We aimed to explore the association between long-term drinking behavior change patterns with hyperuricemia (HUA) in Chinese community adults.This study was designed as a community-based unbalanced cohort study involving 4127 adults aged between 18 ~ 75 years, derived from the China Health and Nutrition Survey (CHNS) in 1997 and 2009. Drinking behavior change patterns were categorized into: never drinking, change to drinking, quitting drinking, and continued drinking. The alcoholism, type, and frequency of drinking were further categorized. We applied logistic regression models to explore the associations between drinking behavior change patterns and HUA.The average age of the participants was 54.6 (± 11.3) years and 47.8% were male. The overall prevalence of HUA was 15.5%. Drinking behavior change patterns of quitting  and continued drinking  were positively associated with high risks of HUA in the male participants. Early drinking behaviors such as liquor intake  and high consumption or frequency showed a positive correlation with HUA. Of note, heavy alcoholism  and daily drinking  had the highest risks of HUA. Furthermore, in the male participants, the association between early total alcohol intake and HUA was more pronounced at 18 standard drinks intake, with a stable increasing trend. In contrast, no statistical correlation was observed between the drinking behaviors and HUA in the female participants.Drinking behavior change patterns of quitting and continued drinking are strongly associated with increased risks of HUA in males. The risks emanated from early drinking behaviors such as liquor drinking, high drinking frequency, and alcohol consumption. Although quitting drinking was associated with lower HUA risks compared to continued drinking, it still presented an undeniable risk for HUA.The online version contains supplementary material available at 10.1186/s12889-022-13637-4. Hyperuricemia (HUA) is a potentially modifiable risk factor for kidney dysfunction, cardiovascular disease (CVD) or death, and affects 21% of the world population . The burSeveral cohort studies have reported that alcohol drinking is associated with approximately 1.5 ~ 2.0 fold higher risk with HUA, compared with non-drinking individuals . The risTo provide scientific evidence for the long-term alcohol consumption change patterns and their association with the risk of HUA among Chinese, data from the China Health and Nutrition Survey (CHNS) was used to explore the effect of long-term alcohol change patterns between 1997 and 2009 on the risk of HUA. The data on the risks of HUA and its association with different drinking patterns over time would have novel implications on the prevention and management of HUA in the Chinese population.CHNS was an ongoing cohort from 1989 to 2015 up to now, as well as an international collaborative project at the Chinese Center for Disease Control and Prevention (CCDC). The CHNS data included nine provinces . It aims to characterize how the social and economic transformation of Chinese society against the health and nutritional status of its population . Since dhttp://www.cpc.unc.edu/projects /china/data/datasets/ biomarker-data). The biomarker data collected from CHNS in 2009 involved 26 fasting blood parameters on individuals over 7 years old )= (A + B + C)/10 g*0.789.The alcoholism was divided into none (no drinking), mild , or heavy  . Alcoholp-value < 0.05 was used as a threshold of statistical significance. Data were analyzed using SAS version 9.3 (SAS Institute Inc).Data were presented as mean ± standard deviation (SD) for continuous variables or N (%) for categorical variables. Group comparison of drinking behaviors was performed using the chi-square test, fisher’s exact test for categorical variables, and variance analysis for continuous variables where appropriate. Univariable and multivariable logistic regression models were used to explore the association between demographic, anthropometry, biochemical index or behavior information, and HUA. To determine whether drinking behavior change patterns and early drinking behaviors were independently associated with the HUA by gender. Variables that were both associated with the HUA and deemed to be causally related to drinking-related behaviors were included as potential confounders (Supplementary Table n = 5335) and missing visits sample (n = 8717) were compared. Follow-up sample had higher proportion of old age, obese WHR, BMI ≥ 24 kg/m2, diabetes and hypertension  while 93 had no data on SUA. Finally, 4127 participants were included in the formal analysis  and 23.1% (216/935), respectively. Further analysis showed that participants who kept heavy drinking had a higher prevalence of HUA (30.7% [54/176]) than those with the other three drinking patterns  or heavy alcoholism , weekly alcohol drinking , and almost daily drinking  and were positively associated with HUA in the males, compared to non-drinking  group showed that quitting drinking (mainly manifestation for mild to abstainer) was positively associated with HUA in the 18 ~ 29 years subgroup  in male. And continued drinking  was positively associated with HUA in the 30 ~ 44, 45 ~ 59, 60 ~ 75 years subgroup  in 1997, with high risk among the participants whose early drinking behaviors including heavy alcoholism, almost daily drinking and liquor intake. There existed no robust associations between drinking-related behaviors and HUA in females  [Although the risk of HUA was lower in those who quit drinking compared to those with continued drinking, it still elevates the risk of HUA, compared to non-drinking. This result implies that early drinking could lead to an increased risk of HUA in males. The mechanism of decreased urate excretion has been implicated in the pathogenesis of alcohol-induced HUA. The study showed that HUA develops following conversion of alcohol to lactic acid, thus reducing uric acid excretion by competitively inhibiting uric acid secretion by the proximal tubule . Faller Consistent with a single-center study in Liaoning of China , our finPotential limitations of our study deserve comment. Firstly, SUA was measured only in 2009 wave in CHNS study. Therefore, drinking status at follow-up of 2009 was assessed at the same time as the assessment of HUA, leading to the weakening interpretability of the results due to the unbalanced panel data structure. Secondly, our data lacked more than half of the variables on physical activity. To bridge this gap, we tried to adjust partly for total protein intake. In addition, significant heterogeneity was observed between included follow-up and missing visits sample, which might be caused the younger age of the missing visits sample. It may produce the potential selection bias in our study. Besides, our data failed to eliminate possible effects of underlying diseases and medications used for diseases such as uric-acid-lowering medication which might have affected the outcome.Taken together, our study demonstrated that drinking behavior change patterns such as quitting and continued drinking are strongly associated with increased risks of HUA in males. The risks emanated from early drinking behaviors such as liquor drinking, high drinking frequency, and alcohol consumption. Although the risk of HUA in quitting drinking was lower than that in continued drinking patterns, it was positively associated with HUA. The long-term effect of early drinking behaviors on HUA could not be ignored.Additional file 1.


