F and t tests. Over the years, there has been a movement from data transformation toward model reformation—the use of non‐normal error structures within the framework of the generalized linear model (GLM). The principal advantage of model reformation is that parameters are estimated on the original, rather than the transformed scale. However, data transformation has been shown to give better control over type I error, for simulated data with known error structures. We conducted a literature review of statistical textbooks directed toward biologists and of journal articles published in the primary literature to determine temporal trends in both the text recommendations and the practice in the refereed literature over the past 35 years. In this review, a trend of increasing use of reformation in the primary literature was evident, moving from no use of reformation before 1996 to >50% of the articles reviewed applying GLM after 2006. However, no such trend was observed in the recommendations in statistical textbooks. We then undertook 12 analyses based on published datasets in which we compared the type I error estimates, residual plot diagnostics, and coefficients yielded by analyses using square root transformations, log transformations, and the GLM. All analyses yielded acceptable residual versus fit plots and had similar p‐values within each analysis, but as expected, the coefficient estimates differed substantially. Furthermore, no consensus could be found in the literature regarding a procedure to back‐transform the coefficient estimates obtained from linear models performed on transformed datasets. This lack of consistency among coefficient estimates constitutes a major argument for model reformation over data transformation in biology.Statistical analyses are an integral component of scientific research, and for decades, biologists have applied transformations to data to meet the normal error assumptions for  Ives’  transformation of the response variable; and (3) a GLM . Given the prevalence of count data in ecological research, we focused the literature search and model comparisons to this type of data so that the results presented here are of interest to ecologists and biologist.Given repeated recommendations to replace data transformation with GLM procedures, we investigated whether statistical textbooks for biologists continue to recommend data transformation for the analysis of count data. We also recorded the prevalence of data transformation versus model reformation in the peer‐reviewed literature over the period of 1980–2017, that is, when the majority of the textbooks consulted were published. We then extended the analysis of Stroup , Ives 2, and War2For the literature review, we divided our search into two categories: textbooks and journal articles published in the refereed literature. In the first, we consulted over 50 statistical textbooks published since 1980  and noted whether the author(s) recommend the use of transformations or of GLM/GLMM when confronted with non‐Gaussian data . We focused our review on general‐purpose textbooks that are suitable for use in undergraduate and graduate levels statistics courses, as they are comprehensive in nature and represent that to which most students and researchers will be exposed. Hence, speciality textbooks focusing on GLM have been excluded, despite their abundance in recent years. The list of publications consulted and their recommendation for the analysis of data with non‐normal error structure is presented in Appendix Snedecor Abnormality, non‐additivity, and heterogeneity of variance ordinarily appear together. It would be ideal if transformation could remedy all the difficulties, but that doesn't often happen. Data transformation to address problems of non‐normal or heterogeneous errors does not appear in any of the 12 editions of Fisher’ text (1925 through 1954). Nor does it appear in the first four editions of Snedecor (y) where y is the response variable). Text recommendations for the use of GLM begin with McCullagh and Nelder The first recommendation for transformation that we could find in a text appears in Snedecor and Cochran  with a bEcology, Oikos, Journal of Animal Ecology, Ecology Letters, Plant Biology, Journal of Ecology, Nature, Plant Ecology, Marine Biology, and Marine Ecology Progress Series. The list of publications consulted and the statistical method applied in each (either transformations or GLM/GLMM) is presented in Appendix For the second part of our literature review, we used Google Scholar to find articles published in peer‐reviewed journals in the fields of biology and ecology presenting original research in which analyses are conducted on count data and determined whether the authors had transformed their data or applied a GLM/GLMM. We used the keywords “count” or “count data” and focused on articles published after 1980. In order to cover both terrestrial and marine publications, we concentrated our efforts on ten ecology journals that publish mainly original research and are influential in their respective fields (as marked by their relatively high impact factor score and citations): The results of the literature review of journal articles show that all the articles published before the year 1996 used the classical approach of applying a transformation to the response variable prior to analysis. The proportion of articles using GLM increased in the following decades: from 4% of the publications using these models between 1996 and 2000, to 43% between 2000 and 2005, and to approximately 52% after 2006. This trend may be due at least in part to the increasing availability of software packages that allow easy application of GLM/GLMM and to increasing knowledge of these software among researchers. It may also be due to the rise in number of articles critiquing the use and outcomes of data transformation, as discussed in our introduction. However, the increasing number of researchers (as indicated by articles published in the primary literature) favoring GLM/GLMM over transformation cannot be linked to general‐purpose texts, which continue to recommend transformation Figure . It is p33.1To contrast the difference in results when using transformation (square root and log) and reformation (GLM), we applied and compared different models to 12 analyses of count data obtained from the landmark text of McCullagh and Nelder y + 1) where y is the response variable) and running a linear model, and (3) running a GLM with either a Poisson or negative binomial distribution, depending on which was more appropriate from examination of residual plots. The residual versus fit plots, the outcome of the test statistic , and the value of the coefficients  were compared among the models applied to each dataset. The models for each dataset, as well as the resulting comparisons, are presented in Appendices Each dataset was analyzed in three different ways by (1) applying a square root transformation to the response variable and running a linear model; (2) applying a log transformation  from the linear model applied to the square‐root‐transformed data, a back‐transformation was necessary. For categorical analyses, we first obtained the estimate of the “transformed” mean for each factor by calculating the sum of each factor added to the value of the intercept estimate, as is the procedure for calculating means from the estimates of a model with the identity link . Then, the value of each “transformed” mean was squared to return the values to the original scale. In the case of regressions, the “transformed” estimates of the intercept and the slope were squared to place them back on the original scale, and when the uncorrected estimate was below zero, the negative sign was retained after squaring to maintain the same trend .β − 1) to obtain the geometric means. The same method  was used to obtain the value of the intercept and the slope in the case of regressions.A back‐transformation was also applied to the estimates of the coefficients of the linear model applied to the log‐transformed data. For categorical data, we first obtained the estimate of the “transformed” mean for each factor by calculating the sum of each factor (separately) and the “transformed” estimate of the intercept. Then, each “transformed” coefficient (β) was back‐transformed by exponentiating it and subtracting 1 . We followed this procedure because the log link was used in the GLM, which produces coefficients that are multiplicative in nature, as the coefficients provide a proportion relative to the intercept mean. In the case of regressions, the exponentiated coefficient for the regression factor shows the proportion change with each increment of the explanatory variable. Thus, we obtained the value of the slope, which was necessary for comparison with the other two models, by subtracting one from the value of the proportion change .The values of the coefficients for the GLM were easily obtained and are known to be accurate  has steadily increased over the past 25 years Figure . The incp‐values (at α = 0.05) were usually consistent among models , although GLMs can be prone to high type I error rates if misspecified ). Nowhere in the literature did we find a clear preference for using 10β − 1 as opposed to 10β − 1 to back‐transform. The lack of a clearly stated procedure for back‐transformation of estimates adds an additional level of uncertainty when comparing results from different studies. For the analyses presented here, coefficients were back‐transformed that seemed most logical based on the overall recommendations found through a thorough web search and consultation of statistical textbooks. We do not maintain that our approach to back‐transformation is definitive. Other investigators attempting back‐transformation of coefficient estimates might well arrive at a different choice in methods and thus obtain different outcomes, which points to a clear need for a definitive treatment of the problem of accurate back‐transformation of coefficient estimates. The analysis of data on its original scale, either via randomization tests or by use of an appropriate error model, is an established and certain way of yielding unambiguous parameter estimates in the field of quantitative biology. The uninterpretability of transformed data has been repeatedly stated  addresses the trade‐off between control over type I error and interpretability of coefficient estimates. When might type I error be more important? A good example comes for Fisher's 5p‐values that rarely resulted in a change in the statistical decision, and the use of transformations resulted in inconsistent and sometimes large differences in the coefficient estimates. The absence of a consensus or clear procedure regarding the back‐transformation of coefficient estimates is at once a gap in statistical practice and a major argument against the use of transformations. GLM/GLMM methods yield directly interpretable estimates on an additive rather than multiplicative scale, without greatly impacting the control over type I error in our analyses as well as in synthetic data sets with known parameters (Stroup, Although the transformation of data and the use of GLM/GLMM both continue to be recommended in statistical textbooks from 1967 to the present, the occurrence of GLM/GLMM applied to count data in peer‐reviewed articles has shown a clear increase since 2000. Our findings from 12 analyses with unknown parameters extend those of Stroup : Transfo Stroup, . Further Stroup, . Given tNone declared.All data used in this study was obtained from published sources, that is, statistical textbooks by McCullagh and Nelder A. P. St‐Pierre and V. Shikon equally contributed to the literature reviews and statistical analyses, under guidance and supervision of D. C. Schneider. A. P. St‐Pierre oversaw the manuscript preparation and editing. All authors contributed to project design and manuscript preparation. Click here for additional data file.


