Cloud Chamber Research Articles

Estimation of Indoor 222Rn Concentration in Lima, Peru Using LR-115 Nuclear Track Detectors Exposed in Different Modes

Radon is the main source of natural radioactivity, and its measurement is considered extremely important in radioprotection, given its relationship with the occurrence of lung cancer. In the last two years, measurements of this radioactive gas were carried out in Lima considering a grid of 5 km2 and the population density to determine the number of measurements to be carried out. Cellulose nitrate nuclear track detectors exposed in bare mode and diffusion chamber mode were used to estimate 222Rn concentrations. In diffusion chamber mode, non-commercial monitors and commercial monitors were used. The monitoring results are presented for 43 districts of the Lima Province whose population is approximately ten million inhabitants occupying a total area of 2655.15 km2. Measurements were made obtaining an average concentration of 49 Bq·m−3 using bare detectors and 66 Bq·m−3 using non-commercial diffusion chambers. Average concentrations obtained by both detector exposure modes were below the maximum concentration recommended by the WHO. A radon (222Rn) map was also obtained as a visual representation of the 222Rn levels in the Lima province using inverse distance weighting (IDW) interpolation.

The Relationship of Aerosol Properties and Ice‐Nucleating Particle Concentrations in Beijing

AbstractThis paper investigates immersion mode ice‐nucleating particle (INP) concentrations measured with a continuous flow diffusion chamber at temperatures of −20°C, −25°C, and −30°C in Beijing from 4 May to 4 June 2018. Aerosol conditions in the experiment period are classified into four types: clean, light PM2.5 pollution, heavy PM2.5 pollution, and dust. The PM mass concentrations and the aerosol size distributions are distinctly different in the four aerosol conditions. INP concentration increases as temperature decreases from −20°C to −30°C for all the four aerosol conditions. At a given temperature, INP concentrations progressively increase as the aerosol condition changes from clean to light PM2.5 pollution and to heavy PM2.5 pollution condition. At −25°C and −30°C, the dust condition has a much higher INP concentration than the other aerosol conditions. The INP concentration is closely related to the number concentration of aerosols with diameters of 1.0–2.5 μm (). Using a similar method as in the previous parameterization of INP concentrations for global and fairly clean aerosol conditions, a new parameterization of the INP concentration based on is provided for the complicated aerosol conditions with high aerosol number concentrations in Beijing.

DSPE-PEG polymer enhanced berberine absorption specifically in the small intestine of rats through paracellular passway.

This study focuses on investigating the potential impact of DSPE-PEG polymers on intestinal absorption and related mechanism of berberine in rats. Effect of DSPE-PEG polymer on intestinal absorption of berberine was investigated with an in situ closed-loop method in rats. To confirm the safety of DSPE-PEG polymer, morphological observation of rat intestine and measurement of biological markers in the intestinal perfusion of rats was performed. Underling mechanism behind promoting action of DSPE-PEG polymer was explored from its impact on the P-gp function and tight junction using in vitro diffusion chamber system, Caco-2 monolayer cells and western blot. DSPE-PEG polymer demonstrated significant enhancement action on the berberine absorption in rats without any obvious membrane toxicity. DSPE-PEG polymer (1.0%, w/v) induced the most significant promoting effect on berberine absorption specifically in the small intestine of rats. Results of mechanistic studies revealed that DSPE-PEG polymer might not regulate intestinal P-gp function, but significantly down-regulated the expression of tight junction-related proteins, which accordingly led to loosening the tight junctions of intestinal epithelium cells, and consequently increased paracellular absorption of berberine in rats. DSPE-PEG polymer, as an excellent absorption enhancer, seems very promising in increasing oral bioavailability of berberine.

Studies on Antifungal Properties of Methacrylamido Propyl Trimethyl Ammonium Chloride Polycations and Their Toxicity In Vitro.