To reduce the cost of inspecting old sewer pipes, we have been developing a low-cost sewer inspection system that uses drifting wireless cameras to record videos of the interior of a sewer pipe while drifting. The video’s data are transmitted to access points placed in utility holes and further transmitted to a video server where each video frame is linked to its capturing position so that users can identify the damaged areas. However, in small-diameter sewer pipes, locating drifting nodes over the full extent of the pipeline using Wi-Fi-based localization is difficult due to the limited reach of radio waves. In addition, there is the unavailability of a GNSS signal. We propose a function to link each video frame to a position based on linear interpolation using landmarks detected by the camera and image processing. Experiments for testing the accuracy of the localization in an underground sewer pipe showed that all utility holes were successfully detected as landmarks, and the maximum location estimation accuracy was less than 11.5% of the maximum interval of landmarks. Aged sewer pipes are susceptible to severe problems such as clogging by sand entering from cracks or by tree roots; the deterioration of sewer function; and road collapse. The year 2022 marks more than 30 years since the installation of 40% of a total of 490,000 km of sewer pipes in Japan ,2. ThereTo shorten the time and reduce the monetary costs, we propose a sewer-pipe-inspection method using drifting wireless camera nodes (CNs) , as showThis system is safe because inspectors do not need to enter the pipes. In addition, unlike fiberscopes and self-propelled robot methods, the inspection range is not limited by the cables. Furthermore, unlike the boat-shaped camera technique, it is possible to watch the captured images before the camera drifts downstream through the sewer pipe. It is also possible to identify where the video frame was captured. These features reduce labor costs and are convenient.This system uses wireless video data transmission from CNs in a sewer pipe. To identify the performance of the wireless communication in narrow  is limited. Additionally, the CN’s weight should be light so that it can easily drift down a sewer pipe. Thus, the additional devices for the location estimation should be minimum. To tackle this problem, it is necessary to link each video frame to the position where it was captured with the minimum additional devices and without depending on radio communication.The contributions of this paper are summarized as follows. Firstly, we propose a method to estimate CN positions based on linear interpolation using utility holes and pipe joints as landmarks in a sewer pipe. We also implemented the proposed method together with a browsing system that links location information to each frame of the video and conducted experiments to evaluate the accuracy of the proposed localization function using a drifting CN in a real underground pipe.The remainder of this paper is structured as follows: we introduce related work on the self-position estimation of wireless mobile devices in In this section, we review studies on indoor localization methods, particularly focusing on their applications in sewer pipes. To link each of captured video frames to the position of a CN, it is necessary to estimate the CN’s position at a given timestamp. Generally, GNSS and signal strength from wireless LAN and cellular phone base stations are used to estimate the locations of wireless communication devices outdoors. Radiowaves from satellites and base stations, however, do not reach the interior of sewer pipes. Therefore, it is necessary to develop self-localization techniques for CNs that do not rely on them. By considering the utilization of a sewer inspection system with drifting cameras moving in a narrow pipe, the weight of the equipment should be small, and the number of additional devices needed to be installed in the environment should be minimal. Potential methods for localization of CNs in sewer pipes include using visible light, sound waves, radiowaves, inertial measurement units (IMUs), and cameras.Visible light enables communication over 1 km using 400–800 THz light waves, which are modulated and emitted mainly by light-emitting diodes (LEDs) . VisibleSound-wave-based localization can be used to estimate the position of CNs in sewer pipes. Sound waves are relatively slower than radio waves; thus, it is easy to measure the arrival delay of sound waves, enabling localizations with high accuracy (error of a few centimeters). There are two types of sound wave localization: ultrasonic and acoustic.The range of ultrasonic-wave-based localization is generally about ten meters in the air . Chew etSince acoustic waves generally have less wave attenuation than ultrasonic sound, they propagate over longer distances than ultrasonic sound. Worley et al. proposed ToF-based localization utilizing acoustic echo in a 15 m pipe using a loudspeaker and microphone installed on a robot . They acUltra-wide band (UWB)-based localization uses radio waves ranging from 3.1 to 10.6 GHz. Despite the high frequency, in general, the localization has highly accurate positioning with an error level of a few centimeters. In addition, it is characterized by low power consumption due to its row duty cycle . Dabove Wi-Fi-based localization techniques are also popular in indoor localization. A CN of our sewer inspection system has a Wi-Fi module for sending video data to an AP. If Wi-Fi-based localization is available for the sewer pipe environment, there is no need for additional sensors on the CN, reducing the cost of implementation and weight limitations. Wi-Fi-based localization using radio signal strength (RSSI) is popular. Poulose et al. conducted localization experiments based on Wi-Fi fingerprinting by using a smartphone device and multiple Wi-Fi RSSI measurements and achieved localization errors within 0.44 m for a linear motion device in an indoor environment . Hashem Maletic et al. conducted a performance evaluation for mmWave-ToF-based ranges in the 60 GHz band in an indoor environment. In the experiment, two anchors placed 1.8 m apart estimated the position of a tag in a room within an error range of 5 cm . In addiAitken et al.  compreheInertial measurement units (IMUs) can potentially be used with our sewer inspection system to localize CNs. IMUs aided by odometry sensing have been used to localize mobile robots ,31. MurtThe CN used in our sewer inspection system was equipped with a camera for inspection. If a CN can be localized with a camera module alone, there is no need for the additional cost of mounting another sensor on the CN. Hansen et al. proposed a localization method that uses a visual localization simultaneously with mapping (vSLAM) with a monocular camera and stereo camera ,34,35. HIn this section, we provide an overview of the sewer inspection system with drifting wireless CNs that we developed for sewer pipes with diameters of 200 to 250 mm, which are the most popular pipes in Japan. We inspect several hundred meters to several kilometers at a time. A CN and an AP communicate with each other via wireless LAN, and their communication range is about 5–10 m, which is much shorter than the distance between utility holes, which is typically 30 m or more.Each CN consists of a camera, sensor, light, wireless LAN interface, battery, and a small computer installed in a waterproof transparent capsule. We developed a prototype CN for this system. Each AP shown in As described in SVTP allows multiple CNs to transmit videos of different parts of a section to a downstream AP based on the timestamp of each CN when they capture the videos. If the velocity of the water in the sewer pipe is constant and known and the position of the CN when it first received a beacon from an AP is known, then estimating the position of the CN when it captured a video frame between the AP and the next AP is easy. However, the speed of the water flow is not generally constant, and APs are installed at only some of the utility holes in the inspection area. Thus, if the distance between APs is long, the position estimation error caused by assuming a constant water speed will be significant. In addition, even if the water flow is constant, the positions where In this section, we propose a method for estimating the location of a CN based on the elapsed time after the CN passes the closest landmark. We use the linear interpolation technique based on the location of landmarks, such as APs and utility holes with known positions.The problem we solve in this paper involves identifying the position of a drifting camera node (CN) moving in a sewer pipe, and this is performed by assuming the following system model.The CN cannot use a GNSS. The CN and APs do not have sensors that can be used to estimate the position of the CN except for cameras and wireless communication interfaces.The CN can communicate with access points (APs) via a radio communication link when it is close to one of them . The APs are installed in some of the utility holes. The distances between neighboring utility holes are longer than twice the maximum communication distance between the CN and an AP. The received signal strength of the radio signal from an AP is sufficiently low when the distance between the CN and the AP is longer than the maximum communication distance. Thus, the CN cannot use the received signal strength of the radio signal from an AP to estimate its position when the distance between the CN and the AP is long.One camera is installed in the CN. The camera points straight up and records videos of the pipe wall, ceiling, and the interior of a utility hole that