This work presents an in vivo transmission quality control methodology, using radiochromic film (RCF) coupled to the linear accelerator (linac) accessory holder. This QA methodology compares the dose distribution measured by the film in the linac accessory holder with the dose distribution expected by the treatment planning software. The calculated dose distribution is obtained in the coronal and central plane of a phantom with the same dimensions of the acrylic support used for positioning the film but in a source‐to‐detector distance (SDD) of 100 cm, as a result of transferring the IMRT plan in question with all the fields positioned with the gantry vertically, that is, perpendicular to the phantom. To validate this procedure, first of all a Monte Carlo simulation using PENELOPE code was done to evaluate the differences between the dose distributions measured by the film in a SDD of 56.8 cm and 100 cm. After that, several simple dose distribution tests were evaluated using the proposed methodology, and finally a study using IMRT treatments was done. In the Monte Carlo simulation, the mean percentage of points approved in the gamma function comparing the dose distribution acquired in the two SDDs were 99.92%±0.14%. In the simple dose distribution tests, the mean percentage of points approved in the gamma function were 99.85%±0.26% and the mean percentage differences in the normalization point doses were −1.41%. The transmission methodology was approved in 24 of 25 IMRT test irradiations. Based on these results, it can be concluded that the proposed methodology using RCFs can be applied for in vivo QA in RT treatments.Despite individual quality assurance (QA) being recommended for complex techniques in radiotherapy (RT) treatment, the possibility of errors in dose delivery during therapeutic application has been verified. Therefore, it is fundamentally important to conduct PACS number: 87.55.Qr, 87.55.km, 87.55.N‐ Some of the most commonly used detectors are the two‐dimensional (2D) arrays of detectors and dosimetric films, in association with the ionization chambers.The main tests in the quality assurance (QA) program of radiotherapy (RT) equipment check its mechanical and dosimetric parameters to ensure an adequate treatment delivery. However, in high technology treatments it is also necessary to evaluate the dose distribution of each individual planning, in addition to the absolute doses delivered.Two‐dimensional arrays of detectors are arrays of detectors capable of acquiring a dose map or a dose distribution in two dimensions in only one exposure. These devices are widely used because of its simple handling; however, there are difficulties related to their spatial and angular dependence.Dosimetric films are widely used in clinical dosimetry; its main advantage is the high spatial resolutionin vivo evaluation of 4337 treatments of IMRT and concluded that the individual QA of the patient plan before treatment is not sufficient to ensure the quality of treatment, considering that 17 errors during treatment application were found in this series. Therefore, it is fundamentally important to conduct in vivo QA during treatment.Despite individual QA being recommended for complex techniques in RT treatment, the possibility of errors in dose delivery during therapeutic application has been verified.in vivo evaluation is intended to ascertain if the dose is released at the correct location and with the correct intensity. In teletherapy, this is generally performed by placing a dosimeter on the patient's skin at the beam entrance; for more complex techniques, however, such methodology is subject to some difficulties.The in vivo evaluation is not well established for more complex treatment techniques, several researchers have dedicated themselves to developing QA and in vivo dosimetry methods using an electronic portal imaging device (EPID).in vivo dosimetry is not guaranteed, since this procedure is not yet well established for all devices manufacturers and, also, a specific calibration for dosimetry purposes is necessary.In view of the need for dose assessment at the time of therapy and that the in vivo evaluation.The first independent methodology to review the monitor units (MU) of a treatment plan in a noncomputerized linac was described by Paliwal and colleagues.in vivo dosimetry, demonstrating that it can be achieved by placing an ionization chamber system using a thin monolithic active pixel sensor (MAPS). With the same goal, Amaral and colleaguesin vivo dose verification by assessing RCF segments relative densities.One of the most recent publications in this field presents a multiwire or multistrip transmission ionization chamber. In this methodology, the wires are placed between two polycarbonate windows with a total thickness of 1.4 cm and subjected to a potential difference of 400 V. During irradiation, different lengths and pairs of wires are exposed and the produced ions are collected by an electrometer.in vivo simple dosimetric methodology for evaluation of complex treatment techniques in RT. Thus, the aim of this work is to present a simple methodology of transmission QA using RCF coupled to the linac accessory holder in its treatment head for in vivo verification of complex treatment techniques in RT.Although several studies are developing devices for dosimetric transmission QA, no study has been published so far describing a methodology using RCFs, and also, it is not well established any in vivo and 2D radiation dose distribution of complex RT treatment plans using Gafchromic EBT2 films . The film was positioned on an acrylic support (similar to a tray) with a source‐to‐detector distance (SDD) of 56.8 cm, attached to the linac accessory holder  throughout the delivery of the planning irradiation fields  and a calibration for the expected absorbed dose using the treatment planning system (TPS) was applied to the pixel number values. Finally, a gamma analysis  was conducted to compare the radiation dose distribution being measured to that one calculated with the XiO TPS . The calculated dose distribution is obtained in the coronal and central plane of a phantom with dimensions of  phantom .The transmission QA was considered approved when it was obtained simultaneously a dose difference in the normalization point of less than 5% and a percentage of points approved in the gamma test exceeding 95%.30cm×30cm×1cm and has a socket in its center with dimensions of 20cm×15cm×0.5cm for film placement. It is covered by an acrylic plate with similar dimensions and both are secured by two screws to prevent them from falling when the gantry is tilted (The acrylic support used has dimensions of s tilted . The supSDD=56.8 cm) to the TPS calculated absorbed doses (SDD=100 cm).To allow the comparison of the dose distribution measured with film to the dose distribution expected by the TPS a calibration curve is necessary. This calibration methodology is one of the main points of the proposed methodology, since it allows the conversion of the film pixel values measured when irradiating the film at the accessory holder (SDD=56.8 cm) with 50, 100, 200, 400, and 600 monitor units (MUs) and using a field size of 10 cm×10 cm. The films were scanned 24 hrs after irradiation, at a resolution of 75 dpi and 12 bits. The obtained pixel value results were associated with the respective absorbed doses calculated by the TPS in the center of the phantom, with dimensions similar to the acrylic support at a SDD of 100 cm and by delivering the same MU used for film irradiation. The calibration was applied grouping the number pixel values of the scanned film, and the dose values obtained through the TPS with the same MU that were irradiated onto the film  and the calculated dose distribution obtained with the TPS (SDD=100 cm) were done to prove the methodology. The first set of tested configurations was composed of square fields, the second was an irregular field, and the third was a five‐fields merging of a conformal prostate cancer treatment. Finally, the methodology was evaluated using a more complex treatment technique, an IMRT treatment irradiation.To validate the proposed transmission methodology, a Monte Carlo simulation was used to verify the difference between the dose distribution generated at a SDD of 56.8 cm (the source distance where the film was positioned during measurement) and 100 cm . Then, several dose distribution comparisons for controlled configurations using the measured dose distribution obtained with the RCF in the accessory holder (SSD=56.8 cm) to the expected dose distribution calculated by the TPS (SDD=100 cm) would be different due to the beam differences and not due to any mistake during the application of the treatment, that is the main objective of the proposed methodology. In order to reproduce the experiment, the ONCOR linac treatment head was simulated and the photon beam spectra of the 6 MV beam for the different field sizes was achieved and analyzed.To evaluate the feasibility of the transmission QA technique proposed, a Monte Carlo simulation was done using PENELOPE code (Penetration and Energy Loss of Electrons and Positron), version 200819.5 cm×5 cm,10 cm×10 cm, and 15 cm×15 cm and 1.109 stories. These simulations were performed in a water phantom with dimensions of 40cm×40cm×40cm at a distance of 100 cm from the source, and the simulated percentage depth doses (PDD) were compared with PDD measured with a CC13 ionization chamber (IBA Dosimetry) in the 6 MV beam of the ONCOR linac, in the same configuration.To verify if the generated spectrum agreed with the linac used in this work, three simulations were done using field sizes of 1.109 stories were performed to evaluate the dose deposition in the two SDDs mentioned (100 cm