The biological activity of polycations is usually associated with their biocidal properties. Their antibacterial features are well known, but in this work, observations on the antifungal properties of macromolecules obtained by methacrylamido propyl trimethyl ammonium chloride (MAPTAC) polymerization are presented. The results, not previously reported, make it possible to correlate antifungal properties directly with the structure of the macromolecule, in particular the molecular mass. The polymers described here have antifungal activity against some filamentous fungi. The strongest effect occurs for polymers with a mass of about 0.5 mDa which have confirmed activity against the multidrug-resistant species Scopulariopsis brevicaulis, Fusarium oxysporum, and Fusarium solani, as well as the dermatophytes Trichophyton mentagrophytes, Trichophyton rubrum, Trichophyton interdigitale, and Trichophyton tonsurans. In addition, this publication describes the effects of these macromolecular systems on serum and blood components and provides a preliminary assessment of toxicity on cell lines of skin-forming cells, i.e., fibroblasts and keratinocytes. Additionally, using a Franz diffusion chamber, a negligibly low transport of the active polymer through the skin was demonstrated, which is a desirable effect for externally applied antifungal drugs. IMPORTANCE Infectious diseases are a very big medical, social, and economic problem. Even before the COVID-19 pandemic, certain infections were among of the most common causes of death. The difficulties in the treatment of infectious diseases concern in particular fungal diseases, against which we have only a few classes of drugs represented by a few substances. The publication presents the preliminary results of the in vitro antifungal activity studies of four MAPTAC polymers on different fungal species and their cytotoxicity to human cells (fibroblasts and keratinocytes). The paper also compares these properties with analogous ones of two commonly used antifungal drugs, ciclopirox and terbinafine.

Transdermal Delivery of α-Aminophosphonates as Semisolid Formulations-An In Vitro-Ex Vivo Study.

α-Aminophosphonates are organophosphorus compounds with an obvious similarity with α-amino acids. Owing to their biological and pharmacological characteristics, they have attracted the attention of many medicinal chemists. α-Aminophosphonates are known to exhibit antiviral, antitumor, antimicrobial, antioxidant and antibacterial activities, which can all be important in pathological dermatological conditions. However, their ADMET properties are not well studied. The aim of the current study was to provide preliminary information about the skin penetration of three preselected α-aminophosphonates when applying them as topical cream formulations in static and dynamic diffusion chambers. The results indicate that aminophosphonate 1a, without any substituent in the para position, shows the best release from the formulation and the highest absorption through the excised skin. However, based on our previous study, the in vitro pharmacological potency was higher in the case of para-substituted molecules 1b and 1c. The particle size and rheological studies revealed that the 2% cream of aminophosphonate 1a was the most homogenous formulation. In conclusion, the most promising molecule was 1a, but further experiments are proposed to uncover the possible transporter interactions in the skin, optimize the topical formulations and improve PK/PD profiles in case of transdermal delivery.

An Intercomparison of Large‐Eddy Simulations of a Convection Cloud Chamber Using Haze‐Capable Bin and Lagrangian Cloud Microphysics Schemes

AbstractRecent in situ observations show that haze particles exist in a convection cloud chamber. The microphysics schemes previously used for large‐eddy simulations of the cloud chamber could not fully resolve haze particles and the associated processes, including their activation and deactivation. Specifically, cloud droplet activation was modeled based on Twomey‐type parameterizations, wherein cloud droplets were formed when a critical supersaturation for the available cloud condensation nuclei (CCN) was exceeded and haze particles were not explicitly resolved. Here, we develop and adapt haze‐capable bin and Lagrangian microphysics schemes to properly resolve the activation and deactivation processes. Results are compared with the Twomey‐type CCN‐based bin microphysics scheme in which haze particles are not fully resolved. We find that results from the haze‐capable bin microphysics scheme agree well with those from the Lagrangian microphysics scheme. However, both schemes significantly differ from those from a CCN‐based bin microphysics scheme unless CCN recycling is considered. Haze particles from the recycling of deactivated cloud droplets can strongly enhance cloud droplet number concentration due to a positive feedback in haze‐cloud interactions in the cloud chamber. Haze particle size distributions are more realistic when considering solute and curvature effects that enable representing the complete physics of the activation process. Our study suggests that haze particles and their interactions with cloud droplets may have a strong impact on cloud properties when supersaturation fluctuations are comparable to mean supersaturation, as is the case in the cloud chamber and likely is the case in the atmosphere, especially in polluted conditions.

Loads prediction and consolidation of virtual machines in cloud

SummaryVirtual machine (VM) consolidation is to assign a set of VMs requested by operators to the physical machines (PMs) in the data centers so that certain cost, profit or performance objective is optimized, subject to the PMs resource capacity constraints. It is an important mean to decrease the total power consumption by reducing the number of active physical machines (PM) in a cloud. In this context, most of the existing solutions rely on highly frequent live migration to reduce the number of active physical machines. However, live migration is a high resource consumption and time‐consuming operation, thus, frequent use of live migration not only increases energy consumption but also affects the stability of the physical machine, which in turn affects the services on the virtual machine. Reducing the number of active physical machines while reducing the number of live migrations is a major challenge in the face of massive fluctuating virtual machine loads. In order to solve this problem, in this paper, we present a VM consolidation algorithm for predictable loads (VCPL) to reduce the live migration operations. First, we present a cyclic usage prediction (CUP) method to predict the load in a whole cycle (a day) of a VM. Then, we separate the VMs with stable and cyclic load out from others and consolidate them to PMs by using VCPL to make sure each PM has a stable load. Thus, energy can be reduced by avoiding most of live migration operations, and the stability of the data center can be observably improved. We evaluate our solution through simulations on real‐world workloads, the results show that, 66% of long‐term VMs have stable and cyclic loads and are predictable, by using VCPL, the live migration operations occurring on the PMs which accommodate those VMs can be reduced significantly than other solutions.

Photoactive and Intrinsically Fuel Sensing Metal-Organic Framework Motors for Tailoring Collective Behaviors of Active-Passive Colloids.

Microorganisms display nonequilibrium predator-prey behaviors, such as chasing-escaping and schooling via chemotactic interactions. Even though artificial systems have revealed such biomimetic behaviors, switching between them by control over chemotactic interactions is rare. Here, a spindle-like iron-based metal-organic framework (MOF) colloidal motor which self-propels in glucose and H2 O2 , triggered by UV light is reported. These motors display intrinsic UV light-triggered fuel-dependent chemotactic interactions, which are used to tailor the collective dynamics of active-passive colloidal mixtures. In particular, the mixtures of active MOF motors with passive colloids exhibit distinctive "chasing-escaping" or "schooling" behaviors, depending on glucose or hydrogen peroxide being used as the fuel. The transition in the collective behaviors is attributed to an alteration in the sign of ionic diffusiophoretic interactions, resulting from a change in the ionic clouds produced. This study offers a new strategy on tuning the communication between active and passive colloids, which holds substantial potentials for fundamental research in active matter and practical applications in cargo delivery, chemical sensing, and particle segregation.

Criminal law regulation of cyber fraud crimes—from the perspective of citizens’ personal information protection in the era of edge computing

Currently, cloud computing provides users all over the globe with Information and Communication Technology facilities that are utility-oriented. This technology is trying to drive the development of data center design by designing and building them as networks of cloud machines, enabling users to access and run the application from any part of the globe. Cloud computing provides considerable benefits to organizations by providing rapid and adaptable ICT software and hardware systems, allowing them to concentrate on creating innovative business values for the facilities they provide. The right to privacy of big data has acquired new definitions with the continued advancement of cloud computing, and the techniques available to protect citizens’ personal information under administrative law have managed to grow in a multitude. Because of the foregoing, internet fraud is a new type of crime that has emerged over time and is based on network technology. This paper analyzed and studied China’s internet fraud governance capabilities, and made a comprehensive evaluation of them using cloud computing technology and the Analytic Hierarchy Process (AHP). This paper discussed personal information security and the improvement of criminal responsibility from the perspective of citizens’ information security and designed and analyzed cases. In addition, this paper also analyzed and studied the ability of network fraud governance in the era of cloud computing. It also carried out a comprehensive evaluation and used the fuzzy comprehensive evaluation method to carry out the evaluation. A questionnaire survey was used to survey 100 residents in district X of city Z and district Y of the suburban area. Among the 100 people, almost all of them received scam calls or text messages, accounting for 99%, of which 8 were scammed. Among the people, more than 59.00% of the people expressed dissatisfaction with the government’s Internet fraud satisfaction survey. Therefore, in the process of combating Internet fraud, the government still needs to step up its efforts.

Intercomparison of equipment measuring radon activity concentration in the air—an example from a hydrotechnical structure in Dobromierz (SW Poland)

The semi-conductor SRDN-3a probe, an AlphaE detector with a silicon diode in a diffusion chamber, an AlphaGUARD monitor with an ionization chamber and CR-39 track detectors had been tested simultaneously in long-term measurements conducted in the technical corridor of Dobromierz dam. The passive detectors were exposed twice: for 56 days, and 117 days, others in parallel, with a 1-h data recording interval. The data distribution was tested with the Shapiro–Wilk test and outliers in the critical region were identified using Shewhart control charts. The correctness was evaluated by a z-score test recommended by the IAEA. The characteristics of outliers for each detectors are determined by the location of the critical region (a two-sided region and a positive skew). These are 13.0% and 13.5% for AlphaE, and 9.81% for SRDN-3a. For the reference device, these are 15.8% and 10.5%. The z-score test confirm that all the detectors can be successfully used both in commercial and scientific monitoring measurements.

New insights into how popular electronic cigarette aerosols and aerosol constituents affect SARS-CoV-2 infection of human bronchial epithelial cells

The relationship between the use of tobacco products and SARS-CoV-2 infection is poorly understood and controversial. Few studies have examined the effect of electronic cigarettes (ECs) on SARS-CoV-2 infection. We tested the hypothesis that EC fluids and aerosols with nicotine promote SARS-COV-2 infection by increasing viral entry into human respiratory epithelial cells. Responses of BEAS-2B cells to JUUL aerosols or their individual constituents were compared using three exposure platforms: submerged culture, air–liquid-interface (ALI) exposure in a cloud chamber, and ALI exposure in a Cultex system, which produces authentic heated EC aerosols. In general, nicotine and nicotine + propylene glycol/vegetable glycerin aerosols increased ACE2 (angiotensin converting enzyme 2) levels, the SARS-CoV-2 receptor; and increased the activity of TMPRSS2 (transmembrane serine protease 2), an enzyme essential for viral entry. Lentivirus pseudoparticles with spike protein were used to test viral penetration. Exposure to nicotine, EC fluids, or aerosols altered the infection machinery and increased viral entry into cells. While most data were in good agreement across the three exposure platforms, cells were more responsive to treatments when exposed at the ALI in the Cultex system, even though the exposures were brief and intermittent. While both nicotine and JUUL aerosols increased SARS-CoV-2 infection, JUUL significantly decreased the effect of nicotine alone. These data support the idea that vaping can increase the likelihood of contracting COVID-19 and that e-liquid composition may modulate this effect.

Investigation of stochastic heating and its influence on plasma radial uniformity in biased inductively coupled Ar discharges by hybrid simulation

A bias power is usually applied in inductively coupled plasmas (ICP) to realize the separate control of the plasma density and the ion energy. In this research, a two-dimensional fluid/electron Monte Carlo hybrid model is developed to self-consistently investigate the bias effect on the stochastic heating and on the radial homogeneity in a biased argon ICP operated at low pressure (3 mTorr). The results show that the temporal evolution of the stochastic heating exhibits a plateau and a peak when the sheath collapses at high bias voltages, due to the limited sheath heating and the electron inertia. In addition, the plasma density in the diffusion chamber increases with bias voltage and bias frequency, because of the more pronounced stochastic heating both at the substrate and at the grounded wall. In the main discharge chamber, the plasma density decreases with bias voltage, due to the compression of the bulk plasma region, and this trend becomes less obvious at high bias frequency, because of the enhanced power absorption caused by the stochastic heating. Therefore, it is concluded that by tuning the bias voltage and bias frequency, the plasma radial uniformity could be modulated efficiently, which is very important for improving plasma processing.

Analysis of plant cuticles and their interactions with agrochemical surfactants using a 3D printed diffusion chamber

BackgroundDecades of research is available on their effects of single component surfactant on active ingredient diffusion across plant cuticular membranes, but ingredient diffusion is rarely analysed in the presence of commercial surfactants. Also, diffusion studies require expensive or specialized apparatus the fabrication of which often requires skilled labour and specialized facilities. In this research we have addressed both problems where the effects of four commercially available surfactants on a known tracer molecule were investigated using a 3D printed customized diffusion chamber.ResultsAs a proof-of-concept a customized 3D printed diffusion chamber was devised using two different thermoplastics and was successfully used in a range of diffusion tests . The effect of various solvents and surfactants on S. lycopersicum cuticular membrane indicated an increased rate of flux of tracer molecules across the membranes. This research has validated the application of 3D printing in diffusion sciences and demonstrated the flexibility and potential of this technique.ConclusionsUsing a 3D printed diffusion apparatus, the effect of commercial surfactants on molecular diffusion through isolated plant membranes was studied. Further, we have included here the steps involved in material selection, design, fabrication, and post processing procedures for successful recreation of the chamber. The customizability and rapid production process of the 3D printing demonstrates the power of additive manufacturing in the design and use of customizable labware.

Perspectives of using artificial intelligence elements in bread baking

Enterprises of bread baking sector produce traditional everyday products and, at the same time, this sector remains one of the most conservative ones. There are always new types of raw materials and additives on the market, but new recipes are developed traditionally based on the results of test baking. However, a technologically justified solution is not always optimal regarding nutritional value. The purpose of this work is consideration of the possibilities and prospects of using elements of artificial intelligence (AI) in bread baking based on examples from other sectors of the food industry and study the AI’s ability to analyze and evaluate (categorise) existing recipes of bread products. The initial stage of AI use is machine learning (ML), but today there are no unified electronic databases that can be used to fulfil the task. We took approved collections of recipes as the basis for filling such databases. In addition, technologically acceptable variations of the main recipe components and their mutual substitution were carried out. The base was analyzed using Microsoft Azure Machine Learning service and Google Cloud Machine Learning Engine. Normalised database with 5,000 variants of recipes of bakery products that can be manufactured in conditions of both large industrial companies and small bakeries were created. The ML showed that the system effectively determines the main components of recipes and can independently, with high accuracy, classify recipes entered by the user into categories "bread" or "enriched bread". The work showed the possibility and viability of using AI elements in the baking industry. The database can be used to design new bakery products with specified recipe composition and (after improvement) to model applications with specified chemical composition or biological value.

Real-time detection of deception attacks in cyber-physical systems

AbstractDetection of deception attacks is pivotal to ensure the safe and reliable operation of cyber-physical systems (CPS). Detection of such attacks needs to consider time-series sequences and is very challenging especially for autonomous vehicles that rely on high-dimensional observations from camera sensors. The paper presents an approach to detect deception attacks in real-time utilizing sensor observations, with a special focus on high-dimensional observations. The approach is based on inductive conformal anomaly detection (ICAD) and utilizes a novel generative model which consists of a variational autoencoder (VAE) and a recurrent neural network (RNN) that is used to learn both spatial and temporal features of the normal dynamic behavior of the system. The model can be used to predict the observations for multiple time steps, and the predictions are then compared with actual observations to efficiently quantify the nonconformity of a sequence under attack relative to the expected normal behavior, thereby enabling real-time detection of attacks using high-dimensional sequential data. We evaluate the approach empirically using two simulation case studies of an advanced emergency braking system and an autonomous car racing example, as well as a real-world secure water treatment dataset. The experiments show that the proposed method outperforms other detection methods, and in most experiments, both false positive and false negative rates are less than 10%. Furthermore, execution times measured on both powerful cloud machines and embedded devices are relatively short, thereby enabling real-time detection.

High-resolution separation of bioisomers using ion cloud profiling

Elucidation of complex structures of biomolecules plays a key role in the field of chemistry and life sciences. In the past decade, ion mobility, by coupling with mass spectrometry, has become a unique tool for distinguishing isomers and isoforms of biomolecules. In this study, we develop a concept for performing ion mobility analysis using an ion trap, which enables isomer separation under ultra-high fields to achieve super high resolutions over 10,000. The potential of this technology has been demonstrated for analysis of isomers for biomolecules including disaccharides, phospholipids, and peptides with post-translational modifications.

Kinetic Asymmetry versus Dissipation in the Evolution of Chemical Systems as Exemplified by Single Enzyme Chemotaxis.

Single enzyme chemotaxis is a phenomenon by which a nonequilibrium spatial distribution of an enzyme is created and maintained by concentration gradients of the substrate and product of the catalyzed reaction. These gradients can arise either naturally through metabolism or experimentally, e.g., by flow of materials through microfluidic channels or by use of diffusion chambers with semipermeable membranes. Numerous hypotheses regarding the mechanism of this phenomenon have been proposed. Here, we discuss a mechanism based solely on diffusion and chemical reaction and show that kinetic asymmetry, a difference in the transition state energies for dissociation/association of substrate and product, and diffusion asymmetry, a difference in the diffusivities of the bound and free forms of the enzyme, are the determinates of the direction of chemotaxis and can result in either positive or negative chemotaxis, both of which have been demonstrated experimentally. Exploration of these fundamental symmetries that govern nonequilibrium behavior helps to distinguish between possible mechanisms for the evolution of a chemical system from initial to the steady state and whether the principle that determines the direction a system shifts when exposed to an external energy source is based on thermodynamics or on kinetics with the latter being supported by the results of the present paper. Our results show that, while dissipation ineluctably accompanies nonequilibrium phenomena, including chemotaxis, systems do not evolve to maximize or minimize dissipation but rather to attain greater kinetic stability and accumulate in regions where their effective diffusion coefficient is as small as possible. The chemotactic response to the chemical gradients formed by other enzymes participating in a catalytic cascade provides a mechanism for forming loose associations known as metabolons. Significantly, the direction of the effective force due to these gradients depends on the kinetic asymmetry of the enzyme and so can be nonreciprocal, where one enzyme is attracted to another enzyme, but the other enzyme is repelled by the one, in seeming contradiction to Newtons third law. This nonreciprocity is an important ingredient in the behavior of active matter.

Determination of Electron Beam Energy in Measuring the Electron-Impact Ionization Cross Section of He-like Fe24+

In an effort to measure electron-impact ionization (EII) cross-sections of He-like Fe24+ at the electron beam ion trap (EBIT) facility of the National Institute of Standards and Technology (NIST), we have experimentally determined the corrections to the nominal beam energy determined by the voltages applied to the EBIT. High-resolution X-ray spectra were recorded at nominal electron beam energies between 6660 eV and 6750 eV using X-ray microcalorimetry based upon an array of 192 transition-edge sensors (TES). A large-scale collisional-radiative simulation of the non-Maxwellian EBIT plasma using relevant atomic data calculated with Flexible Atomic Code allowed us to determine the space-charge correction due to the electron beam including the neutralization factor by the ion cloud of the EBIT.

Preliminary applications carried out in a new-build radon chamber using CR-39 detectors inside non-commercial diffusion chambers

Many CR-39 (poly allyl glycol carbonate) detectors inside two different non-commercial diffusion chambers were used to study the radon permeability and the radon transmission factor. This factor represents the percentage of radon concentration that truly enters a diffusion chamber, since there is a loss of radon concentration inside the chamber compared to the outside radon concentration, due to the radioactive nature of radon gas. Here, a theoretical discussion is presented, followed by an experimental study that was carried out in a new-build radon chamber. These initial results are presented in order to show a preliminary performance evaluation of the radon chamber as well as introducing some preliminary applications. The most remarkable observation is that research consistently shows that the obtained value of radon permeability constant for a commercial membrane is 4.404×10−8±0.012×10−8cm2/s, which is in a good agreement with literature data.

Impact of formulations of the homogeneous nucleation rate on ice nucleation events in cirrus

Abstract. Homogeneous freezing of solution droplets is an important pathway of ice formation in the tropopause region. The nucleation rate can be parameterized as a function of water activity, based on empirical fits and some assumptions on the underlying properties of super-cooled water, although a general theory is missing. It is not clear how nucleation events are influenced by the exact formulation of the nucleation rate or even their inherent uncertainty. In this study we investigate the formulation of the nucleation rate of homogeneous freezing of solution droplets (1) to link the formulation to the nucleation rate of pure water droplets, (2) to derive a robust and simple formulation of the nucleation rate, and (3) to determine the impact of variations in the formulation on nucleation events. The nucleation rate can be adjusted, and the formulation can be simplified to a threshold description. We use a state-of-the-art bulk ice microphysics model to investigate nucleation events as driven by constant cooling rates; the key variables are the final ice crystal number concentration and the maximum supersaturation during the event. The nucleation events are sensitive to the slope of the nucleation rate but only weakly affected by changes in its absolute value. This leads to the conclusion that details of the nucleation rate are less important for simulating ice nucleation in bulk models as long as the main feature of the nucleation rate (i.e. its slope) is represented sufficiently well. The weak sensitivity of the absolute values to the nucleation rate suggests that the amount of available solution droplets also does not crucially affect nucleation events. The use of only one distinct nucleation threshold function for analysis and model parameterization should be reinvestigated, since it corresponds to a very high nucleation rate value, which is not reached in many nucleation events with low vertical updrafts. In contrast, the maximum supersaturation and thus the nucleation thresholds reached during an ice nucleation event depend on the vertical updraft velocity or cooling rate. This feature might explain some high supersaturation values during nucleation events in cloud chambers and suggests a reformulation of ice nucleation schemes used in coarse models based on a purely temperature-dependent nucleation threshold.