is close to the CN.The CN records videos while it drifts in the sewer pipe and records the timestamp when each video frame is captured. When the CN can communicate with an AP, the CN sends the recorded video data with timestamps of the video frames to the AP. The video server that receives all data received by the APs estimate the CN’s position when each frame is captured.The starting position of the CN and positions of all utility holes and joints of pipe segments are known.As described in t during interval [For the sake of simplicity, the following description assumes that only one CN is used; the same method can be used to locate two or more CNs. The timestamp used to localize a CN is assumed to be obtained from the clock on the CN. Let The equation uses only the time difference of local clocks on the same device. Therefore, the local clocks of the CNs need not be synchronized with other devices. When aggregating video data, the video server can estimate the position at which the video frame was captured based on the local timestamp of the CN linked to each frame. Since the estimation error monotonically increases with the distance between the last landmark that the CN passed and the CN, the more landmarks there are, the more accurate the estimation.The potential landmarks in sewer pipes include utility holes, sewer pipe segment joints, and APs. The typical distance between the utility holes of small-diameter sewer pipes ; it links the timestamp of each frame of the received video data to the location based on the linear interpolation, as follows. Let We verified the accuracy of the proposed localization system using an underground pipe testbed. First, we explain the environment for the verification of the localization accuracy and verification method. Then, we show the results of the verification. Finally, we discuss the localization accuracy of the proposed method based on the results.We evaluated the performance of the proposed system in an underground reinforced concrete sewer pipe on our campus, as shown in We conducted the experiments using the following procedure. First, to control the CN, we pre-connected it to a PC via SSH in the 2.4 GHz IEEE 802.11n ad hoc mode. As soon as we released the CN from the first upstream handhole point, we sent a raspivid command  from theAfter the trials, we transferred the videos recorded by the CN to a Linux machine, which ran the video frame localization program explained in It was observed that the estimated drifting position errors were within the distance between neighboring handholes, which prevented the possibility of inspecting and excavating the incorrect section of the sewer pipe.In 2-meter-long sections, between 5 and 7 m and between 7 and 8 m, the localization error was within 0.15 m, as shown in In the experiment, the CN detected all handholes in all trials. However, if some of the landmarks are not detected in the inspection area, it is impossible to use consecutive landmarks to estimate the CN’s position between them, causing a significant error during linear interpolations. To avoid errors, a function for detecting landmark detection failure is needed. As the typical joint interval and the time of passing the utility holes are known, and the moving speed of the CN can be estimated from the history of the time of passage, the landmark detection failure can be easily detected. However, the CN may collide with obstacles in a pipe, e.g., tree roots, and temporarily stop, causing a significant error in linear interpolation. To tackle the drawbacks of linear interpolation, we propose adding IMU and the odometry function described in In these experiments, the drifting speed of the CN was set to 0.26 m/s. However, in a real sewer pipe environment, a CN drifts at a variable speed. If the speed is fast, the video frames captured by the CN cannot reflect all scenes of the inspection area. Let us consider a case when a CN captures video frames at 30 fps, one video frame covers a sewer pipe of length ranging 0.2 m  included in the video frames captured by a camera on a drifting camera node (CN) were successfully detected by using the Hough transform technique and contributed to accurately estimating the position of the CN, i.e., the position where each video frame was captured. The proposed localization system only requires the minimum required components on a CN, a camera, a light, and a Wi-Fi module, which are originally needed for the drifting-camera-based sewer-pipe-inspection system.The results showed that all handholes, installed at 1, 2, and 4 m intervals, were successfully detected, and the maximum localization error was less than 0.46 m, which was 11.5% of the maximum interval of the handholes. Assuming that the pipe joints are used as landmarks, the accuracy of the video frame’s localization with the proposed method will be enough to identify damaged pipe segments, since the intervals are typically 2 m long. To the best of the authors’ knowledge, this is the first study presenting the localization of a drifting camera in a narrow sewer pipe and not a self-propelled robot, and it is based on image processing.In the future, we plan to (1) achieve accurate detection of pipe joints; (2) conduct experiments using actual sewer pipes with large utility holes (manholes), obstacles, and damage; (3) combine the proposed method with IMU for more accurate localization of CNs; and (4) propose a method to correct the localization of CNs in cases some of the landmarks are failed to be detected.


Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis. ML has demonstrated its capability to implement semantic segmentation, which classifies objects in an image pixel by pixel, and has been applied to practical applications for example, automated driving technology and the medical field7.In recent years, researchers have been trying to implement machine learning (ML) based approaches in a wide range of scientific fields, and it has attracted considerable attention17. Many reported cases of extracting specific features from a dataset by ML have shown that ML can be further advanced toward a major unbiased data-driven analysis method to gain new insights from the extracted features2. This is true also for the temporal series of dataset such as observations of dynamic phenomena, there have also been attempts to use ML-based approaches. Several recent studies employed ML to predict the plastic deformation of micron-scale crystalline solids using data from discrete dislocations dynamics simulations18, or to predict microstructure evolution and associated properties changes from spatiotemporal data19. In the case of research focusing on crystal defects, ML has been mostly used to classify and semantically segment crystal defects in materials in electron microscope images22. Therefore, there are very few examples of ML analyzing the temporal change of crystal defects such as dislocation dynamics directly from experimental observation videos.An emerging application of ML is analytical methods for extracting characteristic information about the structure, composition, and properties of various materials, especially nanoscale materials23. However, the quantitative evaluation of dislocation motion has not been studied in details. Dislocations generally exhibit intermittent motions, indicating that it is important to quantitatively evaluate their temporal velocities instead of their average velocities, whereas it has been difficult to capture the motion of individual dislocation and assess their temporal velocities experimentally using transmission electron microscopy (TEM) in the past. Recent dramatic advances in digital imaging technology have made it possible to provide the moment of a nanoscale reaction on a regular laboratory scale24. Nonetheless, frameworks for quantitatively analyzing dynamic observation data taken by TEM and linking them to mechanical properties are still in the trial-and-error stage. There are multiple technical challenges for implementing automatic tracking to nanoscale objects such as dislocations in TEM videos even the nanoscale objects are clearly observed in the video due to the TEM's unique contrast generation mechanisms and the nature of nanoscale microstructural features. First, the nanoscale objects of interest must be recognized in a large number of frames in the TEM video data, in which misleading microstructural or image features frequently coexist. Second, the number of valid video frames is almost always smaller than the number of data required for training in ML, making it difficult to universally satisfy the conditions necessary for ML optimization. Third, even after the nanoscale objects of interest are detected, individual objects must be separately tracked throughout the TEM video with being distinguished from others. Especially in the case that the objects repeat unexpected behaviors such as sudden move-and-stop and irregular change of own shape, tracking the objects becomes highly challenging. The unexpected behaviors are often caused by atomic to nanoscale local environment, which is closely related the inhomogeneity of material. Thus, developing a model to predict such behaviors for data analysis would be nearly impossible.The general relationship between the macroscopic deformation behavior of metallic materials and the average dislocation velocity is a well-known factIn this study, we developed a ML-based framework for quantitative analysis of nanoscale objects’ dynamic behavior based on the information obtained by detecting the objects in a video using machine learning and tracking the detected objects with particle filters. We confirmed that if a video presents a single experiment, the number of data