and 56.8 cm) and to generate their respective dose distribution in the coronal plane of the acrylic phantom with 1 cm thick used in the methodology. A gamma function was carried out to compare the dose distribution generated at SDD of 56.8 cm in the acrylic support that holds the film with the dose distribution generated at SDD=100 cm, the position of the acrylic phantom used in the TPS. It used the maximum dose percentage variation of 3%, maximum distance variation of 3 mm, and threshold of 10%. To implement the gamma function, the dose distribution obtained with SDD=56.8 cm was magnified to the size of the dose distribution obtained with SDD=100 cm and, after that, a manual coregistration based on the agreement of both dose distributions in two perpendicular planes was done. This process was performed in an in‐house software developed using MATLAB . Furthermore, a Gaussian convolution was also applied to the dose distribution to reduce noise in the data. Also, a linear interpolation was done to quadruple the dose distribution points, improving the dose distribution coregistration and increasing the amount of data for the evaluation. This quadruplication reduced the distance between the points in the dose distribution from 2 mm to 0.5 mm.Then, new simulations with SDD=100 cm), several controlled irradiation configurations were tested. The first set of configurations was composed of square fields; three films were irradiated with 5 cm×5 cm,10 cm×10 cm and 15 cm×15 cm square fields. The films were irradiated using 200 MU and the scanned dose distributions were compared to the TPS‐calculated dose distribution. These films were magnified using ImageJ software  to achieve the same resolution of the calculated dose distribution, allowing a comparison using the gamma function. The gamma function was performed in the OmniPro I'mRT software (IBA Dosimetry) with the following criteria: 3% of maximum dose variation, 3% of distance maximum variation, and threshold of 20%.In order to evaluate the difference between irradiated films in the proposed configuration and the dose distribution generated by TPS , taking into consideration the attenuation by the acrylic support. For the film positioned over MatriXX, a calibration based on known absorbed dose values was also conducted.The proposed QA was compared to the QA formed by two conventional dosimetry systems: the MatriXX with solid water plates to provide sufficient backscattering, and the RCF positioned over the MatriXX and below the solid water plates. These QA comparisons were performed using the five IMRT plans of the fourth set of controlled configurations. With each irradiation, the three dosimeters were irradiated together, all at 0° field angle. This was done to avoid influences of the linac performance in our comparisons. For the conventional QA, the gamma analysis were obtained through OmniPRO software  does not indicate that the proposed methodology is flawed. The difference found can be attributed to a small fluctuation in the linac response at the time of irradiation and just emphasizes the need of an in vivo the dose distribution delivered by the linac, subsequent to conventional QA — that is, it is assumed that the treatment plan being assessed has already passed the individual planning QA and thus it must pass the in vivo QA. This way, in case the test does not pass with the proposed methodology, the user cannot cancel out the plan immediately, but on the contrary, it must be reassessed.The purpose of the QA methodology proposed in this work is to verify The methodology used to scan the film proved to be reproducible for two scans on the same film and also the QA reproducibility was achieved in the analyses with two exposures for the same planning. For the two tests, the fluctuations revealed are considered statistical fluctuations.The comparisons of the results obtained with the proposed methodology and with the QA conducted using other dosimeters already established for this application were also satisfactory, which validates the proposed methodology. Only the standard deviation of 2.95% found between the QA performed with the MatriXX and that suggested by our work is noteworthy; however, such difference can be explained by the MatriXX low spatial resolution and large detector dimensions.(24) In the proposed methodology, it is also possible to refine the procedure by designing a support with lower attenuation.This QA methodology using RCF on the accessory holder at the radiation beam output must be applied by observing that the acrylic support used. In this study, it absorbs 5.8% of the dose, which requires a correction in the exposition to be applied. However, this factor does not limit the use of this technique because the dose being applied can be corrected. Furthermore, such attenuation is similar to that provided by PTW's DAVID,During all the irradiations done in this work, an acrylic support with holes in the place of the contact with the interlock sensors was used; this way the linac didn't recognize its presence.However, for safety reasons, when using it for patient verification, the staff must consider using the support as a tray and account for its absorption factor.One limitation of this QA technique in IMRT is that it does not assess the patient's position. Therefore, this methodology must be associated with other control modalities, such as portal film or IGRT techniques, to determine the position.in vivo verification methodology that uses low‐cost commercial dosimeters usually available in radiation therapy departments. Considering that this methodology does not present any dependence with the gantry angle, it can be applied to the most modern RT techniques, such as volumetric‐modulated arc therapy (V‐MAT) using rotational beams. The methodology using the EBT2 RCF attached to the gantry linac accessory holder is effective for in vivo QA in IMRT.This work is important for enabling an in vivo QA methodology using a RCF attached to the linac accessory holder in RT applications is efficient for in vivo verification of IMRT treatments. Moreover, this methodology does not present any dependence with the gantry angle, and can be applied to the most modern RT techniques, such as volumetric‐modulated arc therapy (V‐MAT) using rotational beams.In this study, we proposed the creation of a simple and low‐cost methodology for transmission dosimetry using RCF dosimetry. By the exhaustive set of controlled irradiations tests, it can be concluded that the


Oral mucosal delivery of drugs promotes rapid absorption and high bioavailability, with a subsequent immediate onset of pharmacological effect. However, many oral mucosal deliveries are compromised by the possibility of the patient swallowing the active substance before it has been released and absorbed locally into the systemic circulation. The aim of this research was to introduce a new glimepiride formula for sublingual administration and rapid drug absorption that can be used in an emergency. The new sublingual formulation was prepared after five trials to prepare the suitable formulation. Two accepted formulations of the new sublingual product were prepared, but one of them with disintegration time of 1.45 min and searching for preferred formulation, the binder, is changed with Flulac and starch slurry to prepare formula with disintegration time of 21 seconds that supports the aim of research to be used in an emergency. The five formulations were done, after adjusting to the binder as Flulac and aerosil with disintegration time of 21 seconds and accepted hardness as well as the weight variation. The assay of a new product (subglimepiride) is 103% which is a promising result, confirming that the formula succeeded. The new product (subglimepiride) is accepted in most quality control tests and it is ready for marketing.  It binds to 65 kD protein on β-cells, which appears to be a part of the same sulphonyl urea receptor that binds Glibenclamide. Glimepiride after oral administration lowers blood glucose 3.5 times more potently than Glibenclamide. Glimepiride is classified under class II according to biopharmaceutical classification system ∗100Friability = [. SPSS version 12 was used for statistical analysis. A In formula 1 (F1), the tablets were very friable and cannot be compressed because the hardness was weak due to the presence of high amount of croscarmellose as disintegrant agent and, therefore, the binder would increase in formula 2. Formula 2 (F2) showed disintegration time of about 1.45 min, but while searching for a preferred formula with fast disintegration, low croscarmellose sodium was used as disintegrant agent and therefore add super disintegrant, flavoring agent, and sweetening agent and change the diluent in formula 3. Formula 3 (F3) showed the high friability of tablet due to the fact that the binder is not suitable and, therefore, add new binder in formula 4. In formula 4 (F4), the hardness is strong due to the fact that the binder is high and not suitable and therefore change the formula. Formula 5 showed the best result as shown in The new sublingual formula showed good disintegration with 21 seconds which is more preferred than formula 2, as the assay gives good result compared to Amaryl as the standard drug as well as the hardness and friability.The five formulations were done and after adjusting to the binder as Flulac and aerosil with disintegration time of 21 seconds and accepted hardness as well as the weight variation. The assay of new sublingual glimepiride is 103% which is a promising result and confirms that the formula succeeded and is accepted in most quality control tests and it is ready for marketing. The sublingual glimepiride has fast dissolving time that would be more targeted in emergency DM.


