leading differential formulation is derived theoretically by linking Wakif’s-Buongiorno approach with Maxwell’s model. By invoking fundamentally the general boundary layer assumptions and the passive control strategy for the nanoparticles, the governing PDEs’ formulation is simplified accordingly and then stated properly for the case of the convective heating condition at the impermeable bi-stretching surface. By executing a feasible non-dimensionalization technique, the monitoring ODEs’ system is achieved successfully, whose solutions are presented precisely in different illustrative scenarios using Richardson’s extrapolation method. After carrying out successfully several validating tests, it is demonstrated that the weakly viscoelastic feature has generally a slight delaying effect on the nanofluid motion. This dynamical weakening can be reinforced more with the generation of thermal energy by intensifying the external magnetic field source. Additionally, these physical factors show an intensifying influence on the surface drag forces. However, a dropping impression is seen for the local heat transfer at the contact surface. Contrary to the broadening impact of the radiative heat transfer as well as the convective heating and thermophoresis mechanisms on the thermal and mass boundary layer regions, it is witnessed that the first-order chemical reaction mechanism and Brownian’s motion exhibit a shrinking impact on the mass boundary layer region.

Long-period oscillations in the lower solar atmosphere prior to flare events

Multiple studies have identified a range of oscillation periods in active regions, from 3-5 minutes to long-period oscillations that last from tens of minutes to several hours. Recently, it was also suggested that these periods are connected with eruptive activity in the active regions. Thus, it is essential to understand the relation between oscillations in solar active regions and their solar eruption activity. We investigate the long-period oscillations of NOAA12353 prior to a series of C-class flares and correlate the findings with the 3- to 5-minute oscillations that were previously studied in the same active region. The objective of this work is to elucidate the presence of various oscillations with long periods in the lower solar atmosphere both before and after the flare events. To detect long-period oscillations, we assessed the emergence, shearing, and total magnetic helicity flux components from the photosphere to the top of the chromosphere. To analyze the magnetic helicity flux in the lower solar atmosphere, we used linear force-free field extrapolation to construct a model of the magnetic field structure of the active region. Subsequently, the location of long-period oscillations in the active region was probed by examining the spectral energy density of the measured intensity signal in the 1700\,AA , 1600\,AA , and 304\,AA channels of the Atmospheric Imaging Assembly (AIA) of the Solar Dynamics Observatory (SDO). Significant oscillation periods were determined by means of a wavelet analysis. Based on the evolution of the three magnetic helicity flux components, 3- to 8-hour periods were found both before and after the flare events, spanning from the photosphere to the chromosphere. These 3- to 8-hour periods were also evident throughout the active region in the photosphere in the 1700\,AA channel. Observations of AIA 1600\,AA and 304\,AA channels, which cover the chromosphere to the transition region, revealed oscillations of 3-8 hours near the region in which the flare occurred. The spatial distribution of the measured long-period oscillations mirror the previously reported distribution of 3- to 5-minute oscillations in NOAA12353 that were seen both before and after the flares. This case study suggest that the varying oscillation properties in a solar active region could be indicative of future flaring activity.

Synergistic bifunctionality of ZnO nanowalls: Antibacterial activity and photocatalysis through integrated in silico and in vitro approaches

This research investigation delves into the versatile attributes of ZnO nanowalls, specifically probing into their dual functionality encompassing antibacterial and photocatalytic properties. The synthesis of ZnO was achieved by employing a microwave-mediated co-precipitation technique. The resulting sample underwent thorough characterization through diverse analytical methodologies. X-ray diffraction analysis disclosed the prevalence of the hexagonal wurtzite phase, as confirmed by JCPDS card No. 36–1451, with an average crystallite size determined as 23.48 nm. Tauc plot extrapolation method was applied to the UV absorption spectrum to ascertain the bandgap energy. The ZnO nanostructure morphology, featuring multi-directional nano-walls, was unveiled through scanning electron microscopy (SEM). The BET nitrogen adsorption technique quantified the surface area of the ZnO sample as 6.69 m2/g. In antibacterial evaluation, the in vitro (disk diffusion) method showcased the remarkable efficacy of ZnO against both gram-positive Staphylococcus sp. and gram-negative E. coli bacteria. Complementing these experimental findings, in silico molecular docking studies exposed both nano ZnO ligands with standard and corrected lattice parameter values exhibiting favorable binding energy. Moreover, the synthesized ZnO nanoparticles exhibited remarkable photocatalytic activity, particularly demonstrated in the decolorisation of Azure A and Azure B dyes, following the first-order Langmuir–Hinshelwood kinetic model. The collective findings underscored a synergistic effect within the fabricated ZnO nanoparticles, showcasing their dual prowess in both antibacterial and photocatalytic activities. The observed phenomenon can be chiefly ascribed to the presence of lattice strain and dislocation density. This intriguing dual functionality positions them as promising candidates for potential applications in wastewater treatment.