is sufficient for machine learning to detect dislocations in that video. We then applied the developed ML-based framework to a video in which the dislocation gliding under applied external tensile stresses in a metal was observed using TEM. By detecting and tracking dislocations in the TEM video singly and as a whole using the framework, we were able to calculate the time history of dislocation velocity and quantitatively analyzed its behavior. In particular, we employed the particle filter to the quantitative analysis part of the framework. Thanks to the probabilistic prediction of the particle filter, we successfully captured the unexpected behaviors of individual dislocations.25.When a metallic material is plastically deformed by applying the stress mentclass2pt{minimAssuming no dislocation formation or annihilation occurs, the macroscopic shear strain of a crystal 23. They measured the average velocity of the dislocations by dividing the displacement of the dislocations by the time that the stress was applied. However, since the actual dislocation motion is intermittent, a continuous velocity measurement providing the chronological changes is necessary to understand the intrinsic dislocation behavior. Therefore, the overreaching goal of the framework development is to assess the traverse speed of nanoscale objects such as dislocations without compromising the original data’s temporal and spatial resolutions. In this study, we attempt to archive the10 nm/s order temporal and spatial resolutions by applying a U-Net based ML and particle filter integrated method to in situ TEM deformation videos.For the dislocation velocity measurement by TEM observation, Johnston et al. reported one of the first successful cases that measured the average dislocation velocityThe actual validation of the framework proposed in this study was implemented by the following steps described in the rest of this section. The experimental data, TEM videos, were taken during in-situ TEM deformation experiments, in which a high-manganese austenitic steel (Fe-31Mn-3Al-3Si) was subjected to a forced displacement with a tensile rate of 100 nm/s. as shown in Fig. At the first glance, the position of the field of view (FOV) of the TEM video was not still in order to track down moving dislocations, i.e., there was a large shift of recorded area in the middle of the video. Without fixing the FOV, the velocity of dislocations cannot be measured accurately. We fixed the FOV by i) choose small recognizable features that were in a dislocation-free region and stationary between at least two consecutive scenes and track down the chosen points throughout the TEM video, ii) shift corrections were calculated for the points between scenes , then iii) the corrections were applied to the video under the estimation that the movement of the points were corresponding to that of the scenes. Since the position of each of frames shift relative each other by applying the correct, overlapping parts were cropped throughout the corrected video to finish the FOV fixing.28 was employed to choose the points in the above step i) and to calculate the displacement by tracking the characteristic points in the step ii). Here, optical flow is a method to track feature points in a video, and commonly used in the computer vision field. As nothing moved excepting the dislocations in the TEM experiment video of this study, optical flow is one of the most suitable methods to fix the FOV of the video.It should be noted that the optical flow estimationAn example of the fixed FOV is shown in Fig. In the next step, we performed the semantic segmentation for all frames of the TEM video by ML. Classification of the pixels into dislocation and non-dislocation pixels was conducted on a pixel-by-pixel basis. This mechanical classification makes it possible to objectively evaluate the motion of dislocations among the frames. There are many lines (liner features) in the TEM videos that are not actual dislocations. It would be very time-consuming and tedious to manually detect dislocations in every frame of the video by separating them from other liner feature, as there were dozens of dislocations in one image.There are two advantages to use ML for this task. The first one is that the detection process is efficient and objective. ML detects dislocations in every frame of the video after learning from a training data which is a correct image set created by the operators. The detection of dislocations in the video will be conducted on the same criteria as the one of the correct image set. The second one is that ML is more robust than numerical filtering. ML is able to detect dislocations without being misled by non-dislocation lines in a TEM image. For these reasons, we thought it is the best to use a ML method to detect dislocations in the video.29 and SegNet30. Due to its high performance, U-Net6 has been used in many researches32, therefore we employed U-Net in this study. U-Net is a method developed by Ronneberger et al. that has been succeeded in semantic segmentation for cells in microscope images. We manually traced the first 170 images, i.e., from 1 to 170 frames of the TEM video, to generate 170 correct images. Then we trained U-Net using 1—100 frames as training data and 101—170 frames as test data. Figure There are several ML methods for semantic segmentation, such as FCN34 is more suitable for tracking dislocations. Since particle filter tracks objects using probability distributions, it can retake and keep tracking individual dislocations even if the exact location of more than one dislocations was temporary lost due to a sudden and unforeseen movement. Particle filter is a better fit for this case as the dislocations' shape change likely occur and the movement of dislocations may be unpredictable.In the last step, in order to track down the same dislocation in the video, we used a particle filter, which is one of object tracking methods in videos. Other methods such as optical flow are commonly used for the object tracking. Optical flow, however, cannot track dislocations accurately. Optical flow cannot track the point which moves quickly and it is difficult to specify the feature points in a line with shape changes, although movements of dislocations may be unpredictable and the shapes of dislocations may change. In this study, we thought that a particle filter approachFor the use of particle filter, it is necessary to identify individual dislocations in each of video frames. We adopted a method to identify dislocations based on the spatial continuity of pixels belonging to the dislocations. Figure In here, the results of successful tracking four targeted dislocations are shown. The dislocations (i)-(iv) are shown in Fig. 35.The sample used in the experiment is an austenitic steel having the face-centered cubic crystal structure thus the magnitude of the Burgers vector can be calculated as Since the dislocation density of the TEM image used in this study cannot be determined precisely, we calculated the dislocation density in the FOV of the TEM image and then used it as the dislocation density. The original size of the TEM video was 480 × 480 pixels, and 1 Substituting these values and the measured average dislocation velocity of 0.08 µm/s into the Eq. , the sheIn Fig. In Fig. The goal of our research is to develop a framework that can measure dislocation velocities using machine learning and a particle filter. The results of our measurements can be validated by comparing them with the results of molecular dynamics or dislocation dynamics simulation. The results can also be verified by our method itself applied to a series of experiments with various strain rates. We can qualitatively verify the results by checking whether the dislocation velocity increases with the strain rate.Figure In this study, we developed a Framework to detect dislocations in videos captured using TEM using U-Net and measure their migration velocity using particle filters by taking their intermittent motion and shape changes into account. The dislocation velocities were measured and confirmed to be theoretically valid, and their intermittent motions could be quantitatively evaluated.https://doi.org/10.1126/science.1219643).This method has possibility to be applied not only to dislocation videos like the one used in this study, but also to videos of TEM in situ experiments (dynamic observation) on other phenomena. For example, immediate applications would be dynamically measure the velocity and analyze the shape changes of dislocations in various dislocation reactions including but not limited to Orowan mechanism (particle dispersion strengthening mechanism), grain boundary migration, and deformation twinning behavior induced by external stimuli such as magnetic field, heat or stress field. It is also possible to chase the velocity, motion and shape change of nanoparticles during an oriented-attachment reaction where dynamics in particles, translational and rotational accelerations, is critical to gain the mechanistic understanding , which enables robust tracking against noise and environmental variations. The particle filter algorithm is shown below  and the likelihood (Procedure 4). appropriately based on information such as the motion and shape of the target object, in order to track the target object accurately. In this study, we used the information that dislocations moved only in one direction for prediction. We also used the information that information that the pixel with the dislocation is black and the positional relationship of the dislocations does not change significantly between the previous and current frames for likelihood function.Supplementary Information.