Clinician’s Awareness Towards Cognitive Errors (CATChES) in clinical decision making.Despite their importance on diagnostic accuracy, there is a paucity of literature on questionnaire tools to assess clinicians’ awareness toward cognitive errors. A validation study was conducted to develop a questionnaire tool to evaluate the This questionnaire is divided into two parts. Part A is to evaluate the clinicians’ awareness towards cognitive errors in clinical decision making while Part B is to evaluate their perception towards specific cognitive errors. Content validation for both parts was first determined followed by construct validation for Part A. Construct validation for Part B was not determined as the responses were set in a dichotomous format.For content validation, all items in both Part A and Part B were rated as “excellent” in terms of their relevance in clinical settings. For construct validation using exploratory factor analysis (EFA) for Part A, a two-factor model with total variance extraction of 60% was determined. Two items were deleted. Then, the EFA was repeated showing that all factor loadings are above the cut-off value of >0.5. The Cronbach’s alpha for both factors are above 0.6.The CATChES questionnaire tool is a valid questionnaire tool aimed to evaluate the awareness among clinicians toward cognitive errors in clinical decision making. According to the Institute of Medicine’s report titled “Improving Diagnosis in Health Care 2015)”, diagnostic error is defined as “the failure to (a) establish an accurate and timely explanation of the patient’s health problem(s) or (b) communicate that explanation to the patient” 5”, diagn, 4. CognCampbell et al.  have claIn a survey by MacDonald et al.  involvinNonetheless, as important as these cognitive errors are, it is not known how many clinicians are aware of this. As pointed out by Prochaska et al.  in theirOn the other hand, a person who is unaware of the problem sees no reason to take any action to change. This prior stage is known as the pre-contemplation stage . A tool Clinician’s Awareness Towards Cognitive Errors (CATChES) in clinical decision making. The purpose of this tool is to help create the awareness among clinicians who are in the pre-contemplation stage with the hope of moving them from this stage to the stage of contemplation in the Transtheoretical Model of Change. This tool can also be used as a pre-intervention material to supplement educational resources in teaching cognitive errors in clinical medicine .For content validation, based on the recommendation by Lynn , ten expFor construct validation, emergency physicians and emergency residents with a minimum of four years’ working experience in Hospital Universiti Sains Malaysia were identified as the participants. Using the rule of thumb of a minimum of five participants per item, a minimum of 30 participants were needed. Clinicians who were not residents pursuing a postgraduate degree in emergency medicine or clinicians with less than four years of working experience in the emergency department were excluded. The authors invited 35 of these emergency residents to participate in the construct validation and 31 of them responded. All nine emergency physicians who participated in the content validation also participated in this construct validation process. Hence, a total of 40 participants were recruited in this construct validation process.The questionnaire tool in this study is divided into two parts. The first part of the questionnaire (Part A) aimed to evaluate the awareness of clinicians towards cognitive errors in clinical decision making while the second part (Part B) aimed to evaluate the clinician’s perception towards specific categories of cognitive errors in clinical setting (Part B).A preliminary version of the questionnaire was first developed by two authors (KS and AH) and checked by the third author (YC). For the development of Part A of this questionnaire, the Transtheoretical Model of Change  was usedThis was a cross-sectional study conducted among clinicians  from Hospital Universiti Sains Malaysia (HUSM). Convenience sampling was applied in recruiting the participants. Human Research Ethics approval was obtained from The Human Research Ethics Committee of Universiti Sains Malaysia before the study was commenced.The content validity of the questionnaire (both Part A and Part B) was first determined by a panel of experts consisting of the emergency physicians in HUSM. These experts were briefed by one of the authors (AH) on how to respond to the relevance of the items, ranked in a Likert scale of four, ranging from “1 = not relevant at all” to “4 = highly relevant”. The experts were told to respond anonymously and that they were free to withdraw from the study at any time. The response sheets were passed to the experts to respond on their own and were collected back by author (AH) the following day. The document on the glossaries of terms were handed out and read out to the participants prior to starting the questionnaire.After the content validation process, the construct validation of the questionnaire was determined. For the construct validation of Part A, participants were first briefed on how to respond to the items ranked in a Likert scale of five, ranging from “1 = strongly disagree” to “5 = strongly agree”. Participants were told to respond anonymously and that they were free to opt out at any time. A separate document on the glossaries of terms were handed out and read to the participants prior to starting the questionnaire. All participants responded individually in one sitting.Since the purpose of this Part B is to identify the clinician’s perception towards the specific categories of cognitive errors in clinical setting, it was set in a dichotomous format  and not in an ordinal format. As such, construct validation for this part was not determined. The sequence of content and construct validation is illustrated in Fig. Exploratory factor analysis (EFA) was used to determine the construct validity of Part A of the questionnaire. Principal axis factoring was chosen as the extraction method. The initial run of the factor analysis was performed to determine the number of items to be extracted. An eigenvalue of more than 1 was chosen as the cut-off value to determine whether the numbers of factors to be fixed. Scree plotting was also performed to further verify the number of factors for extraction. Repeated runs of the factor analysis were then performed to determine the factor loadings of the items as well as to identify problematic items that may need to be removed. A cut-off point of 0.5 was used as the criteria in factor loading to determine whether an item is to be removed or not . WhereasTo evaluate the content validity of item relevance, the content validity index (CVI) and the modified kappa (κ) were used. The item relevance CVI (I-CVI) for relevance is defined as the proportion of the judges who rate the item with scores of 3 or 4 on a four-point Likert scale  . CVI valWith regards to the content validity, the CVI values for all items were rated highly as valid in terms of their relevance in clinical settings. In terms of the values of their modified kappa (κ), all items were rated as “excellent” in terms of the validity of their relevance in clinical settings. The results of CVI for Part A and B are given in Tables p < 0.05). This shows that there are correlations among the items based on the correlation matrix. Initial eigenvalue indicates that the first two factors  explain 60% of the total variance (42 and 18% respectively). Furthermore, 2 factors were shown to be above the point of inflexion of eigenvalue on the scree plot  was recognized as problematic with factor loadings of only 0.14 and 0.20 in both factors and its communality value (extraction) of 0.084 only. Item no. 4  was also identified as problematic with factor loading of 0.481 in Factor 2 and a communality (extraction) value of 0.145.After 2 rounds of test re-run, two items out of the six were removed as they did not meet the minimum cut-off points of factor loading >0.5, and communality values of >0.25. In particular, item no. 3  and item no. 2  load on Factor 2 whereas item no. 5  and item no. 6  load on Factor 1. Hence, we labeled factor 1 as the “educational interventions to reduce the risk of cognitive errors” whereas Factor 2 is labeled as the “impact of cognitive errors in clinical decision making”.After removal of the two items, the re-run of the principal axis analysis of the remaining 4 items shows that they explain 75% of the variance with two factors extracted. All items in this analysis had factor loadings of >0.5 and communalities (extraction) of >0.25. The pattern matrix of the factor loading is presented in Table Both factors in Part A yield a Cronbach’s alpha of 0.676 and 0.635 respectively and no further improvement in the Cronbach’s alpha values could be achieved by deleting any of the items. Cronbach’s alpha for Part B is 0.657. Similarly, no further improvement in Cronbach’s alpha value could be achieved by deleting any of the items in this part. In the finalized version of the CATChES questionnaire , the phrase ‘something, rather than nothing’ is rather ambiguous and this may have resulted in its rejection by the participants as a valid item. Re-phrasing it with a more direct sentence may bring greater clarity. For example, it could be rephrased, as ‘Specific de-biasing strategies are effective in minimizing the risk of committing cognitive biases.Furthermore, from the EFA, it is also shown that there are two items that had to be removed. For item no. 4 , its rejection could be due to the fact that the statement is overly generalized, particularly in an Asian culture. Authority gradient is defined as the gradient that may exist between two individuals’ professional status, experience, or expertise that contributes to gap in exchanging information or communicating concerns [For item no. 3 concerns . In our In terms of the internal consistency analysis of Part A, a moderate degree of internal consistency measured by both Cronbach’s alpha values of more than 0.6 in both factors was noted. The internal consistency could be improved by adding more items within the factors. Therefore, future research should consider including more items that are relevant to Factor 1  and Factor 2  or items to generate more factors to move up to the next of stage of “taking actions” along the ladder of Transtheoretical Model of Change .There are a number of limitations in this validation study. First, for Part A, confirmatory factor analysis (CFA) was not performed on another set of samples to confirm the constructs developed based on the EFA result. Second, face validity was not performed to determine its comprehensibility and readability. For example, as mentioned, the phrase ‘something, rather than nothing’ in item no. 4 is rather vague. Third, more items should be included to improve the internal consistency of the constructs. The future development of this project would include rewording and rephrasing the items as well as adding more relevant items based on Transtheoretical Model of Change . More saDespite its limitations, the construct and content validation suggest that the CATChES questionnaire tool is useful in evaluating the awareness among clinicians toward cognitive errors in clinical decision making. Such awareness may in turn, motivate them to take measures to minimize risk of committing these errors.


