The characterisation and monitoring of viscous fluids have many important applications. This paper reports a refined ‘dipstick’ method for ultrasonic measurement of the properties of viscous fluids. The presented method is based on the comparison of measurements of the ultrasonic properties of a waveguide that is immersed in a viscous liquid with the properties when it is immersed in a reference liquid. We can simultaneously determine the temperature and viscosity of a fluid based on the changes in the velocity and attenuation of the elastic shear waves in the waveguide. Attenuation is mainly dependent on the viscosity of the fluid that the waveguide is immersed in and the speed of the wave mainly depends on the surrounding fluid temperature. However, there is a small interdependency since the mass of the entrained viscous liquid adds to the inertia of the system and slows down the wave. The presented measurements have unprecedented precision so that the change due to the added viscous fluid mass becomes important and we propose a method to model such a ‘viscous effect’ on the wave propagation velocity. Furthermore, an algorithm to correct the velocity measurements is presented. With the proposed correction algorithm, the experimental results for kinematic viscosity and temperature show excellent agreement with measurements from a highly precise in-lab viscometer and a commercial resistance temperature detector (RTD) respectively. The measurement repeatability of the presented method is better than 2.0% in viscosity and 0.5% in temperature in the range from 8 to 300 cSt viscosity and 40 to 90 °C temperature. There are more than 50,000 ships world-wide, which are responsible for transporting over 90% of the globally traded goods, and most of them use Heavy Fuel Oil (HFO) as their main propulsion fuel . The fueUltrasonic waveguides are an attractive alternative due to their potential to provide robust measurements at a relatively low cost. They are suitable for online continuous monitoring and can also be designed to work in harsh environments, such as extremely high temperature and pressure, where conventional techniques are not reliable. For example, Balasubramaniam et al.  used a wMost of the applications discussed above can be described as ‘dipstick’ methods where the waveguide is partly or completely immersed in the fluid and the fluid properties are determined by measurements of the ultrasonic properties of the waveguide. Recently, it has been reported that a temperature-sensing accuracy as good as ±0.015 °C can be achieved using SH waves in a ‘dipstick’ waveguide [Reference measurements with the waveguide were initially performed to obtain ultrasonic wave attenuation and SH wave velocity in the waveguide as a function of temperature using a low-viscosity standard that has a marginal viscosity change as a function of temperature (<1.6 cSt over a temperature change of 50 °C). The viscosity standard chosen for this was the S3S high temperature viscosity standard by Paragon Scientific Ltd. . The N35 and N350 general viscosity standards, also purchased from Paragon Scientific Ltd., were used to evaluate the viscosity and temperature measurements using the same waveguide and the results were compared to the Anton Parr viscometer SVM 3001 and the PT100 RTD, respectively.The waveguide used in this study was made of aluminium with the geometry as shown in The wave propagation in the waveguide is as follows: the transducer excites the wave that travels along the waveguide. Once it reaches the notches near the other end, the wave is partially reflected, and this part of the wave travels back and is received by the transducer as the first echo (The shear properties of a fluid can be determined by measuring the attenuation of the SH wave in the waveguide that interacts with it. The attenuation that is purely caused by the leakage of the shear wave into the surround fluid can be estimated by the following equation :(2)αs=12ous work ,20.In the past, this ‘shear attenuation’ was measured by immersing a waveguide at two different depths into the fluid sample . HoweverThe amplitude ratio of the first and second reflections is used to determine the attenuation of the SH wave. As shown in T indicates the temperature dependence. Similarly, in a fluid with unknown viscosity as shown in This quantity is a result of the reflection coefficient from the notch and the end of the waveguide and the material attenuation in the waveguide and should be constant as a function of temperature. However, it is impractical to perform reference measurements in air, especially at different temperatures for velocity calibration; therefore, in our experiments the waveguide is immersed in a low-viscosity calibration liquid. When the waveguide is immersed to a depth of The shear leakage-induced attenuation in this case can be determined by comparing Equations (4) and (5):Even though a low-viscosity standard was chosen for calibration, The experimental setup for the calibration and measurements is shown in The averaged signal is filtered by a 5th-order Butterworth bandpass filter with cut off frequency at 1.6 and 2.4 MHz;The filtered signal is up-sampled to 1 GHz;The peaks of the first and second reflections are used to determine the time of flight and the exact locations of the peaks are extracted by gradient-based linear interpolation. The amplitude of the peaks is used to evaluate SH wave attenuation.Initially, the sample was heated to 90 °C in a glass bottle on top of a hot plate  with an active magnetic flea. The heater was then switched off and the sample was left to cool down at room temperature. Data collection of the ultrasonic signal and temperature was carried out in one-minute intervals. For each measurement, 400 consecutive signals were sent, received and averaged to improve the signal to noise ratio (SNR). For a typical measurement, a 5-cycle Hann-windowed sinusoidal tone-burst with a centre frequency of 2 MHz was sent to the waveguide and the following data processing methods were used to extract the time of flight and amplitude of the first and second reflections:Initially, the waveguide was calibrated in Paragon S3S at an elevated temperature with the PT100 probe to obtain two calibration equations, reported ,7,21,22,reported . Thus, tThe velocity of the shear waves in the unloaded waveguide As Consider a section of the immersed waveguide as shown in For an oscillating plate loaded with a viscous fluid, only half of the mass of the viscous skin depth contributes to the inertia of the plate . The effThe shear velocity in the viscous fluid loaded waveguide with effective density will beBy substituting Equations (8)–(11) into (12) and rearranging, the wave velocity for a waveguide with viscous layer loading can be calculated asThe algorithm shown in Viscosity measurements were carried out to validate the viscosity standards—Paragon N35 and N350—in the temperature range of 20 to 100 °C in 10 °C intervals. As 3) while the density of the waveguide was assumed to be 2690 kg/m3 and its shear modulus 26.34 GPa.The waveguide measurements were also carried out for these two viscosity standards. The results in As can be seen from As a result of this over-prediction of temperature, there is an offset in the attenuation measured and therefore the viscosity predicted in In The repeatability is calculated here as the root mean square of the variance between the measured values and the least square best line fit over the whole range of viscosity/temperature studied. For Paragon N35, it is estimated to 1.80% on average and 0.05 °C (or 0.1%) for temperature prediction. For Paragon N350, a repeatability of 1.17% is achieved for viscosity prediction and 0.20 °C (or 0.4%) for temperature prediction.There are a number of sources of errors in this study and the following areas are considered the main contributions: (1) uncertainties in the physical properties of the waveguide and the fluids; (2) the instrumental errors in the temperature measurements by the PT100 and the ultrasonic measurements using the pulser/amplifier (non-linearities); and (3) wave modes other than SH excited by the transducer. While the data presented here demonstrate very good agreement , the viscosity is predicted using the physical properties , which are calculated with reasonable assumptions or taken directly from the literature rather than experimentally characterised. While the density and viscosity are explicitly known for the calibration fluid and used to calculate This paper presents a method to use an ultrasonic waveguide to simultaneously measure the temperature and viscosity of viscous fluids. Unprecedented measurement precision for this type of ‘dipstick’ setup is reported and the velocity estimates are so precise that for the first time the effect of viscous fluid loading onto the waveguide is demonstrated. An iterative algorithm to correct for the changes in wave velocity due to viscous mass loading was presented and shown to considerably correct the temperature measurements and improve the viscosity predictions. The overall results predicted are in excellent agreement with reference measurements using an Anton Parr viscometer, a PT104 RTD for temperature measurements and literature values provided by the viscosity standard supplier. The observed repeatability was less than 2.0% in kinematic viscosity in the range from around 8 cSt up to 300 cSt and less than 0.5% in temperature from 40 to 90 °C. Without the correction for velocity, the temperature prediction could have an error as large as 15% which would divert the viscosity prediction as much as about 15% for a fluid that has a similar viscosity as the Paragon N350. The refined ‘dipstick’ method reported here gives reliable and accurate measurements for both temperature and viscosity.