Thymus vulgaris, Thymus satureioides, and Thymus zygis are endemic Moroccan species that are intensively used due to their extensive medications and culinary properties. To enhance and preserve these overexploited species, the effect of provenance on the chemical composition of essential oils and antimicrobial activity against human pathogens were studied. Essential oils (EO) obtained by hydrodistillation from the flowering tops of thyme species were analyzed by GC-SM. The determination of minimum inhibitory (MIC), bactericidal (MBC), and fungicide (MFC) concentrations of EO were studied by microplate microdilution. The correlation between the chemical composition of EO and antimicrobial properties were evaluated using R software. The samples studied gave variable yields, ranging from 0.70 ± 0.03% to 4.12 ± 0.21%. The main constituents of Thymus vulgaris harvested from the municipality of El Hammam are carvacrol (68.8%), γ-terpinene (11.5%), and p-cymene (3.9%), while borneol (41.3% and 31.7%) and carvacrol (14.6% and 9.8%) are the most abundant in Thymus satureioides of the communes of Tata and Tigrigra respectively. For Thymus zygis, the results revealed the dominance of carvacrol (51.7% and 57.5%) for the municipalities of Tigrigra and Ain Aghbal, thymol (47.1% and 42.1%) for the municipalities of Bensmim and Timahdite respectively. These chemical profiles have similarities, but also reveal differences from the results given in the literature. In addition, the essential oils most active towards the microorganisms evaluated were those of Thymus vulgaris, followed by Thymus zygis and Thymus satureioides. These EO have very powerful MIC (MIC ⩽ 300 μg/ml) against Gram-negative bacteria, and in particular, concerning Enterobacters cloacae, Citrobacter koseri, and Acinetobacter baumannii. Thymus zygis EO is the most active on candidates compared to Thymus vulgaris and Thymus satureioides EO, except Candida dubliniensis which was inhibited by Thymus satureioides EO from the commune of Azrou with a MIC = 18.75 μg/ml. The correlation determined between the major components and MIC showed that phenols have the strongest positive effects on antimicrobial properties, followed by terpenes and non-aromatic alcohols. In addition, different sensitivities of pathogens to chemical families have been observed against Enterobacter cloacae, Citrobacter koseri, Candida parapsilosis, Staphylococcus aureus multiresistant, Pseudomonas aeruginosa, Acinetobacter baumannii, and Aspergillus niger. Our results support the idea that these oils could be very useful in flavoring, food preservation, as well as a source of antimicrobial agents of great power against multidrug-resistant strains. Their production and antimicrobial potential have taken an important place in scientific research .Thymus zygis, Thymus satureioides, and Thymus vulgaris.Due to its geographical location and the diversity of its ecological conditions, Morocco offers a rich and diverse floristic biodiversity and vegetation. A large number of aromatic and medicinal plants grow spontaneously and are used in the traditional pharmacopeia or exploited for industrial needs . Among tThymus. This genus Thymus includes between 250, and 350 species, subspecies, and varieties of wild plants , they also grow on the mountains of Ethiopia and southwest Saudi Arabia through the Sinai Peninsula in Egypt. They can also be found in Siberia and even the Himalayas. According to the study conducted by Nickavar , the EO of thymes are generally recognized as healthy. Among them, thymol is commonly considered a natural, non-toxic, and ecological bioactive agent, with various pharmacological functions .According to the WHO, by 2050, microbial infections could be one of the world's leading causes of death . Indeed,Thymus vulgaris, Thymus satureioides and Thymus zygis collected from the regions of Khenifra, Tata and Ifrane respectively. We have also determined the chemical composition and evaluated the antimicrobial activity of EOs against twenty-four of the most pathogenic bacteria and eight fungi, which have been shown to be implicated in healthcare-associated and food-borne infections.We have in fact evidenced the effect of the origin of seven samples on the yield, chemical composition and antimicrobial activity of essential oils of This study is integrated in a context of valorization of Moroccan aromatic and medicinal plants that are potentially exploitable.22.1The present study is carried out on samples of three species of thyme from seven sites. These samples were collected at the time of their flowering, at the level of the localities of the regions of Tata, Khenifra, and Ifrane. Then, the plants were dried in the shade for about ten days. They were identified and authenticated at the Scientific Institute of Rabat, Department of Botany. Detailed information on each species is given in the 2.2The determination of the antimicrobial activity of different EO was carried out on twenty-four bacterial strains and eight fungal strains , Table 42.32.3.12.3.1.1The method used is adopted according to the AFNOR standard (NF - V03-402 1985) . A quant0: initial mass of the plant; M1: mass after drying.With: M2.3.1.2The principle consists in adding 10 ml of hot distilled water to a quantity of 2 g of the tested sample. The mixture is filtered and left to cool. pH was measured using Ohaus Starter 3100 pH Bench meter equipped with STPURE electrode.2.3.1.3The principle is based on the calcination of the sample at a temperature of 550° C in a muffle furnace until whitish ash of constant weight is obtained . The org1: Weight of the capsule and sample before calcination; W2: Weight of the capsule and the sample after calcination; TS: Test sample.OM%: Organic matter; WThe ash content is calculated as follows: Ash % = 100 – OM%.2.3.1.43 + 3 HCl). The latter allows for large sample sizes, which limits the problems of sample representativeness. The process consists of mixing the crushed plant material (0.1 g) with 3 ml of the aqua regal prepared from 1 ml of nitric acid HNO3 (99%) and 2 ml of hydrochloric acid HCl (37%), the whole is placed in a reflux assembly at 200° C for two hours, after cooling we let it settle. Then we took the supernatant and filtered it on a membrane of 0.45 μm and then we completed it to 15 ml with distilled water. The concentrations of heavy metals were determined by the ICP-AES inductively coupled plasma atomic emission spectrometer (Ultima 2 Jobin Yvon) at the UATRS laboratory  at CNRST-Rabat , cadmium (Cd), chromium (Cr), iron (Fe), lead (Pb), antimony (Sb), and titanium (Ti). There are limited standards for contamination for each metal. However, exceptions are made for drugs whose raw materials are known to accumulate cadmium in large quantities. For the determination of the contents of major elements , we chose the standardized mineralization protocol , with aqua regia (HNOST-Rabat .2.3.22SO4) and stored at a temperature of-4 °C in a dark bottle until use. The EO yield was calculated from 100 g of the plant matter by the formula =WWith.W(EO): Weight of EO recovered (g).0: weight of plant material (100 g).W2.3.32/air gas. The fragmentation is carried out by electron impact of 70 eV intensity. The column temperature is programmed at a rate of 4 °C/min rise from 50 to 200 °C for 5 min. The injection mode is split , the carrier gas used is nitrogen with a flow rate of 1 ml/min. The device was controlled by a HP Chemstation computer system managing the operation of the device and allowing to follow the evolution of chromatographic analyses. The GC–MS was coupled to a mass spectrometer (HP 5973 series).The chromatographic analysis was carried out on a HP 6890 series gas chromatograph , equipped with a DB-5 (5% phenylmethylsiloxane) capillary column (30 m × 0.25 mm × 0.25 µm film thickness), an FID detector set at 250 °C and lied by a mixture of HThe identification of the chemical composition of the EO was performed by determining and comparing the Kovats Indices (KI) of the compounds with those of known standard products described in the databases of Kovats, E.S. (1965) , Adams  and HübsIdentification of each compound was performed using the Kovats index by comparing peak retention times with those of known authentic standards available in the authors' laboratory and comparing their reported KI and MS data with those recorded in the 14 WILEY and NIST standards mass spectra database and published literature. Kovats's indices compare the retention time of any product with the retention time of a linear alkane containing the same carbon number. They are determined by co-injecting a mixture of the alkanes (C7-C40 standard) under the same operating conditions.2.42 mg/ml of each EO. These dilutions were prepared in Mueller-Hinton broth medium for bacteria and in Sabouraud broth for fungi for a final volume of 100 µl for each concentration. Then, 100 µl of microbial inoculum with a final concentration of 106 or 104 CFU/ml in the case of bacteria or fungi were added to the different concentrations of the dilution series. After incubation for 24 h at 37 °C, 10 µl of resazurin is added to each well as an indicator of bacterial growth. After a second incubation at 37 °C for two hours, microbial growth was revealed by the change in coloration from purple to pink. The MIC value is determined as the lowest concentration that prevents a color change of the resazurin. The 11th and 12th wells were considered the growth and sterility control respectively. The test was repeated twice for each oil. The standard antifungal studied was terbinafin 250 mg, this drug was added, after grinding, to 2 ml of 10% DMSO. To determine the minimum bactericidal concentration/minimum fungicidal concentration (MBC/MFC), 10 µl was taken from each well with no visible growth and plated on Mueller Hinton (MH) agar for 24 h at 37 °C for bacteria or on Sabouraud for fungi. BMC and MHC were defined as the lowest concentration of samples tested that produced a 99.99% reduction in CFU/ml compared to the control. In addition, the MBC/MIC or MFC/MIC ratio of each extract can be calculated to assess the antimicrobial potency, thus, if the ratio is<4, the effect of the essential oil is bactericidal/fungicidal, if the ratio is>4, the sample has a bacteriostatic/fungistatic effect (Determination of the minimum inhibitory concentration (MIC) was performed following the reference method of microdilution using 96-well microplates . The MICc effect .2.5All data are presented as the average (S.E.M) of the indicated number of experiments. The results were analyzed by Unidirectional or Bidirectional Variance Analysis (ANOVA) with a Tukey-Kramer multiple comparison post-test performed using Graph Pad Prism version 8.0 for Windows . The statistical significance was set at p < 0.05. The results relating to the chemical variability of EO were analyzed using the R software. The Principal Component Analysis (PCA) was carried out with Pearson type matrices. The Hierarchical Cluster Analysis (HCA) and the dendrograms were made with dissimilarity matrices calculated in Euclidean distance and the method of aggregation systematically chosen is the average link. To assess whether the constituents of essential oils can be useful in reflecting the relationships between phytochemical and antimicrobial activities, 20 major compounds detected in the oil samples were selected and used for this purpose. The major compounds and all MIC values of essential oils were subjected to PCA and HCA.33.13.1.1The collected samples have undergone quality control at our laboratory level by measuring several characteristic parameters such as moisture content (MC), pH, ash, and ICP . The results are presented in 3.1.1.1Thymus vulgaris (18.88%) collected from El Hammam locality in the Khenifra region, followed by the species of Thymus zygis  collected from the Ifrane region in Ain Aghbal, Bensmim, Tigrigra and Timahdite localities respectively. While the moisture content recorded for Thymus satureioides (14.48 and 14.27%) collected from Tata and Tigrigra localities respectively are the least low.The moisture content of thymes measured by the oven method varies between 14.27 and 18.88%. These moisture contents are directly related to the activity of the water (Aw). The high contents are recorded for In addition, most microorganisms grow at a water activity between 0.95 and 1, molds and most bacteria are unable to grow at a moisture content below 24% where Aw is equal to 0.7. Therefore, samples dried under laboratory conditions are of good quality.3.1.1.2To know the stability of the plants concerning the microorganisms and the assimilability of the mineral elements, the pH of the plant matter was determined, it is a quality index determining the aptitude for the conservation of the plants. It is one of the main obstacles that microbial flora must overcome to ensure its proliferation. Microorganisms pathogenic to humans rarely grow at a pH acid, below 4. Most microorganisms develop at pH levels close to neutrality. Moreover, the pH conditions the assimilability and the good availability of mineral elements. Acidophilic plants, or so-called heathland plants, require a pH < 5.5 and are free of total limestone, whereas neutrophilic plants can tolerate a wide range of pH  .Including our case, the pH of the species studied varies between 5.17 and 5.69. These values offer these thymes a quality of good character with good availability of mineral elements.3.1.1.3Thymus zygis collected in the Bensmim region of Ifrane in which we recorded a high rate of about 14.31%, the other rates vary between 6.39 and 8.40%. The results of our samples are in the limits, since the international food standards “Codex Alimentarius C.X.S 328-2017″ for dried thyme are set at 12%.The percentage of total ash provides information on the mineral content, as minerals are not transformed into volatile substances at high temperatures, unlike organic matter. The total ash contents observed are comparable and similar between the species studied except for 3.1.1.4Medicinal herbs are easily contaminated during growth, development, and processing. After collection and processing, the heavy metals contained in plants eventually enter the human body and can disrupt the normal functions of the central nervous system, liver, lungs, heart, kidneys, and brain, leading to hypertension, abdominal pain, rashes, intestinal ulcers and different types of cancers.Thymus zygis collected in Ain Aghbal (TZAA) locality of the Ifrane region in which we observed a slightly high concentration of Iron (4.489 mg / l) compared to other species. This slightly elevated amount of Iron in TZAA may be due to foliar absorption of ambient air. These results show a slight variation in the concentrations of heavy metals in the powders of the species evaluated. These variations depend on the species and the assimilated element. The accumulation capacity of metals Cr, Pb, Sb, Ti by the studied thymes follows the following order: TVHA > TZTIM > TZAA > TZTIG. However, the order of accumulation of heavy metals As, Cd and Fe is variable from one species to another.The By way of conclusion, the thymes studied can be proposed for direct consumption, as an ingredient in food processing, or for repackaging if necessary, as they can be safely intended for industrial treatments.3.1.2The average essential oil yield of each species was calculated according to the dry plant matter obtained from the flowering tops of the different thymes. The essential oil yield obtained is shown in The density of each essential oil analyzed by the conventional method ranged from 0.863 to 1.113 g/mL, as shown in Thymus zygis (TZBE) collected in Besmim, Ifrane region at an altitude of 1579 m, gave the highest essential oil yield (4.12%) followed by the Thymus vulgaris (TVHA) sample collected at an altitude of 1125 m in El Hammam, Khénifra region which is (3.77%). A high EO yield  was also obtained for Thymus zygis species  collected in the Ifrane region at Tigrigra (1121 m), Ain Aghbal (1170 m), and Timahdite (1961.5) respectively. For Thymus satureioides (TSAZ and TSTA), the average essential oil yield is (1.4%) for Ain Aghbal at an altitude of 1499 m and (0.7%) at Tata located at an altitude of 1625.5 m. These two rates are low compared to those obtained for Thymus zygis and Thymus vulgaris samples. On the other hand, the yields obtained for the different thymes are relatively important compared to some plants that are exploited industrially as a source of essential oils.According to this study, it is found that Thymus satureioides from Ifrane (Morocco), reported by Elouali Lalami, A. and co-workers (Thymus satureioides from Tata (Morocco). Salaheddine El-Bakkal and co-workers (Thymus satureioides from Marrakech (Morocco).The values of the EO yields of -workers  is close-workers  found a Thymus vulgaris, our results are significantly higher than those obtained by Elouali Lalami  by Souad Yakoubi and co-workers  and the Anti-Atlas (Tata region). The GC/MS analyses of the EO of the studied thymes have allowed to make the chromatographic profiles illustrated in By analyzing the main chemical classes of the essential oils studied , we founThymus vulgaris from Khenifra is represented by the chemotype carvacrol (68.8%), γ-Terpinene (11.5%), and p-Cymène (3.9%).Based on the results presented in Thymus satureioides EO from two sites (Tata and Azrou), they have borneol (41.3% and 31.7%), carvacrol (14.6% and 9.8%) as the majority compounds, followed by α-terpineol (8.2 and 7.9), (E)-caryophyllene (3.9 and 5.3%), camphene (5.6% and 4.9%) and linalool (4.9% and 2.3%). On the other hand, thymol presents 14.86% in the EO of Azrou and only traces in that of Tata.As for Thymus zygis EO, we found two different chemotypes; carvacrol and thymol. Thymus zygis EO from Tigrigra and Ain Aghbal are dominated by carvacrol representing respectively 51.7% and 57.5%. While those of Bensmim and Timahdite, are rich in thymol whose values are respectively 47.1% and 42.1%. We note the presence of other compounds with relatively large proportions such as p-cymene and γ-terpinene.In Compared to chemical compositions published in the literature, the chemical profile described in this work shows similarities but also reveals differences. Indeed, our results confirm those of Fachini-Queiroz , ChraibiThymus species in their natural habitat ; shows a strong diversity of the identified compounds both qualitatively and quantitatively. To obtain a statistical description of our sample and to be able to highlight possible chemical variability and identify possible relationships between the abundance of volatile organic compounds and abiotic and geographical factors, we used two of the most common tests of multivariate descriptive statistics including a hierarchical ascending analysis (HCA) and a principal component analysis (PCA).The analysis of the chemical composition of the essential oils of the studied thymes  was performed to divide the sample into groups of homogeneous observations, each group being well differentiated from the others. This analysis will then combine the samples to produce a dendrogram or classification tree .Fig. 4PhThymus satureioides (TSAZ and TSTA), the second group (II) contains a sample of Thymus vulgaris oil (TVHA). Finally, the third group (III) includes the four samples of Thymus zygis .At the level of the dendrogram, we note that the EO of the group (II) includes two samples of EO and are grouped within the same class, so there is an intra-class homogeneity; this is confirmed by the small distance between the two populations, which explains that the two taxa are similar or very close at the level of the chemical profile, for example, species TSAZ presents 91% similarity with species TSTA. On the other hand, groups (III) and (I) are composed of TZAA, TZTIG, TZTIM, TZBE and TVHA. The species of group (III) are heterogeneous concerning class (I), with a significant distance, the species TVHA presents just 17% dissimilarity with the other species .3.2.2Principal Component Analysis (PCA) is a method that simplifies data by studying the relationships between all variables to determine similarities and dissimilarities between individuals .Fig. 5GrTo perform this analysis, we chose the first two factorial axes. The dispersion of thyme species in the plane formed by these two axes concerning the selected variables explains 82.55% of the variability, of which 15.54% on the first axis and 67% on the second axis . This fiWe deduce that the chemical composition of the samples of essential oils of thymes collected in different regions of Morocco presents a heterogeneity; indeed, some samples contain carvacrol as the majority compound, while others contain borneol and/or thymol, p-cymene, and γ-terpinene.Thymus vulgaris of El Hammam of the province of Mrirt which has already been mentioned in some populations of Thymus vulgaris in Morocco , Streptococcus porcinus, Enterococcus faecium which showed resistance to the concentrations of EO studied.The results of antimicrobial activity of different Thymes are shown in Thymus vulgaris, EO which showed very high efficacy and inhibited microbial growth from a very low concentration (MIC = 18.75 μg/ml) for certain strains of Enterobacteriaceae, followed by Thymus zygis and Thymus satureioides species. The EO of the thymes evaluated is very powerful against gram-negative bacteria and in particular, the species Enterobacter cloacae, Citrobacter koseri, Acinetobacter baumannii. This potency of EO against Gram-negative germs is sometimes better than that of the antibiotics tested (vulgaris (carvacrol profile) remains the most effective compared to other chemical profiles against the strains tested and in particular against Gram-positive bacteria. Indeed, at a concentration of<300 μg/ml, this chemical profile showed bactericidal activity on all the strains tested, even for the strain Acinetobacter baumannii and Staphylococcus aureus multidrug-resistant which are species increasingly involved in infections in certain hospital areas such as intensive care units.As can be noted in this discovery, the essential oils of the thyme species tested showed a remarkable antimicrobial effect towards all the microorganisms studied; in particular s tested . In addi3.3.2Thymus zygis species are the most active against candidiasis, followed by the EO of Thymus vulgaris and then the two species of Thymus satureioides, except Candida dubliniensis which is inhibited by a low concentration of Thymus satureioides EO from the commune of Azrou (MIC = 18.75 μg/ml), the yeast of Saccharomyces cerevisiae was found to be very sensitive to EO of Thymus vulgaris species, Thymus zygis from Tigrigra and Bensmim communes, with a moderate to low effect towards the two Thymus satureioides EO tested. The mold evaluated, Aspergillus niger is inhibited with a MIC of 37.5 μg / ml by the EO of Thymus vulgaris, Thymus zygis of the communes of Ain Aghbal and Timahdite. Both species of candidiasis; Candida kyfer and Candida krusei showed some resistance to the EO of the different thymes evaluated, knowing that, even for the standard antifungal “terbinafin”, a higher concentration was needed to inhibit the growth of these two strains in question with a concentration ranging from 25 to 50 μg/ml of terbinafin. In contrast, other fungi are inhibited just by concentrations below 12.5 μg/ml terbinafin , Citrobacter koseri (3DT2151), Candida parapsilosis (Cpa), multidrug-resistant Staphylococcus aureus (2DT2220), Pseudomonas aeruginosa (2DT2138), Acinetobacter baumannii (7DT2404) and Aspergillus niger (AspN). In addition, the phenol carvacrol present in the species Thymus vulgaris (TVHA), Thymus zygis of the commune Ain Aghbal (TZAA), and Thymus zygis of the commune Tigrigra (TZTIG) has a strong positive correlation about the inhibition of the growth of gram-negative bacteria as well as Candida parapsilosis (Cpa), Aspergillus niger (AspN) and Candida tropicalis (Ct). An example of a weak correlation is that of carvacrol with Candida krusei (Ckr) and Candida kyfer (Cky). In addition, it is known that genetic makeup and environmental conditions influence the yield and composition of the volatile oil produced by thyme plants. Correlations between chemotypes polymorphism, sexual polymorphism, and environment have been detected   .In this research, the antimicrobial activity of oils may be due to carvacrol, thymol, borneol, p-cymene and γ-terpinene. According to literature reviews, the above-mentioned bioactive molecules have been found to have significant antimicrobial activities . FurtherThe antimicrobial activity of thyme essential oils is related to its phenol-like components, non-aromatic alcohols, and monoterpene hydrocarbons  since th4The essential oils of Moroccan thymes contain as main components; carvacrol in the EO of Thymus vulgaris from El Hammam of the province of Mrirt, the borneol/carvacrol chemotype for the two Thymus satureioides from the commune of Tata and the commune of Tigrigra, as well as a dominance of the carvacrol/thymol/p-cymene and γ-terpinene chemotype for Thymus zygis subsp. Gracilis. The samples of the evaluated thymes have a strong antimicrobial power with a bactericidal and fungicidal effect against the evaluated microbial strains. Pharmaceutical, food and cosmetic industries need ecological alternatives to drug molecules to treat infectious diseases. Thus, these EOs could be a potential source of alternative antimicrobial agents and could play an important role in the discovery of new products against a wide range of pathogenic microorganisms in the near future.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Clinical evidence logic statements (CELS) are shareable knowledge artifacts in a semistructured “If-Then” format that can be used for clinical decision support systems. This project aimed to assess factors facilitating CELS representation.2 analysis.We described CELS representation of clinical evidence. We assessed factors that facilitate representation, including authoring instruction, evidence structure, and educational level of CELS authors. Five researchers were tasked with representing CELS from published evidence. Represented CELS were compared with the formal representation. After an authoring instruction intervention, the same researchers were asked to represent the same CELS and accuracy was compared with that preintervention using McNemar’s test. Moreover, CELS representation accuracy was compared between evidence that is structured versus semistructured, and between CELS authored by specialty-trained versus nonspecialty-trained researchers, using χP value < .00001). More CELS were assigned for representation with 379 total CELS subsequently included in the analysis (278 structured and 101 semistructured) postintervention. Representing CELS from structured evidence was associated with significantly higher CELS representation accuracy (P = .002), as well as CELS representation by specialty-trained authors (P = .0004).261 CELS were represented from 10 different pieces of published evidence by the researchers pre- and postintervention. CELS representation accuracy significantly increased post-intervention, from 20/261 (8%) to 63/261  requires the evidence to be in a standard shareable format. Clinical Evidence Logic Statements (CELS) are shareable and come in an “If-Then” format. Representing evidence as CELS can be a difficult task and incomplete or incorrect representations may not reflect the true intent of the evidence. In this study, we assessed factors that may facilitate CELS representation, including training sessions, evidence structure, and educational level of CELS authors. First, we asked researchers to represent CELS from narrative evidence. Then they completed training sessions, after which they were asked to represent more CELS. We compared the accuracy of CELS representation: 1) pre- and post-intervention, 2) between structured and semi-structured evidence, and 3) between CELS authored by specialty-trained vs. non-specialty-trained researchers. Accuracy of CELS representation significantly increased post-intervention. CELS represented from structured evidence had a higher representation accuracy compared to semi-structured evidence. Similarly, specialty-trained authors had higher accuracy when representing structured evidence. Training sessions with explicit authoring instructions significantly improved CELS representation, although the task remains difficult with many CELS remaining inaccurately represented compared to those authored by knowledge representation experts with experience in representing evidence for CDS. Clinical evidence or appropriate use criteria are authored into several layers of representation before they are incorporated into CDS, which are referred to as CDS artifacts. The 4-layered framework for representation includes a model for an increasingly structured representation—unstructured , semistructured , structured , and executable .In this study, we assessed factors that facilitate CELS representation, including: (1) an educational intervention targeted towards CELS authors, (2) the structure of clinical evidence (structured vs semistructured), and (3) the educational level of CELS authors . A secondary objective evaluated the clinical significance of CELS representation accuracy.This study was exempt from Institutional Review Board review. Imaging-related decision rules were represented from 10 randomly selected guidelines (a.k.a. appropriate use criteria or evidence) from the HLE, an existing publicly available library of evidence.The primary unit of analysis was a decision rule—a unit of evidence, defined as an assertion regarding the appropriateness of utilizing a diagnostic imaging procedure for certain indications and contraindications, taken from a published recommendation, guideline, systematic review, or clinical decision rule.IF “pregnant” AND “suspected PE” AND “signs and symptoms of DVT” THEN “Bilateral Venous CUS”. Every phrase within quotation marks  is an atom, therefore there are 4 atoms in this CELS example.We illustrate with a portion of one guideline on managing PE in pregnant women,,,In this study, we investigated whether an educational intervention can improve the accuracy of CELS authoring or representation. Preintervention, authors were only provided with copies of publications on CELS and knowledge content in the HLE that they then reviewed prior to representing CELS.The general content of the first session included descriptions and examples of guidelines, recommendations, and evidence. Other topics covered grading of strength of evidence,,Guidelines included in the HLE can be structured or algorithm-based evidence in the form of flowcharts, decision tables, or imaging procedure-based tables.Four CELS authors were medical doctors, with 2 of them having additional specialty training in radiology. The fifth CELS author was a senior Harvard Medical School medical student. None of these authors had previous experience in knowledge representation of evidence. The CELS in the HLE were represented by 2 expert scientists each with more than 5 years of experience in CELS representation. One of them has specialty training in Internal Medicine and has more than 10 years of experience in knowledge representation of clinical evidence that has been implemented in CDS.In order to assess whether CELS representation accuracy was clinically significant in addressing the intent of recommendations, we evaluated clinicians’ perception of the intent of represented CELS compared with the actual text guidelines. Two expert clinicians with at least 20 years of combined clinical experience reviewed 40 represented CELS (20 CELS each from structured evidence and semistructured evidence), calculated based on 80% power and 95% confidence level to detect a 30% difference from a 76% accuracy of representing atoms. Kappa agreement was performed on 10 CELS. Each clinician was asked to answer yes/no to these 4 questionsThe primary study outcome was the proportion of correct CELS representation based on the formal representation in the HLE. The numerator of this measure is the number of correctly represented CELS and the denominator is the total number of CELS represented. For evaluation of CELS representation, correctly represented CELS are those that matched the formal representation completely and accurately. We similarly measured the proportion of correctly represented atoms within CELS, with the numerator being the number of correctly represented atoms and the denominator being the total number of atoms represented for all the atoms in the CELS.We compared the CELS representation accuracy before and after the educational intervention for 261 decision rules from 6 guidelines. McNemar’s test was used to assess statistical significance in a paired analysis. Similarly, atoms representation accuracy was also measured and statistically compared using McNemar’s test.P value. A P value < .05 was considered significant.To analyze the impact of having structured versus semistructured pieces of evidence on the accuracy of CELS representation as well as the accuracy of representing atoms, 4 additional guidelines were represented with 118 additional decision rules, resulting in 379 total CELS that were represented. CELS and atoms representation accuracy was compared between structured and semistructured evidence using chi-square analysis. The same comparison was applied between radiologist and nonradiologist CELS authors. Chi-square statistical analysis was also used to calculate the Finally, we used percentage and kappa agreement to measure interannotator agreement between the 2 expert reviewers. Fisher’s exact test was used to compare the proportion of “yes” answers to Question 4 for CELS that were similar to the gold standard  compared with those that were not.P < .00001, McNemar) and 1362/2208 (62%) to 1633/2208 (74%) for atom representation  to 63/261 (24%) for CELS representation (P = .002) and atom representation  compared with semistructured evidence (11%) and the difference was statistically significant for both CELS (P = .0004); but nonspecialty-trained authors had a higher percentage of correctly represented atoms , but not in the THEN clause . CELS for structured evidence are more similar to the gold standard  and more significantly represent the same clinical intent . Interannotator agreement was 80% with a kappa statistic of 0.55, indicating moderate agreement.P = .0006). However, 31% of authored CELS that were not similar to the gold standard were assessed by experts as having similar clinical intent to the actual text guidelines.Finally, we assessed the number of “yes” answers for each of the 4 questions for structured versus semistructured evidence and showed that there is significant dissimilarity in the IF clause /chiropractic evaluation in preceding 60 days” THEN “CT cervical spine without contrast”. The answers to Questions 1–4 are:Does the represented CELS target the same patient presentation ? NO—The authored CELS adds a stipulation about PT/chiropractic evaluation.Is the recommendation similar between the represented CELS and the gold standard ? YES—Both CELS recommend CT cervical spine without contrast.Is the represented CELS similar to the gold standard? NO—See answer to Question 1. Question 3 is logically equivalent to Question 1 AND Question 2.Does the represented CELS reflect the same clinical intent? YES—Although there is a stipulation about PT/chiropractic evaluation, experts perceive that it does not change the clinical intent of the recommendation.In this example, the authored CELS further constrains the cohort of patients with “Adequate conservative treatment with no improvement” by adding “Claim for PT/chiropractic evaluation in preceding 60 days.” The latter constraint is a very specific instance of the former. Also, information about the latter constraint requires access to various payers’ billing data (as such services may have been performed within or outside the institution deploying this specific CELS) making the CELS impractical for implementation.,An educational intervention with authoring instructions significantly improved CELS representation with a 3-fold increase in accuracy, from 8% to 24%. Authoring textual guidelines, recommendations and evidence is a difficult task.Two other factors significantly facilitated accurately authoring CELS and atoms. We demonstrated that structured evidence is more likely to be represented accurately, compared with semistructured guidelines.adequate conservative treatment without improvement” versus “physical therapy/chiropractic evaluation in preceding 60 days with no improvement OR follow-up evaluation and management in preceding 28–60 days with no improvement.” The second representation is more detailed and has 2 atoms instead of one. Authors with more relevant experience may provide more detailed as well as more granular representations. Other examples of inaccurate artifact representations are shown in Several reasons have been proposed for variations in artifact representation. These include (1) differences in the representation of detail ; (2) differences in the organization of medical concepts; and (3) differences in encoding temporal information .Nevertheless, a goal of knowledge representation is to capture the clinical intent of evidence recommendations.This study did have a limitation; although clinical experts assessed the similarity of CELS to textual evidence and the clinical intent of the evidence, we did not determine impact on use as CDS artifacts during an actual implementation.Authoring instructions with an educational intervention significantly improved CELS representation with a 3-fold increase in accuracy. CELS represented from structured evidence had higher representation accuracy compared with semistructured evidence. Similarly, specialty-trained authors had higher accuracy when representing structured evidence. However, CELS representation remains a challenging task with only 24% of CELS represented accurately.All coauthors contributed to the conception and design of this project. RL, ME, LC, IG, AL, AZ, and RK specifically contributed to data acquisition and analysis. All coauthors contributed significant intellectual content during the article preparation, approved the final version, and accept accountability for the overall integrity of the research process and the article.