IntroductionStudent evaluation of teaching (SET) has been in use in some parts of the world for almost a century now. Though India has the highest number of dental colleges in the world, very few colleges employ SET as a tool for improving teaching. The present study was designed to investigate the attitudes of the faculty and students of a dental institute in India, and the differences, if any, that exist between the two major stakeholders.Materials and methodsTwo validated questionnaires for faculty and students about the various aspects of SET were given to consenting participants and the results of the same were statistically analyzed. ResultsForty-six faculty and 198 students participated in the study. The average age of the students was 21 years while that of the faculty was 37 years. The majority of the faculty thought of SET as a useful educational tool and were open to their teaching being evaluated, though they were divided about SET being used for appraisals. Most students wanted SET to be implemented in their institute and thought that it will improve the teaching being rendered to them.DiscussionOn most aspects, like the when, how often, its mode of administration, and the format of SET, there was an agreement amongst the students and faculty. They differed significantly on the visibility of SET results, where most faculty felt that the results of SET should only be known to the faculty. This can be attributed to apprehensions among the faculty about SET.ConclusionThe present study concludes that SET is perceived as a useful tool by the students and faculty of the studied institution.  Student evaluation of teaching (SET) has been used as an accountability tool in higher educational institutes from as long back as 1920 in some North American universities . It has Unfortunately, in India, to date, few dental colleges and universities implement SET as a routine practice, in spite of its proven benefits. This contrasts the situation in the US, where almost 81% of dental schools use it as a routine practice . This isThe present study was designed to investigate the perceptions of the students and faculty of a dental college in Mumbai, India, on student evaluation of teaching and its various aspects.The study was approved by the institutional ethics committee. The minimum sample size for the study to be valid was calculated, keeping the total strength of the faculty and student body as the entire population, with a confidence interval of 95% and a margin of error of 5%. The minimum sample size thus calculated was 184 for students and 45 for faculty.Two questionnaires were designed, one for the faculty and the other for students; these questionnaires were content and face validated by an expert in the field of medical education, who checked whether they were in line with the objectives of the study. The questionnaires were first piloted among four faculty members and 10 students. The results of the pilot were not included in the final sample. The questionnaires can be found in the appendices. All full-time faculty members and students (both undergraduate and postgraduates), ie., the entire population of the institute, were invited to fill the questionnaire. Those who consented to participate were given a copy of the questionnaire or the web link to the same after signing an informed consent form. A total of 198 students and 46 faculty members returned the filled questionnaires.  The faculty questionnaire had 14 items and was divided into three parts. The first part had three questions and inquired about the age, gender, and teaching experience of the respondent. The second part had five questions about their perceptions on SET, and if it should be used for appraisals and promotions. Finally, the third part had six questions that were common to the faculty and student questionnaires, which inquired about how often SET should take place, who should participate in it, what should be the format, how it should be administered, who should have access to the results, and if it should be mandatory for students to participate.The student questionnaire had 11 items and was also divided into three parts. The first part consisted of three items inquiring about the age, gender, and year of study of the respondent. The second part consisted of two items inquiring about the student’s opinion about SET being implemented in their institute and the reasons for the same if the answer was ‘yes’ to the previous question. Third part consisted of the same six questions as in the faculty questionnaire.The paper and pencil responses were entered into Google forms , and the results were downloaded as an Excel file , which were imported to  SPSS vrs21 . Descriptive statistics were drawn to throw light on the respondents' characteristics. Mean, standard deviation, and ranges were calculated for the last six questions from both the faculty and student questionnaires about the various attributes of SET. Chi-square test was used to find the differences in the responses of students and faculty.Forty-six faculty and 198 students returned the filled questionnaires. The faculty population consisted of 41.3% females and 58.7% males, while the student population consisted of 74.7% females and 25.3% males.The average age of the faculty was 37 years while the average student age was 21 years. The average teaching experience of the faculty was 9.5 years.Of the faculty participants, 87% were open to the teaching they provided being evaluated by the students, while 78.3% of the faculty thought that students would like to evaluate the teaching rendered to them. Most faculty (89.1%) were of the opinion that SET will be a useful tool to improve education, and 89% of the faculty were willing to make changes in their teaching methodology based on the feedback received.The question about linking appraisals and promotions to students feedback met with a variable and divided response as shown in Table Most students (92.9%) wanted SET to be implemented in their institute. Students wanted SET to be implemented for one primary reason, i.e., they felt that the faculty will become aware of what students feel about the quality of education rendered to them and this, in turn, will bring about a change in the same (38.4%) thus improving the quality of teaching.It was also observed that as the students progressed from the first year to part three of MDS , there was a change in why they thought SET should be introduced. Significantly, more MDS part three students responded with “I feel empowered by filling SET” as compared to the first year, where the predominant response was “Faculty becomes aware of the way students feel about the quality of their teaching, which can bring about a change in how the course will be taught by them." This difference was statistically significant (p=0.0012).The gender distribution and the results of the six questions about the format, frequency, participation, and method of conducting SET were similar among students and faculty Table .The present study was aimed at exploring the attitudes of students and faculty at a dental institute where evaluation of teaching is not in practice.From the results of the present study, it can be inferred that both the faculty and the students have an overall positive attitude towards implementing SET at the institute. Most faculty (89.1%) responded affirmatively about making changes in their teaching methodology based on SET feedback. Most students also felt that the faculty will make changes in their teaching methodology, thus making the course better.When asked about how frequently SET should take place, there was a difference of opinion between the faculty and students. The faculty were almost equally divided between all four options from “after every lab or lecture” (23.9%) to “term end” (28.3%). In contrast, students were majorly divided between “monthly” (33.8%) and “fixed interval” (40.9%). There was a consensus among students and faculty about the prefered format for SET. Most faculty and students were of the opinion that either an open-ended SET questionnaire or a combination of open and closed-ended questions should be used. This definitely demonstrates a positive view, as it has been shown by a previous study that neither a closed-ended SET method nor a simple scoring scale has a high value when it comes to interpreting the results of SET and making changes accordingly .  On the question of who should fill SET, most faculty (63%) and students (83.8%) felt that the entire class should fill it, though there was a statistically significant difference between the two, with students more strongly feeling that the entire class should engage in the process. This difference can be attributed to the fact that the faculty may perceive the process of SET to be time-consuming, and may thus want the evaluation to be filled by a fixed percentage of the class.Questions regarding the way SET should be administered met with similar responses from the students and faculty, with the majority of both groups indicating a preference towards online SET administration, though students felt more strongly than the faculty about this. This can probably be attributed to the comfort, convenience, and flexibility that online administration provides to the user, and to which the current generation of students are accustomed. Online administration had the added advantage of saving valuable class time.Most students (64.6%) and faculty (58.7%) wanted SET to be made mandatory for students. This again reflects the positive attitude of stakeholders towards SET.There was an interesting contrast in students' and faculty members' responses when they were asked who should know the results of SET. About 70% of the faculty felt that the results should be known only to the faculty, while around 70% of the students felt that it should be known to both the students and faculty. Less than 15% in both the groups felt that the results should be displayed for all to see. This stark contrast between the perceptions of the faculty and students can be attributed to the fact that since the faculty have never been evaluated before, they may have apprehensions that a negative outcome on SET may tarnish their image as a teacher. This can also possibly be because many faculty members perceive SET to be a personal evaluation of them by students, and not of their teaching. This attitude will probably change once SET becomes a routine part of the teaching curriculum, and the faculty understand that SET is a tool for improving one’s teaching and is not a judgment of one as an individual. The difference in the perceptions can be appreciated in Figure The question about linking appraisals and promotions to SET provoked a divided response amongst the faculty Table , which pThe overall results of the study indicate that faculty and students regard SET positively, and both stakeholders perceive it as a positive tool for improving the teaching and learning process.