Mathematical models for the action potential (AP) generation of the electrically excitable cells including the heart are involved different mechanisms including the voltage-dependent currents with nonlinear time- and voltage-gating properties. From the shape of the AP waveforms to the duration of the refractory periods or heart rhythms are greatly affected by the functions describing the features or the quantities of these ion channels. In this work, a mathematical measure to analyze the regional contributions of voltage-gated channels is defined by dividing the AP into phases, epochs, and intervals of interest. The contribution of each time-dependent current for the newly defined cardiomyocyte model is successfully calculated and it is found that the contribution of dominant ion channels changes substantially not only for each phase but also for different regions of the cardiac AP. Besides, the defined method can also be applied in all Hodgkin–Huxley types of electrically excitable cell models to be able to understand the underlying dynamics better. Cardiac APs are long APs due to the long plateau phase with a stable resting potential around −80 mV. The differences in AP waveforms and durations occur due to the differences in the underlying ionic currents. Understanding the underlying mechanisms of the spiking activity due to the various ionic currents has been an important problem experimentally and mathematically. Mathematical models of the excitable cells including the heart have been defined since the 1960s based on experimental data and the early mathematical models were based on the extensions of the Hodgkin–Huxley model that is defined for nerve conduction  ([Ca2+]i) begin the processes of VDI and CDI at phase 0, and they are dominant during phase 2 causing a progressive decrease in ICaL. But to regulate the roles of the VDI–CDI ratio, [Ca2+]i and calmodulin level is increased in the model so that the dominant role of CDI could be observed. Moreover, the Ca2+ transient duration is shorter than the physiological AP duration in the model [2+ mechanism should be calibrated and the Ca2+ process should be studied separately according to the experimental results. Thus, the contribution analysis-like methods can be a useful tool to calibrate mathematical models by quantifying nonlinear properties and comparing them with the experimental findings. The new parameters are incorporated in the model given in the Appendix section.Once the contribution analysis is applied to the rat ventricular model for the first time, the results were able to catch the part of the Caworks of . The methe model . So the 2 (sulfur dioxide)) [We applied our method for the ventricular cardiomyocytes but the contributions of detailed molecular identities of the membrane currents change dramatically within the cell type , within the species , location within the heart , within the developmental stage , and in response to hormones and drugs (ISO (isoproterenol), SOioxide)) . For exaioxide)) . SimilarThe next thing that can be done is to verify this method for each gating variable in dynamic clamp set-up. Dynamic clamp enables us to real-time interface between cell model and real cell to observe the role of each ionic current . It is pdt = 0.001 ms) in this work. This leads to approximately 12 minutes running time of the computer program for a computer with 2.80 GHz processor. This time step is enough to see even the contribution of small T-Type Ca2+ current and rapidly activated K+ current, but it is not enough to see which Na+ gating variable contributes to the occurrence of very small late current in the plateau phase. For this reason, all contributions were also observed with dt =0.0001 ms and the dynamics that contribute to the occurrence of late Na+ current were also determined, the other contribution values didn’t change too much. This shows dt =0.0001 ms should be enough to see the correct contribution value and the method is stable enough. Another limitation is that the contribution analysis method is not able to measure the contributions of time-independent currents like pump currents. For these, other quantification analysis from the literature like dominant scale analysis can be applied.The contribution analysis method can measure the contribution of each dynamic to every region of AP. However, there is a trade-off between the correctness of the contribution values and the speed of the computer program. The smaller determination of time steps for solving differential equations the more correct contribution values we can get. For this reason, the time step was chosen as small as possible (Click here for additional data file.


We present a comprehensive set of deterministic transformations that can be inserted as distinct layers into the computational graph of a trained generative neural network and applied during inference. In addition, we present a novel algorithm for analysing the deep generative model and clustering features based on their spatial activation maps. This allows features to be grouped together based on spatial similarity in an unsupervised fashion. This results in the meaningful manipulation of sets of features that correspond to the generation of a broad array of semantically significant features of the generated results. We outline this framework, demonstrating our results on deep generative models for both image and audio domains. We show how it allows for the direct manipulation of semantically meaningful aspects of the generative process as well as allowing for a broad range of expressive outcomes.This paper presents the  Network bending allows for active divergence [groups of features combine to produced different aspects of the image. We show results from these processes on two kinds of generative models; using StyleGAN2, the current state-of-the-art for unconditional image generation [The ramework , allows vergence ,3 from tneration , and a cA generative model consists of the application of machine learning to learn a configuration of parameters that can approximately model a given data distribution. This was historically a very difficult problem, especially for domains of high data dimensionality such as for audio and images. With the advent of deep learning and large training datasets, great advances were made in the last decade. Deep neural networks are now capable of generating realistic audio ,6 and imlatent space of generative models has subsequently been a growing area of research. Semantic latent manipulation consists of making informed alterations to the latent code that correspond to the manipulation of different semantic properties present in the data. This can be done by operating directly on the latent codes [Understanding and manipulating the nt codes ,18 or bynt codes . Evolutint codes ,21 and int codes  for humanetwork dissection [Developing methods for understanding the purpose of the internal features (aka hidden units) of deep neural networks has been an on-going area of research. In computer vision and image processing applications, there have been a number of approaches, such as through visualisation, either by sampling patches that maximise the activation of hidden units ,24, or bssection  where hissection , by remossection . This lessection .The manipulation of deep generative models is itself a nascent area of research. An interactive interface built upon the GAN Dissection approach  was presAn approach that alters the computational graph of the model such that a change alters the entire distribution of results, is presented as an algorithm for “rewriting the rules of a generative model” . In thisTo demonstrate our framework, we have used two different architectures of generative models in different data domains for analysis and manipulation. To demonstrate our method in the image domain we use StyleGAN2, analysing models trained on three separate data domains. To demonstrate our method on audio, we train a custom VAE on spectrograms trained on a dataset of varied musical genres. The two architectures are detailed in the following subsections.In our experiments we used three StyleGAN2 models trained on different datasets: the Flickr Faces High Quality (FFHQ) , LSUN chWe train a variational autoencoder (VAE) ,10 on spFor the VAE we employ a convolutional architecture with a latent vector with dimension autoencoding [After training it is possible to sample randomly in the latent space and then sample directly from the decoder. It is also possible to input audio sequences, both from the training set and outside of it, and produce reconstructions of the audio track mediated through the VAE model, in a method that we have previously referred to as encoding . By perfk-means clustering algorithm [As most of the layers in current state of the art generative models, such as StyleGAN2, have very large numbers of convolutional features, controlling each one individually would be far too complicated to build a user interface around and to control these in a meaningful way. In addition, because of the redundancy existing in these models, manipulating individual features does not normally produce any kind of meaningful outcome. Therefore, it is necessary to find some way of grouping them together into more manageable ensembles of sets of features. Ideally such sets of features would correspond to the generation of distinct, semantically meaningful aspects of the image, and manipulating each set would correspond to the manipulation of specific semantic properties in the resulting generated sample. In order to achieve this, we present a novel approach, combining metric learning and a clustering algorithm to group sets of features in each layer based on the spatial similarity of their activation maps. We train a separate convolutional neural network (CNN) for each layer of the respective generative models (the StyleGAN2 generator and the decoder of our VAE) with a bottleneck architecture  to learlgorithm ,39 to grFor each layer of both generative models, we train a separate CNN on the activation maps of all the convolutional features. As the resolution of the activation maps and number of features varies for the different layers of the model (a breakdown of which can be seen in We employ the ShuffleNet architecture  for the k-means) does not scale well for feature spaces with high dimensionality.After the convolutional blocks, we flatten the final layer and learn from it a mapping into a narrow bottleneck We generated a training set of the activations of every feature for every layer of 1000 randomly sampled images, and a test set of 100 samples for the models trained on all of the datasets used in our experiments. We trained each CNN using the softmax feature learning approach , a reliaAfter training, the softmax layer is discarded and the embedding of the bottleneck layer is used as the discriminative feature vector where the distances between points in feature space permit to gauge the degree of similarity of two samples. Our approach differs from standard softmax feature learning in