A Review on Unlocking Toxicity: How Zebrafish embryos Help Ensure Safe Chemicals

Aquatic ecotoxicity testing has benefited greatly from zebrafish embryo toxicity testing (ZFET) because of its high throughput, low cost, sensitivity to a variety of toxicants, and ethical issues. This study highlights the benefits of ZFET over conventional fish toxicity testing, such as its capacity to detect teratogenic defects and possible long-term impacts. The limitations of ZFET are also addressed, notably its emphasis on acute dosages and difficulties with interspecies extrapolation. In addition to the generation of in vitro alternatives utilizing zebrafish cell lines, recent developments in ZFET technology are also highlighted, including the use of transgenic zebrafish lines and high-throughput screening techniques. The paper's conclusion includes a discussion of potential prospects for ZFET research. These include improving interspecies extrapolation methods, optimizing chronic toxicity assessment procedures, and integrating ZFET with other ecotoxicity testing strategies. ZFET is a great instrument for environmental protection and a crucial component in avoiding chemical contamination of aquatic ecosystems, so long as it is acknowledged for what it is and is open to future improvement

ORGANISATION OF MARKETING ACTIVITIES IN AGRICULTURAL ENTERPRISES

The aim of the article is to identify the characteristics of the introduction and development of marketing activities in agricultural enterprises in order to increase the efficiency of their activities. Methodology. The theoretical and methodological basis of the study is a systematic approach to the study of economic phenomena and processes related to the marketing activities of agricultural enterprises. In formulating theoretical generalisations and formulating conclusions and proposals, the paper uses historical, abstract and logical, and monographic methods. Forecasting of indicators characterising the marketing potential of enterprise in the context of increasing labour productivity at enterprises, market parameters and substantiation of the choice of marketing strategy of agricultural producers is carried out using the methods of extrapolation and economic forecasting. The article uses general scientific and special research methods: abstraction and comparison, analysis and synthesis, graphical methods, deduction, economic and mathematical modelling, observation and comparison, and the logical method. The results of the study show that marketing instruments include methods of its implementation, i.e., advertising, sales, customer service, pricing policy, study of needs and demand, communication with consumers and the public. Calculation of a comprehensive indicator of efficiency of marketing activity of enterprises is an important direction of assessment of the status and level of development of the marketing complex at enterprise. The indicator makes it possible to promptly identify and eliminate deviations in achieving goals and fulfilling tasks, which affects the overall performance of the enterprise. The results of the study are presented in the form of tables, graphs, diagrams, and charts. Practical implications. Since the marketing activity of an agricultural enterprise is multifaceted, it is necessary to evaluate its effectiveness in the following areas: efficiency of implementation of marketing functions, implementation of the marketing complex and use of marketing resources. In order to assess the level of efficiency of marketing activities, it is necessary to analyse both strategic and tactical aspects of the agricultural enterprise. Value/originality. An important component of ensuring marketing activities in the agricultural market is the communication policy of the enterprise. A modern system for assessing the effectiveness of marketing activities should take into account the possibility of disseminating information via the Internet, which is an indispensable tool for obtaining up-to-date marketing information.

Revisiting influenza-hospitalisation estimates from the Burden of Influenza and Respiratory Syncytial Virus Disease (BIRD) project using different extrapolation methods.

Revisiting influenza-hospitalisation estimates from the Burden of Influenza and Respiratory Syncytial Virus Disease (BIRD) project using different extrapolation methods.

Extending the wind profile beyond the surface layer by combining physical and machine learning approaches

Abstract. Accurate estimation of the wind profile, especially in the lowest few hundred meters of the atmosphere, is of great significance for the weather, climate, and renewable energy sector. Nevertheless, the Monin–Obukhov similarity theory fails above the surface layer over a heterogeneous underlying surface, causing an unreliable wind profile to be obtained from conventional extrapolation methods. To solve this problem, we propose a novel method called the PLM-RF method that combines the power-law method (PLM) with the random forest (RF) algorithm to extend wind profiles beyond the surface layer. The underlying principle is to treat the wind profile as a power-law distribution in the vertical direction, with the power-law exponent (α) determined by the PLM-RF model. First, the PLM-RF model is constructed based on the atmospheric sounding data from 119 radiosonde (RS) stations across China and in conjunction with other data such as surface wind speed, land cover type, surface roughness, friction velocity, geographical location, and meteorological parameters from June 2020 to May 2021. Afterwards, the performance of the PLM-RF, PLM, and RF methods over China is evaluated by comparing them with RS observations. Overall, the wind speed at 100 m from the PLM-RF model exhibits high consistency with RS measurements, with a determination coefficient (R2) of 0.87 and a root mean squared error (RMSE) of 0.92 m s−1. By contrast, the R2 and RMSE of wind speed results from the PLM (RF) method are 0.75 (0.83) and 1.37 (1.04) m s−1, respectively. This indicates that the estimates from the PLM-RF method are much closer to observations than those from the PLM and RF methods. Moreover, the RMSE of the wind profiles estimated by the PLM-RF model is relatively large for highlands, while it is small for plains. This result indicates that the performance of the PLM-RF model is affected by the terrain factor. Finally, the PLM-RF model is applied to three atmospheric radiation measurement sites for independent validation, and the wind profiles estimated by the PLM-RF model are found to be consistent with Doppler wind lidar observations. This confirms that the PLM-RF model has good applicability. These findings have great implications for the weather, climate, and renewable energy sector.

Accelerated numerical solutions for discretized Black–Scholes equations

Abstract Accepted by: Aris Syntetos This study thoroughly investigates the efficiency of advanced numerical extrapolation methods aimed at enhancing the convergence of vector sequences in the realm of mathematical finance. Our focus lies in the application of polynomial extrapolation techniques to calculate finite difference solutions for the Black–Scholes (BS) equation—an indispensable model in options pricing. The performance of our algorithms undergoes rigorous evaluation through a comprehensive analysis involving both simulated and real-world data. Notably, our experiments uncover that a stochastic scheme, incorporating two extrapolation strategies and a random relaxation parameter, outperforms other proposed methods, excelling in both convergence and stability metrics. Our findings underscore the potential of this numerical extrapolation method to enhance the efficiency of financial calculations, particularly in the realm of option pricing. This innovation holds promise for refining financial models and addressing specific challenges within the field of mathematical programming, providing effective solutions to the primary computational bottlenecks commonly encountered in financial decision-making.

Glocal Design as an Interdisciplinary Model of Project Work

The purpose of the article is to explain the introduction and essence of the concept of «glocal design» and illustrate it with examples of visual communication design. Research methods. The article applies an interdisciplinary approach, analysis, synthesis, and extrapolation method, which means extending the conclusions obtained about one component of the system to another component of the same system. Scientific novelty. The article first introduces, reveals, and substantiates the concept of «glocal design» based on the materials of scientific discussions; adds the concept of «glocalization»; identifies the factors that influence the creation of glocal design (social, cultural, resource, and natural context); provides examples of the empirical source base – Ukrainian glocal design projects that are modern in terms of design style approaches and contain Ukrainian identity at the same time. Conclusions. The definition of the concept of «glocal design» is given on the basis of the refined concept of «glocalization», which, as a result of the synthesis of scientific research by other scientists, is understood by us as the process of refraction of a global wave by a local context, as a result of which it is individualized and reflected back into the world (global) space in an enriched form. We define glocal design as the process and result of complex project activities that are carried out by conscious individualization of the global project wave by the local context to reflect national identity and further presentation to the world space. The local context that ensures the creation of glocal design includes social, cultural (traditional and modern), resource (human, material, financial), and natural contexts. The concept of «glocal design» applies to all types of design – product design, environmental design (interior and landscape), fashion design, visual communications. Based on the concept of a systematic approach, we argue that the synergy of all types of design in creating a glocal product ensures efficiency in each type separately.

Comparison of Commonly Used and New Methods to Determine Small Molecule Non-Specific Binding to Human Liver Microsomes

Accurate measurement of non-specific binding of a drug candidate to human liver microsomes (HLM) can be critical for the accurate determination of key enzyme kinetic parameters such as Michaelis-Menton (Km), reversible inhibition (Ki), or inactivation (KI) constants. Several methods have been developed to determine non-specific binding of small molecules to HLM, such as rapid equilibrium dialysis (RED), ultrafiltration (UF), HLM bound to magnetizable beads (HLM-beads), ultracentrifugation (UC), the linear extrapolation stability assay (LESA), and the Transil™ system. Despite various differences in methodology between these methods, it is generally presumed that similar free fraction values (fu,mic) should be generated. To evaluate this hypothesis, a test set of 9 compounds were selected, representing low (high fu,mic value) and significant (low fu,mic value) HLM binding, respectively, across HLM concentrations tested in this manuscript. The fu,mic values were determined using a single compound concentration (1.0 µM) and three HLM concentrations (0.025, 0.50, and 1.0 mg/mL). When the HLM non-specific binding event is not extensive resulting in high fu,mic values, all methods generated similar fu,mic values. However, fu,mic values varied markedly across assay formats when high binding to HLM occurred, where fu,mic values differed by up to 33-fold depending on the method used. Potential causes for such discrepancies across the various methods employed, practical implications related to conduct the different assays, and implications to clinical drug-drug interaction (DDI) predictions are discussed.

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

Abstract CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state. Significance Statement Snowfall is a critical contributor to the global water–energy budget, with important connections to water resource management, flood mitigation, and ecosystem sustainability. However, traditional spaceborne remote monitoring of snowfall faces challenges due to a near-surface radar blind zone, which masks a portion of the atmosphere. In this study, a deep learning model was developed to fill in missing data across these regions using surface radar and atmospheric state variables. The model accurately predicts reflectivity, with significant improvements over conventional methods. This innovative approach enhances our understanding of reflectivity patterns and atmospheric interactions, bolstering advances in remote snowfall prediction.