Festuca rubra. Individuals from four natural populations representing two levels of temperature and two levels of precipitation were cultivated in four growth chambers that simulate the temperature and precipitation of origin of the populations . Each population was represented in each growth chamber. After 6 months, single young ramets of these plants were reshuffled among the growth chambers and let to grow for additional 2 months (offspring phase). The results show that transgenerational effects  significantly modify species response to novel climates, and the direction and intensity of the response depend on the climate of origin of the plants. For traits related to recourse acquisition, the conditions of maternal phase, either alone or in interaction mainly with climate of origin, had stronger effect than the conditions of cultivation. Overall, the maternal climate interacted more intensively with the climate of origin than with the offspring climate. The direction of the effect of the maternal climate was of different directions and intensities depending on plant origin and trait studied. The data demonstrated strong significant effects of conditions during maternal phase on species response to novel climates. These transgenerational affects were, however, not adaptive. Still, transgenerational plasticity may be an important driver of species response to novel conditions across clonal generations. These effects thus need to be carefully considered in future studies exploring species response to novel climates. This will also have strong effects on species performance under increasingly variable climates expected to occur with the climate change.In spite of the increasing number of studies on the importance of transgenerational plasticity for species response to novel environments, its effects on species ability to respond to climate change are still largely unexplored. We study the importance of transgenerational plasticity for response of a clonal species  The variance explained by the maternal environment will be lower than the variance explained by cultivating conditions in highly plastic traits such as plant size. In contrast, in traits previously showing low plasticity  confirmed that these clones were genetically differentiated from each other, thus representing true independent genotypes. We use the term genotype throughout the subsequent text. These genotypes were cultivated for 5 months in the experimental garden of the Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic  prior to the experiment. Further, they were grown for two more months in a greenhouse heated to ensure that the temperature never drops below 10°C .Festuca plant, which was intermixed among the experimental plants and was of the same size as the experimental plants, but was not a part of the experiment. For all the regimes, the same day length and radiation were used, that is, 16 hr of full light (6 a.m.–10 p.m.) and 4 hr of full dark with a gradual change of light availability in the transition between the light and dark periods over 2 hr. Over the full light period, the radiation was 360 μmol m−2 s−1, red radiation  of 26 μmol m−2 s−1, and far‐red radiation  of 15 μmol m−2 s−1, R/FR = 1.73 .Four ramets (single‐plant tillers able of independent existence) of each of the six genotypes from each population have been individually planted into four growth chambers. The plants were grown in the growth chambers for a purpose of another experiment from mid‐March to end of August 2015 . To account for the variation in biomass between the selected ramets, we recorded height of each planted ramet and used this height as a covariate in the subsequent tests. The roots of the ramets as well as the aboveground part of the ramets were then shortened to ensure that all the ramets have similar belowground as well as aboveground systems of 3 cm in length. Three pots containing ramets of each genotype and each C1 growth chamber were placed into each of the new four growth chambers, leading to 288 pots in each new growth chamber in total . The plants were let to grow in the growth chambers for 63 days. The conditions in the growth chamber corresponded to the conditions during the peak vegetation season, that is, the last temperature setting in the C1 generation, and were retained over the whole period. This second phase of cultivation represents the offspring generation and is further referred to as C2. At the end of the experiment, we recorded number of all ramets and measured length of the longest ramet (hereafter referred to as plant height). We also distinguished between intravaginal and extravaginal ramets and estimated the proportion of extravaginal ramets. Intravaginal ramets are those that develop within the subtending leaf sheath, resulting into minimal interramet distance. In contrast, the development of extravaginal ramet proceeds laterally through the subtending leaf sheath contributing to a greater interramet distance within a clone , target conditions in the maternal generation (C1), target conditions in the offspring generation (C2), and all their interactions on performance of the plants in C2. We used initial plant size  as a covariate in preliminary tests. As it did not have any effects on plant performance due to its very small variation, it was discarded from the final tests. In all cases, the conditions of origin, C1 and C2, were coded separately by their temperature, precipitation, and their interaction. For visualization of the results, we, however, merged the effects of origin, C1 and C2, without distinguishing the species factors. All the tests were conducted using linear or generalized linear mixed‐effect models with plant genotype as a random factor using the package LME4 in R 3.2.1  and offspring generation (C2 conditions), we will conclude that transgenerational plasticity is adaptive.t test. While these t tests have a high chance of type I, they are only meant to help in interpreting the figures. The proper tests of the data are provided in Table To visualize the results, we calculated mean value of each plant characteristic across all individuals grown within each C2 growth chamber and subtracted the value from values of all individuals grown in that C2 growth chamber. In that way, we obtained deviations of each individual from mean performance of individuals in that C2 growth chamber. Thanks to this, we could easily compare plant performance across different origins and C1 cultivating conditions, without the necessity to visualize the effects of C2 conditions. While the effects of C2 are indeed also interesting and represent plastic responses of the species, they have already been studied in our previous study , we thus retained only one. Thanks to this, we excluded rhizome weight and belowground biomass from further analyses. All the above described tests were thus conducted for the following dependent variables: plant height, number of ramets, proportion of extravaginal ramets, total aboveground biomass, ratio between belowground and aboveground biomass.Some of the dependent variables were closely correlated with each other Table . From paTo explore differences in the importance of the transgenerational plasticity in more detail, we tested the effects of C1 and C2 conditions in each population separately. We used these analyses to visualize the proportion of variance explained by C1 and C2 in each population.p level from 0.05 to 0.01  accounted for more than 50% of the explained deviance in proportion of extravaginal ramets of the plants in C2 Figure .Specifically, plants experiencing low temperature in C1 had significantly higher values of all the size measures in C2 Table . In addip > .05 in all cases).Plant performance in C2 was also affected by interaction of the conditions in C1 and original conditions in the field Table . The effComparison of the importance of transgenerational plasticity across populations demonstrated that transgenerational plasticity was least important in population from warm‐dry site. For ramet number, it was highly important in plant from cold sites but not in plant from warm sites Figure .4The results of this study confirmed that transgenerational plasticity may be an important factor affecting species response to changing climate and may strongly interact with conditions of cultivation as well as with conditions of origin. The results also showed that such a transmission of effects is important also across clonal generations. For foraging‐related traits , the variance explained by transgenerational effects and its interactions with target (C2) and origin were higher than the variance explained only by target (C2) and original conditions. This suggests that transgenerational effects may be the key factors driving performance of species of different origins in novel climates at least when it comes to resource acquisition by the plant.Significant transgenerational effects detected in this study are in line with general expectation that such effects may be important for species performance in general (e.g., Guillaume et al., The current result may also be linked to studies dealing with species acclimation ability. Acclimation is defined as facultative phenotypic response within juvenile or adult organisms that result in shift of reaction norms in response to environmental variation that occurs over a period of several days or longer. Phenotypic changes resulting from acclimation are reversible and repeatable in the lifetime of individuals (Beaman, White, & Seebacher, In terms of species response to climate change, the results of this study suggest that short‐term exposure to novel climate will modify future species response to these conditions. However, the results did not confirm our expectation that plants exposed to certain conditions for half a year will subsequently perform better in those same conditions than in other conditions, that is, that transgenerational plasticity will be adaptive. This was evident from the result, showing that exposure to the same condition in the maternal and offspring phase did not affect plant performance in a different way than when the maternal and offspring conditions were different. This contrasts with a study showing that transgenerational plasticity may be adaptive in bryozoans in response to competition (Allen et al., The absence of indication of adaptive transgenerational plasticity may be also linked to the fact that the traits measured in our study were not proper measures of fitness. It was suggested that the various proxy traits measured on plants to describe their performance when assessing their adaptive potential may confuse the conclusions on adaptiveness of various processes in plant life (Marshall & Uller, Important outcome of our study is that for some traits the terms including the transgenerational effects either alone or in interaction with conditions of origin and conditions of cultivation accounted for more variation in the data than the terms accounting for species origin and for cultivating conditions alone. Such an effect was especially strong for proportion of extravaginal ramets. This trait has been previously shown to be strongly affected by environment of origin and showed strong interaction between environment of origin and cultivation in our previous study in the same system (Münzbergová et al. One of our hypotheses was that the transgenerational effects will depend on population origin. Indeed, we found many significant interactions between plant origin and conditions during the maternal environment. In contrast to Lampei et al. , the intA common procedure for experiments in multiple control conditions is to first cultivate the plants in standardized conditions for a certain period to remove the maternal effects (reviewed in Latzel, Understanding importance of transgenerational plasticity in response to climate is crucial as it may have significant effects on species ability to respond to novel climatic conditions likely to occur along with global climate change. It is expected that along with a continuous change in averages of climatic variables, the climate will simultaneously become more variable, extreme, and unpredictable IPCC, . In thisIn addition to responding to novel conditions in situ, species‐facing novel climates may also respond to climate change by migrating to different locations (e.g., Kokko & Lopez‐Sepulcre None declared.ZM and VH conceived the idea and designed methodology; VH and ZM collected the data; ZM analyzed the data; ZM wrote the manuscript. VH contributed critically to the drafts and gave final approval for publication. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises. The maximum entropy model characterizes the correlation structure of a network activity without assumptions about its mechanistic origin and enables predictions of the collective effects2. These maximum entropy models are equivalent to Ising models in statistical physics and, as we show in the following, it allows us to explore critical behavior of the network.Classical inverse statistical mechanics has been applied to determine properties of pairwise interaction potentials from ensemble properties in complex networks5, the main focus has been made on characterization of specific interaction between two elements or community structure of networks. However, global dynamical response of an evolving network based on its inherent symmetries has not been addressed yet. Here we apply percolation theory to measure the strength of interactions in a time-dependent evolving network of financial market and show that away from financial crisis the interaction network is self-similar and exhibits a geometrical criticality at a certain size-independent interaction threshold while during the crisis the network responses differently at different size-scales.Despite wide range application of maximum entropy model in the recent decade6 is the simplest fundamental model in statistical physics that displays phase transitions and explains the behavior of connected clusters in a random graph. The geometric critical behavior is dominated by the emergence of a giant connected component which controls the global response of the network. Resilience of networks under attack8, spreading phenomena and epidemics14 are examples of diverse problems that can be treated using percolation theory.Percolation theory10 was put forward by Erdös-Rényi15 who introduced the simplest imaginable random graph ERn(p) including n vertices in which an edge is placed between any pair of distinct vertices with some fixed probability p. This random graph exhibits a continuous phase transition at a critical threshold pc which leads to a sharp global connectivity of the network components and serves as the mean-field model of percolation.The concept of random graphsn(p) random graph of n interacting stock markets when the control parameter p is taken to be the strength of pairwise interactions.We find that despite seemingly strong correlations in the interaction network of financial market away from a global crisis, it can be modeled, to a good extent, by an ER16.In this paper, we study the critical behavior of a financial network consist of about 400 indices (or vertices) in S&P 500 whose activities are available as time series. We first build up a time-dependent correlation matrix of the stocks from the time-series. Then, we extract the interaction matrix among system’s elements in which the non-direct correlations are eliminated. This interaction matrix is the adjacency matrix of elements’ interaction network. Given the interaction network of a system, we can reduce the full system to some disjoint components which have positive intra-interactions . The collective and large-scale information of the system is somehow encoded in the statistics of the largest component which can also control the dynamics of the system. This collective behavior can also result in large-scale deviations in system states. For example, in financial market all stock indices may fall down and influence global index of the marketn(p) away from a global financial crisis, while around and at the crisis the network departures from criticality. This observation is in contrast with the ordinary critical phenomena in which the large-scale fluctuations play a crucial role in the behavior of systems in the vicinity of the critical state and the fluctuations are actually responsible for the criticality. Despite large fluctuations in stock’s prices over a crisis period  and We analyse the available data for “adjusted closing prices” in S&P 500 index between 2000 and 2017. The time-series t and a time window τ . Due to the finite sample size in our data sets, we used “Graphical LASSO” technique19 to evaluate interaction matrix 19.).Based on the above correlation matrix Eq. , we extrInteraction matrix has an important advantage over the correlation matrix in which all mediated correlations are eliminated in the interaction matrix. Therefore, if a high correlation between indices A and B would be due to their high correlation with an index C, this effect will be eliminated in the interaction matrix.18. It is also related to the maximum entropy network in the inverse statistical physics1. Based on this fact, elements of the interaction matrix are independent of each other and one can remove them during the attack process (percolation model).This concept is related to the partial correlation matrix in multivariate Gaussian noiset, we have an adjacent network θ for the weights on the links to transform the network to an unweighted one θ, and keep other links in the network by setting their weights equal to 121, i.e.,For each interaction matrix Gθ we define the percolation strength 10. To be more comparable with the ERn random networks, we interchange our percolation parameter θ with the corresponding mean degree n graphs, the critical point is known to be 10.Figure s. In Fig. n random networks, while close to the crises, the original network substantially deviates from the shuffled one  of independent realizations and i-th realization. Figure The other quantity of interest is the mean cluster size (or susceptibility) int Fig. . It alsoint Fig. .Figure 410 which states that it is possible to compute the giant component probability To quantify the amount of deviation from the critical behavior near the crisis, let us now measure the difference between the strength of the giant component and its prediction based on the random network theoryNext, we measure the mean absolute difference s in Fig. We have plotted 24. According to this hypothesis, the stock prices fluctuate mostly like uncorrelated random variables. In other words, it states that it is impossible to extract information from the past history of the prices of a stock to predict its future and earn money.Efficiency of financial markets is a hot debate in financial economics. Some studies support the hypothesis of market efficiency–see for example26 and references therein.Despite early observations which supported the hypothesis of efficiency, some later works challenged it and revealed deviations from it. Although it was hard to find correlations in time series of an individual stock, noticeable information could be captured if some other parameters such as cross correlations or earning price ratio were brought into account–see for example15 which similarly exhibits the properties of scale invariance and self-similarity at the critical point of a continuous phase transition. When the financial market approaches a crisis, our observation is that the interaction network model deviates from the critical random network and looses its scale invariance, i.e., the system behaves differently at different size scales. The deviations are summarized in Fig. The studied methods have mostly focused on the individual indices or their cross correlations and the analysis based on an aggregated behavior is still lacking. In the present work, we studied the global behavior of indices as an example of an interaction network by using the concepts of percolation theory. We find that away from financial crises the interaction network behaves like a random network of Erdös and Rényi29. As shown in Fig. During the financial crises, usually because of the spreading fear in the market, the stocks move together and correlation grows amongst them. This fact raises a natural question if our main result is just another derivation of the previous observations concerning the growth of correlation between the indices. In order to address this appropriately, let us compute the largest eigenvalue of the correlation matrixIt should be notified that our observation close to the crises does not contradict the efficient market hypothesis, since it is not still clear if it can help one to extract money. Should we be able to extract money from such structure is left as an open question for the future works.Extraction of real system’s interaction networks is a rapid growing field. Beside the statics features of these networks, they could be used to deduce some dynamic features of the system. In this work, we established a correspondence between the critical phenomena and the external macroscopic state of a system. This approach could however be generalized to other fields where maximum entropy network is used like gene regulatory networks, neural networks, protein interactions and etc.http://finance.yahoo.com.The datasets analysed during the current study are available in the Yahoo Finance, Supplementary Information