that we use the feature vector from the bottleneck, rather than the last layer prior to softmax classification, giving a more compressed feature representation than the standard softmax feature learning approach.Once the CNNs for every layers have been trained, they can then be used to extract feature representations of the activation maps of the different convolutional features corresponding to each individual layer of the generative model. There are two approaches to this. The first is to perform the clustering on-the-fly for a specific latent for one sample. A user would want to do this to get customised control of a specific sample, such as a latent that has been found to produce the closest possible reproduction of a specific person from the StyleGAN2 model trained on the FFHQ dataset ,42. The d and feature f is fed into the CNN metric learning model for that layer k-means clustering algorithm—using Lloyd’s method [The clustering algorithm for a single example is activated by a forward pass of the generative model performed without any additional transformation layers being inserted, this to obtain the unmodified activation maps. The activation map s method  with Fors method ,43. ThisN randomly generated samples—the results herein are from processing 1000 samples. Then we perform the same clustering algorithm as previously for individual samples on the mean feature vectors. The number of clusters for each layer in StyleGAN2 can be seen in Alternatively, to find a general purpose set of clusters, we first calculate the mean feature vector We have implemented a broad variety of deterministically controlled transformation layers that can be dynamically inserted into the computational graph of the generative model. The transformation layers are implemented natively in PyTorch  for speex. We have implemented four distinct numerical transformations: the first is ablation, which can be interpreted as inversion, which is implemented as multiplication by a scalarp implemented as binary thresholding (often referred to as posterisation) with threshold t, such that:We begin with simple numerical transformations X for feature f as an individual matrix, that simple affine transformations can be applied too. The first two are horizonal and vertical reflections that are defined as:translations by parameters scaling by parameters rotation by an angle For this set of transformations we treat each activation map Other affine transformations can easily be implemented by designing the matrices accordingly.erosion and dilation [r which is the radius for a circular kernel  used in the morphological transformations.We have implemented two of the possible basic mathematical morphological transformation layers, performing dilation  when appYAML configuration files [In our current implementation, transforms are specified in on files , such thz, or be calculated using a projection in latent space w [After loading the configuration, we either lookup which features are in the cluster index, or randomly apply indices based on the random threshold parameter. Then the latent is loaded, which can either be randomly generated, or be predefined in latent space  space w ,42  oThe framework we have presented is the first approach to manipulating generative models that focuses on allowing for a large array of novel expressive outcomes. In contrast to other methods that manipulate deep generative models ,30, our You Are Here [Since we introduced it, network bending has been used in the production of a number of artworks. The artist Derrick Schulz utilises network bending frequently in their practice of chaining models, where multiple generative models and deep learning based manipulation techniques are used in sequence to produce desired results . For insAre Here , SchultzTeratome [Fragments of Self presents a self portrait  thatied gaze  is a vidnetwork bending, which we have demonstrated on generative models in the image and audio domains. By inserting deterministic filters inside pre-trained networks, we present a framework for performing manipulation inside the networks’ black-box and utilise it to generate samples that have no resemblance to the training data, or anything that could be easily created using conventional media editing software. We also present a novel clustering algorithm that is able to group sets of features, in an unsupervised fashion, based on spatial similarity of their activation maps. We demonstrated that this method is capable of finding sets of features that correspond to the generation of a broad array of semantically significant aspects of the generated results in both image and audio domains. This provides a more manageable number of sets of features that a user could interact with.In this paper, we have introduced a novel approach for the interaction with and manipulation of deep generative models that we call We have demonstrated that network bending is a framework that is sufficiently expressive and flexible that it has been used in different ways in the production of a number of artworks. We have shown how this framework can be utilised for creative expression in various workflows: either by controlled direct manipulation over specific semantic properties, or in an exploratory fashion by chaining multiple stochastic transformation layers. These different approaches can be used in both the audio and image domains.The inserting of deterministic filters into pre-trained models, has been adopted and utilised in the development and evaluation of the next generation of generative models, namely StyleGAN3 , which hIn future work we look to further advance our network bending framework in the audio domain . We


Skin biopsies of the penis are sometimes necessary to diagnose neoplasms and/or inflammatory eruptions in the groin. Little is published on proper technique, education, and/or comfort with performing genital skin biopsies, and it is an important skill for dermatologists to develop.To mitigate pain and alleviate anxiety surrounding a genital skin biopsy, the authors have found that the addition of topical anesthetic to the area requiring sampling for 30 minutes before the injection of intradermal lidocaine can greatly decrease the pain from both the needle stick and the burning associated with the injectable anesthetic. The epidermis of the penile skin is approximately 20 μm that allows for rapid penetration of topical medications.None disclosed.


Exposure to a face can produce biases in the perception of subsequent faces. Typically, these face aftereffects are studied by adapting to an individual face or category  and can result in renormalization of perceptions such that the adapting face appears more neutral. These shifts are analogous to chromatic adaptation, where a renormalization for the average adapting color occurs. However, in color vision, adaptation can also adjust to the variance or range of colors in the distribution. We examined whether this variance or contrast adaptation also occurs for faces, using an objective EEG measure to assess response changes following adaptation. An average female face was contracted or expanded along the horizontal or vertical axis to form four images. Observers viewed a 20 s sequence of the four images presented in a fixed order at a rate of 6 Hz, while responses to the faces were recorded with EEG. A 6 Hz signal was observed over right occipito-temporal channels, indicating symmetric responses to the four images. This test sequence was repeated after 20 s adaptation to alternations between two of the faces . This adaptation resulted in an additional signal at 3 Hz, consistent with asymmetric responses to adapted and non-adapted test faces. Adapting pairs have the same mean (undistorted) as the test sequence and thus should not bias responses driven only by the mean. Instead, the results are consistent with selective adaptation to the distortion axis. A 3 Hz signal was also observed after adapting to face pairs selected to induce a mean bias , and this signal was not significantly different from that observed following adaption to a single image that did not form part of the test sequence . In a further experiment, we found that this variance adaptation can also be observed behaviorally. Our results suggest that adaptation calibrates face perception not only for the average characteristics of the faces we experience but also for the gamut of faces to which we are exposed. The appearance of a face can be strongly affected by the faces seen previously, and many studies have examined the properties and implications of these face adaptation effects  and aftereffects are measured by showing that neutral test faces are biased away from the adapting category  from the University of Nevada, Reno, took part in the experiment. They included author OG. Observers provided signed, informed consent before participating in the experiment, which was approved by the University of Nevada, Reno’s Institutional Review Board, and conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). Optical corrections were worn where applicable.Fifteen  young adults , with eight trials in each. Following a similar procedure as Retter and Rossion , for theThe data were recorded using a BioSemi ActiveTwo system with a 128 Ag-AgCl active-electrode array  multi-notch filter with a width of 0.5 Hz was also applied to remove electrical noise at three harmonics of 60 Hz. The data were then segmented by trial, including 1 s before and after the beginning of stimulation. To correct for artifacts caused by eye blinks, independent component analysis (ICA) with a square matrix was applied /standard deviation of the baseline). Baselines were defined as the 20 bins surrounding the bin of interest (x), excluding the immediately adjacent bins  region of interest (ROI), comprising electrodes PO8, PO10, PO12, P10, and P8  in the orthogonal single condition. Baseline-subtracted amplitudes for the first three harmonics, excluding the second as this corresponds to the base stimulation frequency (6 Hz), were summed for each condition separately. The average of these summations across participants is shown for each condition in t-tests were used to separately compare the magnitude of responses in the complementary pair vs. orthogonal pair conditions, and the orthogonal pair vs. orthogonal single conditions. These analyses showed that response asymmetries in the orthogonal pair condition  were significantly greater than those in the complementary pair condition . Conversely, these same response asymmetries in the orthogonal pair condition were not significantly different to those in the orthogonal single condition .To compare the magnitude of the adaptation-induced response asymmetries across conditions, a sum of harmonics was calculated. Significant harmonics with To first visualize the recordings in the time domain, a more conservative Butterworth low-pass filter was applied to the data averaged across trials described at the end of pre-processing. This fourth order filter comprised a cutoff of 30 Hz, which is more typical of a filter used in ERP studies of face perception  to the second cycle (217–384 ms), as described in “Methods” section “Time domain analysis”. In tion see , with thtion see . As prevIn the preceding experiments, we presented evidence for contrast adaptation in face coding, using EEG. We next examined whether the effects of this contrast adaptation can also be observed behaviorally. To assess this, we explored a different and potentially sensitive measure of face aftereffects based on the logic of tilt aftereffects . They provided signed, informed consent before participating in the experiment, which was approved by the University of Nevada, Reno’s Institutional Review Board, and conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). Optical corrections were worn where applicable.The 11 participants included authors OG and SO and nine  students from the University of Nevada, Reno  and horizontal (0°–180°) axes see . HoweverExperimental sessions began with an initial 2.5 min adaptation phase in which participants were simultaneously adapted to images along one axis in one visual field and the other axis in the other field . Images were presented approximately 8.5 degrees to the left and right of a central fixation cross, measured from the center of the image. Participants were instructed to maintain fixation on the central cross throughout adaptation and test phases. Images were shown sequentially on a continual loop in a pseudo-random order, ensuring each image was seen an equal number of times and the last three images seen at the end of the sequence were never the three maximum expansion or contraction amplitudes. This was done to reduce possible recency contrast or assimilation effects. Each image remained on the screen for 500 ms with an inter-stimulus interval (ISI) of 0 ms. Additional 10 s “top up” adaptation sequences were shown after each trial, with each of the 20 faces shown for 500 ms each. Following the initial adaptation phase and an ISI of 500 ms, participants viewed two test images presented on either side of the fixation cross in the same locations as the adapting images. In a single testing session, these images were only from the 0°–90° quadrant or the 180°–270° quadrant. For these test images, participants were required to rate which of the two (left or right) appeared more horizontally expanded by pressing the corresponding mouse button (left or right). The order of presentation of the test images was determined using a double interleaved staircase. Interleaves began with the largest possible difference between the two images. For example, one interleave would start with the 0° image on the left and the 90° image on the right, and the other interleave would start with the 0° image on the right and the 90° image on the left. If a participant rated the right image as appearing more expanded, on the next trial a more contracted version was shown on the right and a more expanded version was shown on the left. Beginning with a maximum step size of an 80° adjustment , this was halved after each reversal such that after the fourth reversal the minimum 5° step size was reached. A reversal was defined as a change in responding such that images in the opposite visual field now appeared more horizontally expanded. Left and right images were adjusted in tandem, such that if one was increased by 5°  the other was decreased by 5° . Note that on some trials it was possible for both left and right images to be identical . As this was a forced-choice task, participants were required to select which image they nonetheless perceived as more horizontally expanded. Each interleave continued until 10 reversals had been reached. All participants reached 10 reversals within the maximum 40 trials. Points of Subjective Equality (PSE) were calculated by taking the average of the last four reversals of each interleave. A PSE indicates the angular distortion required for both left and right test images to appear equally distorted along the horizontal axis. If adapting to distortions along the horizontal vs. vertical axes were to have no effect or produce mean biasesThe experiment was run over four sessions, each separated by a minimum of 7 days to reduce potential adaptation effects carrying over between sessions. In half of the sessions, the adapting images on the left were from the horizontal axis (0°–180°) and images on the right from the vertical axis (90°–270°). In the remaining half of the sessions, this was reversed. Likewise, in half of the sessions, the test images were from the 0°–90° quadrant, while in the other half images were from 180° to 270° quadrant. Note that rather than comparing the effect of adaptation to a baseline we will be comparing the effect of adapting to one axis compared to the other.M = 53.51, SD = 6.26) compared to PSEs following adaptation to the horizontal axis . For test images between 180°–270°, PSEs are again larger following adaptation to the vertical axis  compared to adaptation to the horizontal axis . That is, in all cases, the PSE following adaptation shifted closer to the adapted axis. To allow for data from the two test quadrants to be analyzed together, data from the 180°–270° quadrant were re-scaled to range between 0°–90°. Data were analyzed using a 2 × 2 repeated measures ANOVA with the factors Adapting axis  and Test quadrant (0°–90° vs. 180°–270°). Analyses showed a significant main effect of Adapting axis  without a baseline noise subtraction. Adapting and test sequences were matched such that the first image seen in a test sequence was also the first image seen in the adapting sequence or a product of one of these images in the case of the single adapting image. If we take responses to be associated more with the image primarily presented in the same time window than the image not presented, these results indicate that the response changes from adaptation reflect a reduction in the amplitude of the responses to faces more similar to the adapting images. This would be consistent with predictions from models of face processing based on behavioral observations  by assuming a loss of sensitivity to that axis, or to the overall “contrast sensitivity” for that axis. However, an alternative is that the adaptation produced localized losses in sensitivity to the two adapting distortion levels . While the present experiments were not designed to test this alternative, we note that the latter account is more in line with the prediction of a multiple-channel model for the distortion levels, and is inconsistent with previous findings that adaptation to facial distortions instead reflects an opponent-like code .It is perhaps worth noting that in the article by Calder et al.  referencThe discovery of contrast adaptation in faces holds potentially important implications for our understanding of models of face processing. In addition to the more standard form of face aftereffects, in which perceptions are biased in a single uniform direction (e.g., Webster and MacLin, sharpening of the tuning curves of the neural populations sensitive to the adapted stimulus (Oruç and Barton, In the current experiment, we measured the perceptual effects of contrast adaptation in faces as a bias away from the adapting axis. However, in studies of spatial or color contrast, the effects of contrast adaptation have also been observed as a reduction in contrast sensitivity, resulting in a change in the thresholds for detecting contrasts (Blakemore and Campbell, We have presented evidence for contrast adaptation in face perception. This was observed both as changes in neural responses measured using EEG, likely reflecting a reduction in sensitivity to the adapted face axis, as well as behavioral changes in the appearance of subsequently viewed faces. These findings show that in addition to the human visual system adjusting to the average face to which the observer is exposed, adaptation can also selectively adjust to the range or variance of a set of faces. These contrast adaptation effects reflect a distinct form of face adaptation and may underlie effects that have previously been interpreted in terms of contingent face aftereffects.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Institutional Review Board, University of Nevada, Reno. The patients/participants provided their written informed consent to participate in this study.OG, TR, and MW contributed to conception and design of the study. OG, TR, and SO’N contributed to technical aspects of implementing the experiment and collecting data. OG and TR analyzed the data. OG wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: The burden of foodborne illness is considered to be high across the world.  Based on the Knowledge-Attitude-Practice (KAP) model, physician’s awareness is essential for conducting individualized treatments, thus reducing the burden of foodborne illness. However, there have been no validated questionnaires specific to the awareness of physicians with foodborne diseases. This study aims to develop and validate a KAP questionnaire for physicians to assess their awareness about the diagnosis and management of foodborne illness.  Results: A total of 160 physicians from both public and private primary health care centers were approached to enrol 125 study participants into the survey (response rate 78.13%). Of the 31 items designed for assessing the KAP of physicians on foodborne illnesses, three items were excluded after Cronbach’s α analysis. In total, 29 items were included in the final set of the questionnaire. Results of different validity and reliability analyses suggest the questionnaire has a high face and content validity as well as good reliability in internal consistency and stability. Conclusions: This study introduces a newly developed questionnaire with good reliability and validity values that can assess physician’s awareness of foodborne disease. The awareness questionnaire, as a study instrument, had a favourable acceptance among physicians. It is a sound method for evaluating and measuring levels of foodborne disease-related awareness among physicians in Abha, Saudi Arabia. Methods The questionnaire was developed in three phases: a comprehensive literature review, face and content validity, followed by a reliability test by internal consistency. A cross-sectional study was designed in Abha, Saudi Arabia. Physicians (n=125) were opportunistically recruited from both public and private primary healthcare centers. The questionnaire’s content and validity were confirmed by experts in their corresponding fields. After signing the informed consent, the study participants received the questionnaire to evaluate their KAPs on foodborne diseases.   The pattern of foodborne illness has changed dramatically due to the lifestyle and behavioral changes of the population. The frequency of foodborne illness outbreaks is growing because of newly discovered pathogens. The WHO has estimated that, globally, 1 in 10 people fall ill yearly and 420,000 die as a result of food contamination. However, the most recent data on the burden of foodborne diseases in the Kingdom of Saudi Arabia have not yet been published.Foodborne illness is a major, but preventable, public health problem across the world.Bacillus cereus andStaphylococcus aureus.The major concern in the Kingdom of Saudi Arabia is the hajj season, where millions of pilgrims come from different parts of the world. The government is very particular about the quality of food items in the food establishment. However occasionally there have been reports on foodborne disease outbreak due to Salmonella, According to the World Health Organization (WHO), populations in the developing countries including the Middle East, are more likely at risk of foodborne illness due to the restricted strategies in the disease surveillance and prevention and control programs. After the African and South-East Asian regions, it is estimated that the highest burden of foodborne diseases was reported in the Middle East and North African (MENA) region. Several studies, including literature reviews and primary studies related to foodborne illnesses in the Kingdom of Saudi Arabia have been conducted to assess the burden.–There has been a constant increase in the number of food poisoning cases in the past few years in the Kingdom of Saudi Arabia, especially during the summer and the Hajj season.Escherichia coli 0157:H7 were reported in many countries.,Most of the countries across the globe have some kind of mechanism to report foodborne illness. In the last ten years, countries such as Canada, England, Japan and the United States generated an annual report on the cases of foodborne diseases. It is apparent that the cases of staphylococcus intoxication have decreased in most of the countries except in Latin America, due to high consumption of unpasteurized milk and cream-filled desserts. However, the cases of salmonella increased all over the world and new agents such asVibrio vulnificus septicaemias have been increasingly reported during the last few years in hospitals in these regions, especially in the Gulf of Mexico states. The patients are more likely to die if the treatment is not given at the appropriate time. The death associated with foodborne diseases is multifactorial and it is also based on the toxicity of the agents.Cases ofHepatitis E is one of the major public health issues across the world and is transmitted through the contaminated food. The sporadic cases of hepatitis E is widely reported in many industrialized nations including the Europe, Asia and North America. The burden due to hepatitis E can be reduced through effective disease surveillance program and health education. Primary health centers are considered to be the entry point in to the health care delivery system for the population in the specific country.The level of awareness among the public regarding the food safety has been increasing in the last few years. Though the national statistics of several countries showed a steady decrease in the foodborne illness; still the threat to the population continues due to new emerging pathogens. In order to tackle the new emerging pathogens international organization introduced a risk based approach such as Acceptable Level of Protection (ALOP) and Food Safety Objectives (FSOs). General physicians play an important role in the detection and treatment of foodborne illness as they are the first point of contact and a trusted primary source of information for the general public. Primary health centers are the first point of contact of the healthcare delivery system, where people in all countries visit for accessing the healthcare services.General physicians play an important role in the detection and treatment of foodborne illness as they are the first point of contact and a trusted primary source of information for the general public.Physicians play a significant role in communicating public health messages to the patients, as the information given is trusted by the patient. Therefore, the physicians must provide information regarding foodborne diseases, at least to the vulnerable population. However, some physicians may not value the counselling session provided for the patients about the foodborne diseases due to the lack of knowledge on food safety, lack of time and lack of perceived benefit.Even though there are common guidelines for the diagnosis and treatment of foodborne illness, these vary across physicians. The diagnosis and treatment procedures also vary between physicians working in public and private primary healthcare centers. The literature indicates that misunderstandings occur between the healthcare providers and the patients due to the absence of cultural knowledge and awareness, as well as through the lack of understanding and flexibility.,, The self-administered questionnaire is a tool for assessing the insight and experiences of individuals who work alongside the healthcare organization. It is also considered to be another way for evaluating the acceptability and awareness about the multiplicity in healthcare institutions.Furthermore, a one-dimensional biomedical perspective is frequently found among the healthcare service providers rather than a holistic perspective for providing patient care.Validated and reliable instruments are lacking for the measurement of the knowledge, attitudes, and practices (KAPs) regarding foodborne illness among physicians in the Kingdom of Saudi Arabia, as well as in all the Gulf Cooperation Council (GCC) countries. The aim of this study was to construct a valid and reliable instrument for assessing the KAPs of physicians in the Kingdom of Saudi Arabia toward foodborne illness.; the sample size has been calculated with a 5% margin of error, and confidence interval of 95 %, a response distribution of 50% and a total population size of 180 (n = 180). The final sample size was n = 125.This is a cross-sectional study conducted in the selected public and private primary health care centers in the city of Abha located in the south western region of Asir in the Kingdom of Saudi Arabia. By using the Raosoft sample size calculatorMultistage cluster sampling was used in order to recruit the physicians from the selected public and private primary health care centers. A formal permission was obtained from the ministry of health for conducting this particular study on primary health care centers. Permission from the private primary health care centers was obtained separately in order to collect the data for this study.Physicians in the selected public and private primary health care centers in the city of Abha were approached. Individuals who agreed to participate and had given written consent were included in this study.There were various phases involved in developing the KAP tool for confirming the validity and reliability. The items in the instrument were designed by a group of experts from the fields of nutrition, microbiology and public health during the first phase. The pilot study, in addition to face, content, and construct validity  was carried out to determine the validity and reliability of the questionnaire. Factor analysis and the test-retest reliability were performed to ensure the internal consistency and the stability of the questionnaire. Same study participants were asked to complete the questionnaire for the second time within the interval of seven days, to measure the test-retest reliability.The questionnaire was distributed to 125 physicians from both the public and private healthcare sectors to collect information about foodborne illness. After collecting the completed questionnaires, each response was examined carefully looking at the consistency of the answers indicating the questions were widely comprehensible. The questionnaire was then modified to enhance its clarity.To appraise the face validity of the questionnaire, ten experts from the Department of Public Health, College of Health Sciences, Saudi Electronic University were selected based on their research experience. They were provided with the questionnaire and the specific objectives of this research. The experts were asked to provide their opinions about the questionnaire related to these research objectives. The feedback from the experts regarding the questionnaire was accepted and incorporated to endorse the face validity.To improve content validity, the experts were selected based on their experience in epidemiological research, as determined by their number of peer-reviewed publications derived from the PubMed using the keywords “foodborne illness in the Kingdom of Saudi Arabia”. Totally around 15 experts were approached however only 7 accepted the invitation and evaluated the questionnaire with their expertise. The specialist team included 3 public health professionals, 2 microbiologists, and 2 nutritionists. Their recommendations and perspectives were deliberated and integrated into the questionnaire, thereby helping to establish the content validity of the questionnaire. Knowledge, in this paper, refers to the accurate technical knowledge among the physicians about foodborne illness, whereas attitude represents the perceptions of physicians regarding foodborne illness. Practices denote the existing management and treatment modalities that the physicians follow when handling food poisoning cases. The questionnaire comprises of four sections. Section one consists of eight questions on collecting various socio-demographic information from the physicians; section two consists of seven questions for determining the knowledge level among the physicians about foodborne diseases; section three consists of seven questions describing the perceptions of physicians about foodborne illness; and section four consists of ten questions for evaluating the current practices of physicians related to the diagnosis and management of foodborne diseases.The final version of the questionnaire contains information about the KAPs related to foodborne illness and it is available as an extended data. The internal consistency of the questionnaires was determined using Cronbach's α at a satisfactory level that varied between 0.70 and 0.95., Pearson's correlation coefficient was used to calculate the test-retest reliability. Cross tabulation and the kappa measure of agreement (k) were used to measure the test-retest agreement of the KAP questionnaire. A two-sided p-value <0.05 was considered statistically significant. As per Cade et al. large correlation coefficients were defined as 0.5 or greater, which indicated higher reliability., The strength of agreement was calculated using kappa, and according to Masson et al., the kappa measure of agreement (k) can be classified as follows: poor (<0.20), fair (0.21–0.40), moderate (0.41–0.60), good (0.61–0.80), and very good (0.81–1.00).The data analysis was carried out using SPSS . The raw data of the food Poisioning study has been deposited as underlying data (v5.5).Ethical permission was obtained from the research ethics committee from the College of Medicine, King Khalid University, Abha, Kingdom of Saudi Arabia (REC#2017-03-08). The study was conducted in Abha, Asir Region, where King Khalid University is a designated institutional ethical committee for providing approval for all the research that are confined to the Asir Region. Written consent was obtained from all study participants. Anonymized data were used for analysis and interpretation. The questionnaire and the consent form were securely stored in locked file cabinets and access was given to the specific researchers involved in data analysis.A total of 125 from 160 physicians who participated in this study were selected from the government and private primary healthcare centres in the Abha city, with a response rate of 78.13%.Majority of the physicians (41.6%) were in age group of 35-44 years, 68.8% were male and 35.2% practice family medicine. Majority of physicians (54.4%) reported practising experience of 6-15 years. The internal reliability between the questions was calculated by using Cronbach's α. Our KAP questionnaire on foodborne illness showed adequate internal uniformity (α = 0.723). Numerous previously published studies on Cronbach's α have projected a satisfactory α value that varied between 0.70 to 0.95 for this test., The results of the present study, α = 0.723, are supported by the values mentioned in recently published research articles. A study conducted in Iran for assessing the KAPs of disaster preparedness reported an internal consistency of α = 0.785, which is somewhat greater than the current study. Another study conducted in Malaysia for assessing the KAPs related to dengue fever prevention, also demonstrated internal consistency with Cronbach's α = 0.798, which is higher than the results of the present study.A similar value of Cronbach's α was obtained in a study aimed at measuring the KAPs for the prevention of dengue fever among the male population in the Maldives. A study among Iraqi patients about the KAPs related to immunization, reported an internal consistency with Cronbach's α score of 0.812, which is also higher than that observed in our study.A study was conducted among 125 physicians from selected governmental and non-governmental primary healthcare centres in Abha city to evaluate the KAPs among physicians toward foodborne illness. The content and face validity assessments were completed by specialists in related fields, inclusive of microbiologists and public health practitioners. Item clarity was tested by conducting a pilot study among these 125 physicians. The same evaluations of the face and content validity were performed in a study conducted in Malaysia to validate the questionnaire on KAPs related to lifestyle. Similarly, a study in Malaysia of a KAP questionnaire among the childcare providers reported a Cronbach's α coefficient ranging between 0.89 to 0.90, which is much higher than the present study.A study conducted in Spain for assessing the development and validation of the questionnaire related to academic stress in secondary education found that the internal consistency Cronbach's α value is 0.77, which is slightly higher than the current study. A similar study conducted among Iranian adults regarding the KAPs related to oral health reported a Cronbach's α of 0.82, which is higher than the value reported in this study. To determine the KAPs regarding vitamin D among adults in Tehran, Amiri P. et al. presented an internal consistency value of 0.60, which is less than recorded in our study.Likewise, a study conducted in Iran for evaluating the KAPs related to obesity among adults and adolescents revealed a Cronbach's α score of 0.72, which is similar to the current study. on the test-retest reliability of a new questionnaire on diet and eating behaviors, found that the correlation coefficient was high for most questions, which supports the results of this study.The current study results showed that the correlation coefficient was high for many questions in the KAPs questionnaire about foodborne illness. The results of a study by Rachel et al. in Brazil on the reliability of a questionnaire for the assessment of food safety knowledge, perceptions, and practices found significance in stability and reliability of the questions. Comparable results were observed in the studies that were conducted previously about the knowledge, perceptions and behaviors related to food safety, which also support the results of the current study.,The present study indicated that 29 of 32 items had a good level of reliability. Similarly, a study conducted by Luísa. et al.There are certain limitations in this study. Although the study had representative samples of physicians from both public and private primary health care centers; the sample was drawn only from one particular region (Asir region) in the Kingdom of Saudi Arabia. Self-reported questionnaire was the primary source for collecting the information from the physicians, therefore, the quality of information delivered by the study participants is arguable.A questionnaire was framed and developed to evaluate the KAPs among physicians toward foodborne illness. It was shown to have adequate validity and reliability. This questionnaire can be classed as a noteworthy instrument for assessing the KAPs related to foodborne illness among physicians across the country. The study highlights the importance of a standardized questionnaire to assess KAPs among physician towards foodborne illness to initiate an appropriate interventional program for physicians to reduce the burden of foodborne illnesses.http://doi.org/10.7910/DVN/QP1KVI21.Harvard Dataverse, V1: Data-Food Poisoning.The project contains the following underlying data:[Data-Food Poisioning] .Harvard Dataverse, V1: “Data-Food Poisioning”.https://doi.org/10.7910/DVN/G67UW3.•Annexure 1: Questionnaire on Socio-demographic Variables•Annexure 2: Questions regarding the knowledge, attitude and practices about food borne illnessThis project contains the following extended data:Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).Data are available under the terms of the This  paper submitted to your journal evaluated to possible methods of reducing the burden of foodborne illness. In this study, the author to try to develop and validate a KAP questionnaire in order to assess, diagnose and take charge of foodborne illness. This study was carried out on 125 study participants. This manuscript is well structured and which deals with a topical subject and which deals with a real problem which affects the people to the whole world. I give a favorable opinion for the indexing of this manuscript without changes. After reading, my conclusion is that this version has been revised well and the responses to the comments and suggestions of the reviewers are clear and therefore this version can be accepted for indexing in this form.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?No source data requiredIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Food and human diseasesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. General comments:This is a significant study concerned with the development of tools used to investigate knowledge, attitude, and practices of physicians engaged in the diagnosis and treatment of food-borne diseases.The study tackles important issues related to food safety KAP and it participates actively in providing knowledge about physician food safety KAP. However, food safety descriptive findings related to knowledge attitude and practices could be included in the manuscript to maximize the benefit of this research for instance the descriptive data could be extended beyond the demographic data to Include (concisely) the major findings of physician knowledge attitude and practices instead of presenting them only in the forms of Internal consistency and test-retest reliability.Nevertheless, the study gives a deep inside look at the construction of the questionnaire in terms of reliability and validity and it gives substantial weight to general questionnaire construction techniques.Specific comments:Abstract:The phrase ‘Physicians (n=125) were opportunistically recruited’ does not clearly reflect the multistage cluster sampling technique applied for selected public and private primary health care centers mentioned in the method sectionIntroduction:In the 2nd paragraph, line 2 the sentence ‘The government is very particular about the quality of food items in the restaurant; may need modification to reflect more generalized food control activities i.e., food establishments instead of the phrase ‘the restaurant’.Bacillus cereus andStaphylococcus aureus should be in italics .In the same paragraph bacterial namesEscherichia coli (paragraph 4 line 5) should also be italicized.The bacterial namesVibrio vulnificus (paragraph 5 line 1).Same should be done forParagraph 6 needs revision to specify the Saudi government, a slight reordering of the sentences in this paragraph will increase its readability.I suggest merging Paragraphs 7 and 8 to avoid redundancy in specifying the importance of the Physicians roles in food safety.Methods:A slight change in the abstract is needed to reflect the methods followed in selecting samples.It appears to the reader that evaluating face validity and evaluating content validity for the questionnaire were done in the same way, hence no need to repeat the sentences, I suggest merging the evaluation of face and validity.In the sentence ‘experts were randomly selected from the authors listed in the publication derived from the PubMed using the keyword “foodborne illnesses”'. It is not clear if the author includes Saudi Arabia among search keywords? More elaboration is needed here about the responders’ number and distribution in fields.The questionnaire:Some of the questions, for example, question 13 could have had been asked with less ambiguity for example question 13 (The target microorganism in canning is?) could be asked in a more straightforward way (i.e. The most encountered food poisoning microorganisms from canned food is?).Some of the questions regarding the knowledge, attitude, and practices about foodborne illness are barely related to food safety issues generally tackled by physicians, for example, question 19 is quite lengthy and hardly fulfills the required target. In annexure 2:Results and discussion:These are professionally written sections with clear tables and main finding paragraphs.I could not find the descriptive results of the findings related to knowledge, attitude, and practices of physicians towards food safety. It seems that it is the author's preference not to present descriptive data in this regard. Adding such data will benefit readers from the field with fewer statistics knowledge and increase the manuscript audience.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?I cannot comment. A qualified statistician is required.Are all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Food safety, bacteriology, Public healthI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. We have incorporated the reviewer comments and uploaded the new version of the manuscript.


To develop a method to perform quality control (QC) of X‐ray tubes and automatic exposure control (AEC) as a part of the QC of the radiographic and fluoroscopic X‐ray system. Our aim is to verify the output from the X‐ray tube by comparing the measured radiation output, or air kerma, to the theoretical output given the applied exposure settings and geometry, in addition to comparing the measured kV to the nominal kV. The AEC system for fluoroscopic and conventional X‐ray systems is assessed by determining the absorbed dose to a homogenous phantom with different thicknesses.phantom). The following input is needed: a parameterized model of the X‐ray spectrum, the X‐ray tube measurements using a multifunctional X‐ray meter, the exposure parameters recorded via imaging of polymethyl methacrylate (PMMA) slabs of different thickness that simulate the patient using AEC, and a parameterized model for calculating the dose to water from Monte Carlo simulations. The output is the entrance surface dose (ESD) and absorbed dose in the phantom, Dphantom (µGy). In addition, the parameterized X‐ray spectrum is used to compare theoretical and measured air kerma as a part of the QC of the X‐ray tube. To verify the proposed method, the X‐ray spectrum provided in this study, SPECTRUM, was compared to two commercially available spectra, SpekCalc and Institute of Physics and Engineering in Medicine (IPEM) 78. The fraction of energy imparted to the homogenous phantom was compared to the imparted fraction calculated by PCXMC.This study presents a model to verify the X‐ray tube measurement results and a method to determine the dose to a homogenous phantom  with the materials Al (2.2–8 mm), Cu (0–1 mm), and any combination of the filters, PMMA and water. The deviation of energy imparted from the results by PCXMC was less than 8% for all measurements across different kV, filtration, and vendors, obtained by using PMMA to record the exposure parameters, while the dose was calculated based on water with same thicknesses as the PMMA.This study presents an accurate and suitable method to perform a part of the QC of fluoroscopic and conventional X‐ray systems with respect to the X‐ray tube and the associated AEC system. The method is suitable for comparing protocols within and between systems via the absorbed dose. The filtration and X‐ray beam qualities vary, leading to changing corresponding dose ranges. According to IAEA, there are two reasons for determining patient dose: (a) setting and checking protocol standards and (b) assessing detriment for justification and risk assessment.There is risk associated with high patient doses due to the use of automatic choice of exposure parameters. In radiography, the automatic exposure control (AEC) often adjusts the exposure time to obtain constant detector dose for a given kVp and mA. For fluoroscopy, the system often selects the filtration, kVp and mAs, usually denoted as automatic dose rate control (ADRC). For the sake of simplicity, it is denoted AEC further in this paper, regardless of whether it refers to radiography or fluoroscopy. Application of AEC may result in high milliampere‐seconds (mAs) or suboptimal tube voltage (kV) and filtration. An unintentional increase in the dose may occur due to changes in AEC during equipment servicing or because of dose creep resulting from nonoptimal use of AEC.It is crucial to have QC procedures that accurately monitor dose and equipment output. The X‐ray spectrum affects both the imaging properties and the dose. Knowledge of the X‐ray spectra provides important information regarding how the spectra change if the filtration, current or voltage values change. Hence, this knowledge provides an opportunity to calculate the energy imparted, which depends on the X‐ray beam quality, field size, and irradiation geometry.Models of X‐ray spectra have been available for decades,The main aim of the present work was to establish a method for which the calculation of the energy imparted can be used frequently as part of QC for a conventional and fluoroscopic X‐ray laboratory. We expect this method to provide the medical physicist with knowledge of the X‐ray spectra and, thereby, important information about parameters that could affect the dose and image quality.2To derive the energy imparted, an accurate prediction of the photon spectrum emerging from the X‐ray tube is required. In the present work, the theoretical spectra of Birch and Marshallphantom) using the following four input data: (a) a parameterized model of the X‐ray spectrum, (b) the measurements of the X‐ray tube using a multifunctional X‐ray meter, (c) the exposure parameters, obtained from imaging polymethyl methacrylate (PMMA) slabs of different thicknesses that simulate the patient, using AEC, and (d) the calculation of the dose to water using Monte Carlo simulation for a simple cylindrical geometry and the associated parameterization of the energy fluence. The output is the entrance surface dose (ESD) and the absorbed dose in the phantom (Dphantom [µGy]). In addition, a parameterized X‐ray spectrum enables QC of the X‐ray tube by comparing the measurements obtained using a multimeter with the theoretical results for the actual exposure settings and geometry.In this study, we present a method for determining the absorbed dose to a homogenous phantom (D2.12.1.1ε) to the matter in a certain volume is defined by the ICRURin is the radiant energy incident on the volume, namely, the sum of the energies (excluding rest energies) of all the charged and uncharged ionizing particles that enter the volume. Rout is the radiant energy emerging from the volume, namely, the sum of the energies (excluding rest energies) of all the charged and uncharged ionizing particles that leave the volume. ΣQ is the sum of all the rest mass energy changes for the nuclei and elementary particles in any nuclear transformations that occur in the volume. Considering the X‐ray energies applied in diagnostic imaging, ΣQ is approximately zero, due to the absence of annihilation or pair production, and Rin is the energy of the primary photon incident on the volume. Therefore, the ε to the patient is simplified toIF is the imparted fraction that decreases with increasing energy, which also represents the total energy deposited in a patient undergoing a radiological examination. Assuming that the focal spot can be approximated as a photon point source, the radiant energy that is incident on the area, A, of the registration due to the energy fluence of photons, Ψ, at the angle of incidence, θ to the normal of the area element, dA, is described by Ref.  corrects for relativistic effects, θ is the target angle, N is Avogadro's number, ρ is the density, A is the atomic weight, and Q is the X‐ray energy intensity per unit energy interval per incident electron flux per atom. dT/dx is given by the Bethe equation,C is the Thomson–Whiddington constant.The X‐ray intensity produced in a solid target is obtained via integration along the electron path to the point where the electron energy, The Birch and Marshall's theoretical spectra, supplemented with data for the characteristic radiation from the tungsten target, were integrated into a Microsoft Office Excel 2010 spreadsheet (SPECTRUM) for general and daily use. The input parameters were the kV, mAs, distance between the X‐ray tube and the detector, referred to herein as the source‐to‐image distances (SIDs), and thickness of the filtration or object in the X‐ray beam. The spectra may be computed for any desired target angle (1–25°) and tube voltage between 40 and 150 kV with the use of attenuation data for these materials: Al, Cu, Pb, Be, C, Sn, I, water, PMMA, air, muscle, and bone. This spreadsheet provides the mean photon energy, air kerma, energy fluency, photon fluency, and HVL for an X‐ray beam traveling through a given combination of these materials.2.1.3The Monte Carlo calculations were designed specifically for these spectra and were performed using cylindrical symmetry, to decrease the computational time. In the simulations, a cylindrical water phantom was centered inside a larger cylindrical air phantom. A cone‐shaped X‐ray beam originating from the focal spot entered the phantom in such a manner that the central radiation of the beam coincided with the cylinder axes. Both phantoms were divided into ring‐shaped dose‐accumulation voxels. The air phantom was 120 voxels high with a 60 voxel radius, and the width of a voxel was set to 20 mm. The height of the water phantom varied between 40 and 300 mm, and the radius was set to 120 mm. The SPD for the water phantom was set to 1500 mm. The field radius of the X‐ray beam entering the water phantom was 50 mm; see Figure 9 photons were simulated in total. The energy loss from primary and scattered photons was recorded separately. The energy loss from primary photons was recorded in special voxels that were adapted to the cone‐shape of the X‐ray beam to avoid unnecessary partial volume effects and to reduce the amount of stored data.The incident X‐ray photons had energies ranging from 1 to 150 keV at increments of 1 keV. All the interactions, such as Compton scattering, coherent, and photoelectrical effects, were tracked through the air and water, and all the energy losses were registered until the photons came to rest or left the air phantom. The atomic interaction cross sections and form factors were from Hubbell et al.2.2To achieve an applicable theoretical calculation of air kerma and absorbed dose to a homogenous phantom for QC purposes, they were parameterized as function of standard exposure parameters applied in an X‐ray laboratory.2.2.1AK. This was done in two steps. Step one is a parameterization of a preliminary air kerma, KA,prelim, where Cu filtration is excluded. This parameterization was given byU is the tube voltage and TF is the total filtration without added Cu filters (mm Al). This calculated TF includes filtration through the X‐ray tube glass and Al‐filters, if built‐in or added. The 25 ija values were obtained from the best fit of a rational function with fourth‐order polynomials for any voltage and TF values.In the proposed method, the calculation of the X‐ray spectrum emerging from an X‐ray tube was obtained by parameterization of the air kerma, AK,prelim as a reference and is given byStep two is a parameterization of the transmission through Cu filters (mm Cu) with ijka values were obtained from the best fit of a three‐dimensional exponential polynomial for any voltage, TF (without Cu) and Cu filtration values.The 48 A is given byAK. In the Excel sheet, TF is the filtration through the X‐ray tube glass and built‐in filtration, and added Al is recorded separately. However, in the estimation of KA,prelim according to Equation (6), the sum of TF and the external added Al is applied. The nominal input values includes the distance from the source to the X‐ray meter, referred to herein as the source‐to‐detector distance (SDD), additional mm filtration of Al or Cu, applied focal spot , kV, mA, and ms or mAs and pulses per second (pps) for fluoroscopic imaging. Input values from the X‐ray multimeter measurements are tube voltage in kV, exposure time in ms and air kerma in µGy for radiography and µGy/s for fluoroscopy. The outputs include the theoretical air kerma at an SDD of 1 m, the measured value for the air kerma at 1 m, the associated deviation, the discrepancies between the nominal and measured values for the kV and exposure time, and the DF and TF. If any earlier estimates for TF and DF exist, they are included in the spreadsheet. If it is the very first measurements for the actual X‐ray tube a measured TF can be input as the first guess for TF in the model, and the DF values are set to one. Previous measurements of the X‐ray tube can be included in the spreadsheet; however, they can be emphasized less. In the present work, the weighting was performed by reducing the influence of the deviation between the measured and calculated air kerma on the determination of TF and DF. The DF and TF values are applied in an Excel sheet to determine the dose to the homogenous phantom based on recorded exposure parameters, which were applied using AEC as described in Section 2.2.3.Applying the input parameter tube voltage (kV), mAs, and the distance between the focal spot of the X‐ray tube and the detector (SDD), K2.2.2U is the notation for tube voltage (kV) and E is photon energy (keV). The values of ija were derived from the best fit of a two‐dimensional polynomial for any values of the voltage and photon energy. The simulated air kerma from the primary photons multiplied by the beam cone‐shaped area yielded the KAP.As shown in previously published studies, the fluence can be parameterized.2.2.3pT is the transmitted energy fraction of the primary photons and Sε and Pε are the fractions of the ε from the scattered and primary photons, respectively. On this basis, the parameterization of the transmitted energy from the primary photons, Tp, in the water phantom was given byt is the thickness of the water phantom, Ψ is the energy fluence from the Monte Carlo calculations and AK is the air kerma derived from the Birch and Marshall spectra. The ija values were obtained from the best fit of a three‐dimensional exponential polynomial for any values of the energy fluence, air kerma, and thickness of a water phantom.The imparted fraction of the energy was summed over the total water phantom given by the Monte Carlo calculations. The primary photons that register as escaped or unhindered in the Monte Carlo data were excluded since they do not contribute to the energy. The imparted fraction was calculated using Equation 19:(10)IFε from both the primary photons and the scattered photons was based on the same equation:t is the thickness of the water phantom, U is the tube voltage, Ψ is the energy fluence, and AK is the air kerma. The aij values were obtained from the best fit of a three‐dimensional exponential polynomial for any values of energy fluence, air kerma, and thickness of a water phantom. However, the aij values were different for Pε and Sε. The corresponding values for the air kerma and energy fluence were calculated for different beam qualities. This relationship was parameterized asThe parameterization of the Using Eq. , the dos2.3In order to validate the method, the SPECTRUM, the parameterized air kerma, and the dose to homogenous phantom were compared to previously published methods or measurements.The proposed method to calculate air kerma was verified by comparing SPECTRUM to two commercial spectra, SpekCalcThe absorbed dose to a homogenous phantom was verified through calculations using PCXMC.This paper includes results from four different laboratories representing five different X‐ray tubes and generators, a variety of imaging technique parameter settings , and vendors, as described in Tables 3In this study, the parametrization of the air kerma is embedded in an Excel spreadsheet. The spreadsheet provides immediate feedback on the multimeter measurements of the X‐ray tube compared to the theory. The measurement conditions, including the SDD, kV, mAs (or mA and ms), pulses for fluoroscopic imaging and filtration, are recorded in the spreadsheet. This method is the most convenient if the results from the multimeter are automatically transferred to the spreadsheet. The input information to determine the absorbed dose to the homogenous phantom is acquired by imaging a phantom of different thicknesses using AEC. Hence, one can perform QC of the X‐ray tube and obtain easy access to the energy imparted to a homogenous phantom, which is shown to correspond to actual patient doses.3.1A comparison between the spectrum calculated using the SPECTRUM Excel sheet and the two commercially available X‐ray spectra, IPEM 78 3.2y‐axis. Figure R2  and length (cm) change. Because all types of X‐ray laboratories can be controlled by the same method, Dphantom can also be used to compare examinations, or protocols, at different laboratories. The doubling of Dphantom indicates twice the absorbed dose to the patient, regardless of the applied exposure parameters. The reason for this large dose effect is that these measurements reveal the differences between the different laboratories and different modalities regarding the applied kV, mAs, and filtrations using AEC. The presented method is well suited to estimate the energy absorbed by a homogeneous phantom, Dphantom, which is useful for application in acceptance tests and QCs of AEC systems. Typically, there is no need to perform QC measurements of the TF and reproducibility of the radiation output using exactly the same geometry and exposure settings. This is because the TF and reproducibility of the radiation output are obtained by the same measurements that are performed to estimate the TF and DF for determination of the dose to a homogenous phantom. Another advantage of this method is that there is no need for a multimeter in the image field when AEC is assessed.Figure phantom is calculated for representative procedures to notice changes from one control to the next. If the X‐ray equipment or the protocol changes, it may affect the Dphantom and image quality. This method is an effective tool to optimize protocols and compare protocols within and between X‐ray systems, especially for new systems lacking exposure parameters and dose values from patient examinations. For instance, if an X‐ray system is replaced by a new system from a vendor that promises to give a lower dose by a certain percent, this dose can be verified using the proposed method to determine the actual dose to the homogenous phantom. Hence, protocols can be adjusted with respect to dose before the first patient is even imaged. However, the concept of a dose to a homogenous phantom should not be used in isolation because it is always necessary to obtain the required diagnostic information. The presented method is limited to X‐ray tubes with tungsten anodes. The implementation of this method requires only a simple template spreadsheet to run iterative calculations and a multimeter that can link to the actual spreadsheet. This linkage allows the measurement results to be automatically populated in the spreadsheet, as shown in Figure phantom   phantom Equation , 24 aijEquation , 16 aijEquation , and 14Equation . These E5ε for conventional and fluoroscopic imaging for any PMMA thickness, filtration, kV, and geometry . This calculation method is easily accessible in an Excel spreadsheet. The presented method has the advantages that absorbed doses from a large number of protocols and a wide range of patient sizes are easily obtained through a few measurements for each piece of X‐ray equipment. The corresponding results are provided immediately, and it is possible to perform calculations to investigate the absorbed dose impact from any changes in the exposure parameters, such as filtration and kV. The method allows dose comparison from protocols within and between the systems. In addition, it gives the user automatic feedback on the measurement results from a multimeter compared to the model. Hence, it is possible to immediately reveal whether the measurements are performed under the intended conditions. The presented method is useful as a part of QC of the X‐ray tube and appropriate Dphantom on periodic basis, and optimization of X‐ray systems.We provide a method for computing the 6None.