In an atmospheric pressure surface barrier discharge the inherent physical separation between the plasma generation region and downstream point of application reduces the flux of reactive chemical species reaching the sample, potentially limiting application efficacy. This contribution explores the impact of manipulating the phase angle of the applied voltage to exert a level of control over the electrohydrodynamic forces generated by the plasma. As these forces produce a convective flow which is the primary mechanism of species transport, the technique facilitates the targeted delivery of reactive species to a downstream point without compromising the underpinning species generation mechanisms. Particle Imaging Velocimetry measurements are used to demonstrate that a phase shift between sinusoidal voltages applied to adjacent electrodes in a surface barrier discharge results in a significant deviation in the direction of the plasma induced gas flow. Using a two-dimensional numerical air plasma model, it is shown that the phase shift impacts the spatial distribution of the deposited charge on the dielectric surface between the adjacent electrodes. The modified surface charge distribution reduces the propagation length of the discharge ignited on the lagging electrode, causing an imbalance in the generated forces and consequently a variation in the direction of the resulting gas flow. The SBD configuration offers numerous advantages over alternative designs due to its unique construction, typically comprising of metallic electrodes adhered to opposing sides of a thin dielectric material. On application of a sufficiently high voltage, plasma forms around the electrode edges and propagates across the dielectric surface. Typical advantages of the configuration include ease of scalability, with such discharges routinely used on an industrial scale, and exceptional energy efficiency8. A drawback of the SBD configuration is that the highly reactive neutral and charged species produced are essentially confined to the active (visible) discharge region, which is located close to the dielectric surface («mm). For many established applications, such as ozone generation, this does not present a problem as it is the long-lived species that are the primary application enablers. Conversely, in many emerging applications such as those in the healthcare sector, it is the short-lived RONS that are primarily responsible for the observed effects; examples include the use of plasma generated NO to stimulate wound healing and the role of O and OH in plasma mediated biofilm decontamination12.Of all the plasma systems currently under investigation to generate and sustain a stable non-thermal discharge under ambient air conditions, the Surface Barrier Discharge (SBD) configuration is one of the most commonly used due to its prevalence in small scale commercial ozone generation devicese.g. living tissues) and limits the potential for cross-contamination of the sample and electrodes. In such a scenario, it is extremely unlikely that charged species or highly reactive neutrals will reach the downstream sample, having a negative impact on application efficacy13. To overcome these challenges, several studies have posited that plasma induced electrohydrodynamic (EHD) forces could be manipulated to induce a convective gas flow through the active discharge region, thus transporting the species generated downstream and enhancing mass-transport14. Indeed, the previous computational studies of Hasan et al. have demonstrated that such convective flows could enable the transport of relatively short-lived species, such as OH and NO, to considerable distances downstream of the active discharge region13. Furthermore, it has been demonstrated that the introduction of a convective flow impacts the generation and loss rates of species in the downstream gas region, resulting in enhanced production of key RONS13.In healthcare related applications of the SBD, a spatial separation of » 1 mm is commonly employed between the active plasma region and the sample to be treated; this removes the possibility that intense plasma filaments could interact directly with a delicate substrate  was used to quantify the resulting gas flow velocity from the arrangement shown in Fig. d = 5 mm). The spatial separation between the electrodes was found to be a critical parameter influencing the extent to which the voltage phase difference caused a shift in the direction of the generated gas flow. Figure d). From the presented data, it is clear that an increased electrode separation distance yields a less pronounced variation in the angle of the induced flow. At large electrode separations, considered to be d => 20 mm in this investigation, the generated flow shows no dependence on the voltage phase difference.The results presented in Fig. From the results presented in Figs 17. As the fluid flow is known to develop on a millisecond timescale in a dielectric barrier discharge it is surprising that such small time delays have a significant impact on the direction of the fluid flow.While the results presented in Figs Given that the change in flow direction is a function of the spatial separation between the adjacent electrodes, it is reasonable to assume that the phenomenon occurs due to a mutual interaction between the discharges generated on each electrode edge. As the two discharges are placed closer together, their interaction becomes increasingly intense. In an SBD, streamers form during the positive half cycle of the applied voltage waveform, these are ignited at the edge of the electrode and propagate rapidly <50 ns) across the dielectric surface, resulting in charge deposition on the dielectric material. Streamer propagation continues until the electric field at the streamer tip becomes insufficient to initiate new electron avalanches. Upon termination, the quasi-neutral region behind the streamer tip gradually decays through a process of recombination and further charge deposition on the dielectric surface. During the negative half cycle, a glow-like discharge is ignited under the influence of the deposited surface charge remaining from the positive half cycle. When a second, adjacent electrode is placed in close proximity, discharges form on both electrodes and the possibility for mutual interaction arises. To unravel the nature of this interaction, the numerical model was employed to capture the dynamics of the adjacent phase shifted discharges. The results from the model indicated that the discharges in the positive cycle are coupled through the surface charge they deposit within the space between the electrodes. The deposited surface charge density profiles are shown in Fig. 0 ns acrox = 0.5 mm for both streamers, meaning the length of the streamer originating from the electrode at −2.5 mm is 3 mm and the streamer originating from the electrode at +2.5 mm is 2 mm. When a phase difference of +15° is applied, the same process occurs with the first streamer originating from the electrode edge at +2.5 mm and the minimum surface charge point is at x = −0.5 mm, closer to the −2.5 mm electrode. In the case when no phase difference is applied, both streamers ignite simultaneously, demonstrated by the location of the minimum surface charge point being exactly in the middle between the two electrodes.The surface charge density profiles presented in Fig. 19. In the negative half cycle, a discharge ignites between the deposited charge on the surface and the electrode, given that the surface charge density is altered by the applied phase shift, the EHD force exerted in the negative cycle is also modified. Figure In an SBD, the EHD force is generated by the movement of charged species drifting in the electric field, resulting in momentum transfer to neutral species through repeated collisions. In the positive half cycle, this force is exerted as the streamer tip propagates away from the electrode. Given that the localised electric field in the streamer is determined by the voltage difference between the streamer and the deposited surface charge, it is to be expected that any distortion in the surface charge profile would subsequently impact upon the force generated by the propagating streamerd = 20 mm in Fig. From Fig. In this contribution, a technique is reported that enables the direction of reactive species transport in a SBD to be manipulated without compromising the generation efficacy of the reactive species. By introducing a phase difference between the voltages applied to adjacent electrodes in an SBD an imbalance in the EHD forces generated by the discharges occurs, yielding a change in the direction of the EHD induced gas flow. Voltage phase differences between +/−60° were investigated and shown to give rise to shifts in the gas flow direction of +/−50° from the conventional perpendicular direction. A 2D numerical air plasma model was used to investigate the underpinning physical processes giving rise to the observed phenomenon. Using the model it was determined that an interaction occurs between the two adjacent discharges as a result of a distortion in the charge deposition profile in the region between the two electrodes. The profile of charge distribution in this region influences the localised electric field which in turn impacts the EHD forces generated by each plasma. Through the introduction of a phase difference between the applied voltage waveforms, it was established that one discharge was able to propagate longer and exert force in its direction of propagation over a larger distance compared to that exerted by the discharge originating from the opposite electrode, resulting in a shift in flow direction.As the generation of reactive plasma species is not compromised by the introduction of a phase difference, this technique can be safely used to facilitate the targeted delivery of plasma generated RONS to a given downstream location without compromising generation efficacy. Essentially, the technique could be used to enable large area samples to be treated using a smaller and potentially non-uniform SBD electrode. Alternatively, the technique could be employed to deliver differing compositions of RONS to targeted spatial location on a downstream sample, facilitating patterning etc.The low temperature plasma system used in this investigation consisted of two home-made high-voltage power amplifiers driven by a single low-voltage sinusoidal signal generator (Tektronix AFG3101C). The signal generator provided two sinusoidal outputs at a constant frequency of 15 kHz and the functionality to introduce a user-programmable phase shift between the two generated waveforms. The phase shifted waveforms were used as inputs to the two high-voltage amplifiers and a gain was set to give a 4 kV amplitude output. The high-voltage waveforms were connected directly to the electrodes shown in Fig. 21. The velocity vectors were computed on a square grid with spatial resolution of 56 µm using a recursive cross-correlation technique.The SBD electrode was placed within a chamber measuring 1000 mm wide, 1000 mm tall and 1500 mm long to contain the seeding particles, shown Fig. 2 and 21% O2, Equation , a plasma model and a chemical transport model. The plasma model was only solved in the plasma domain shown in Fig. nk is the density of the kth species, Γk is the flux of the kth species, klj is the two-body reaction coefficient, μk is the mobility of the kth species, Dk is the diffusion coefficient of the kth species, and V is the electric potential. A list of the reactions included in the model is given in Table In Equations  and 2),,2), nk In addition, the plasma model solved the electron energy conservation equation given by Equation .3\documenen is the electron energy density, θl is the electron energy cost of the lth reaction, Γe is the electron flux, μen and Den are the electron energy mobility and diffusion coefficients, calculated using BOLSIG +, respectively22. The system of conservation equations were coupled with the Poisson equation, which was solved for the electric potential as given by Equation (In Equations  and 4),,4), nenEquation .5\documeqe is the elementary charge, ε0 is the free space permittivity. To follow the dielectric surface charging process, the surface charge continuity equation, given by Equation , as given in Equation , ρ , ρ 12), http://datacat.liv.ac.uk/.Data used to construct the figures is made available at: