Objective monitoring and assessment of human motor behavior can improve the diagnosis and management of several medical conditions. Over the past decade, significant advances have been made in the use of wearable technology for continuously monitoring human motor behavior in free-living conditions. However, wearable technology remains ill-suited for applications which require monitoring and interpretation of complex motor behaviors . Recent advances in computer vision and deep learning have opened up new possibilities for extracting information from video recordings. In this paper, we present a hierarchical vision-based behavior phenotyping method for classification of basic human actions in video recordings performed using a single RGB camera. Our method addresses challenges associated with tracking multiple human actors and classification of actions in videos recorded in changing environments with different fields of view. We implement a cascaded pose tracker that uses temporal relationships between detections for short-term tracking and appearance based tracklet fusion for long-term tracking. Furthermore, for action classification, we use pose evolution maps derived from the cascaded pose tracker as low-dimensional and interpretable representations of the movement sequences for training a convolutional neural network. The cascaded pose tracker achieves an average accuracy of 88% in tracking the target human actor in our video recordings, and overall system achieves average test accuracy of 84% for target-specific action classification in untrimmed video recordings. Clinical assessment of human motor behavior plays an important role in the diagnosis and management of medical conditions like Parkinson’s Disease (PD) . HoweverRecently, artificial intelligence (AI) assisted classification of human behavior using computer vision has received newfound attention among researchers in machine learning and pattern recognition communities for applications spanning from automatic recognition of daily life activities in smart homes to monitoring the health and safety of elderly and patients with mobility disorders in their homes/hospitals ,10,11,12Automated assessment of human behavior in multi-person video  requires the tracking and classification of a sequence of actions performed by a target . Therefore, accurate temporal tracking of the target is an essential requirement for this application, along with robust feature extraction that can be used for classifying human behaviors at different levels of complexity. In this paper, we present a hierarchical target-specific action classification method, which is illustrated as a block diagram in Assigning a single action label to a multi-person video clip dilutes the specificity of information and makes it less meaningful. For many real-world applications such as video-based assessment of human behavior, there is a need for person-centric action recognition, which assigns an action label to each person in a multi-person video clip. One of the challenges in person-centric action recognition is robust tracking of the target in long-term videos. Tracking is challenging because there are many sources of uncertainty, such as clutter, occlusions, target interactions, and camera motion. However, most of the research studies on human activity classification have typically dealt with videos with a single human actor or video clips with ground-truth tracking provided , with thBeside the importance of dealing with non-target objects in providing a well-performing real-world human action recognition system, creating robust and discriminating feature representations for each video action clip plays an important role in detecting different human activities . Most ofIn general, convolutional neural network (CNN) based action recognition approaches can be divided into three different categories based on their underlying architecture: (1) spatio-temporal convolutions , (2) recurrent neural networks, and (3) two stream convolutional networks. The benefit of multi-stream networks is that different modalities can be aggregated in the network to improve performance of the final action classification task. In this paper, we addressed the problem of person-centric action recognition by long-term tracking of the target human actor. In addition, our method provides a novel pose evolution representation of the target human actor rather than the common spatio-temporal features extracted from raw video frames to the classification network. It is worth mentioning that our pose-based action recognition stream can be used to augment the current multi-stream action classification networks.The rest of the paper is organized as follows. In Diverging from the common approach of learning spatio-temporal features from videos for action classification, pose-based action classification methods have shown promising results by providing a compact representation of human pose evolution in videos ,27,28,29The primary task in pose-based action classification in untrimmed videos is locating the target. This requires a robust estimation and tracking of human body poses by addressing the challenges associated with long-term videos recorded for assessment of human motor behavior. These challenges include partial to complete occlusion, change of scene, and camera motion. In this section, we propose a cascaded multi-person pose tracking method using both time and appearance features, which will be used in later steps to generate pose evolution feature representations for action classification.classification head responsible for person detection and bounding box regression, and a keypoint head for estimating the human body joints defined as a human pose in each detected bounding box. The outputs of this pose estimation network are seventeen keypoints associated with various body joints and a bounding box surrounding each person.In order to extract human pose information in each video frame along with their associated bounding boxes as the first step in our system, we used a 2D version of the state-of-the-art human pose estimation method proposed in . The preIn many real-world settings where a person has to be tracked across videos recorded from different cameras located in different environments, a single tracker is unable to track the person throughout the video and all of them fail when the target leaves one environment and appears into another environment or is occluded from the camera view and then reappears in the camera’s field of view . In ordeIn order to continuously track the pose of the target  in video recordings, we propose a two-step procedure based on the estimated bounding boxes and keypoints provided by the pose estimation network in Given the detected bounding boxes for each person in the video, we link the bounding boxes that belong to the same identity in time to create pose tracklets. Assuming that there is no abrupt movement in the video, tracklets are generated by solving a data association problem with similarity measurement defined as the intersection over union between the currently detected bounding boxes and the bounding boxes from the previous frame. Like ,43, we ft. Affinity metric, Given the large number of tracklets generated from the previous stage , we fuse tracklets that belong to the same identity to generate a single long-term track for the target. As illustrated in timation ,35. The After locating the target, providing a compact yet discriminative pose evolution feature representation for each action clip plays an essential role in recognizing different actions. To achieve this, we first provide a compact spatio-temporal representation of the target’s pose evolution in By using pose of the target for each frame of the video clip provided by the pose tracking stage, we create a fixed-size pose evolution representation by temporally aggregating these pose maps. Pose tracking in preceding stages gives us locations of the body joints of the target  in each frame of the video clip. We first generate joint heatmaps from given keypoint positions by locating a Gaussian kernel around each keypoint. These heatmaps are gray scale images showing the probability of the estimated location for each body joint. The pose evolution representations are created based on these joint heatmaps.t is transformed into a C-channel color image of i of the target in a given frame number t. j evaluated at time t. i. The final pose evolution representation, As illustrated in Equation , this trT is divided into t that sits in kth interval which In order to calculate the time encoding function for a C-channel pose evolution representation, the video clip time length We trained a CNN for classifying different actions using the pose evolution representations. Since pose evolution representations are very sparse and have no contextual information of the raw video frames, the network does not need to be very deep or pre-trained to be able to classify actions. We used the network architecture illustrated in The action classification network includes two blocks of convolutional layers, a global average pooling layer, and a fully connected layer with a Softmax loss function as the classification layer. Each block contains two convolution layers with filter sizes of To evaluate the performance of the proposed approach, we used a real-world dataset collected in a neurology clinic. We provide an overview of the dataset in Our dataset consists of video recordings of 35 patients with Parkinson’s disease  or OFF (before medication intake) state for the first visit, and underwent the second visit in the other state. During each study visit, patients performed a battery of motor tasks including activities of daily living  and a standard battery of clinical motor assessments from the Movement Disorder Society’s Unified Parkinson’s Disease Rating Scale (MDS-UPDRS)  administBehaviors of interest were identified within each video using structured definitions and, their start and end times annotated using human raters as described elsewhere . BrieflyGiven that video recordings involved the presence of multiple people, we first detected all human actors along with their associated keypoints in each video frame using the multi-person pose estimation method described in In order to recognize activities of the target, we first locate and track the subject  in each frame. This was accomplished by using the hierarchical tracking method described in To evaluate the performance of our target tracking method, we first manually annotated all tracklets generated by short-term tracking and then calculated accuracy of the long-term tracking method with respect to the manually generated ground-truth. Accuracy is calculated by treating the long-term tracker as a binary classifier as it excludes non-patient tracklets and fuses tracklets belonging to the target to find a single final patient track for the entire video recording. Considering patient tracklets as the positive class and non-patient tracklets as the negative class, our tracker achieved an average classification accuracy of 88% across 70 videos on this dataset.In the last stage of our multi-stage target-specific action classification system, we trained a CNN to recognize the following five actions of interest: sitting, standing, walking, sitting-to-standing, and standing-to-sitting. After applying the target pose tracking system illustrated in To prepare input data for the action classification network, we transformed each action clip into a pose evolution representation as described in We used Real-world assessment of motor behaviour can provide valuable clinical insights for diagnosis, prognosis and prevention of disorders ranging from psychiatry to neurology ,50. In tThe second aspect of our work focused on classification of activities of daily living. Activities like sitting, standing, sit-to-stand, stand-to-sit and walking are basic elements of most of the tasks that we perform during daily life. To train the activity classification model, we used pose evolution representations to capture both temporal and spatial features associated with these activities. While this model achieved a classification accuracy of 84%, as we can see in Another source of error which impacts overall performance is the error propagated from pose tracking (~12%) and pose estimation stages. Pose estimation error can be tolerated to some degree by aggregating the colorized joint heatmaps in the pose evolution feature representation. However, since the output of the pose tracking is directly used for generating pose evolution maps, any error in tracking the patient throughout the video would negatively impact the action classification performance. One approach for tolerating the error from pose tracking stage is to incorporate raw RGB frames as the second stream of information for action classification and using attention maps based on the tracking outcome rather than excluding non-target persons from the input representations.Vision-based monitoring tools have the distinct advantage of being transparent to the target, which would help with issues of compliance associated with the use of wearable devices. Also, unlike wearable devices, vision-based approaches can capture contextual information, which is necessary for understanding behavior at higher level. However, this also comes at an increased risk to privacy for the target as well as other people in the environment. The proposed approach can potentially mitigate this concern by limiting monitoring to the target  and transforming data at the source into sparse feature maps .https://github.com/brezaei/PoseTrack_ActionClassification).In this paper, we have presented an AI-assisted method for automatic assessment of human motor behavior from video recorded using a single RGB camera. Results demonstrate that the multi-stage method, which includes pose estimation, target tracking and action classification, provides an accurate target-specific classification of activities in the presence of other human actors and is robust to changing environments. The work presented herein focused on the classification of basic postures  and transitions (sitting-to-standing and standing-to-sitting), which commonly occur during the performance of many daily activities and are relevant to understanding the impact of diseases like Parkinson’s disease and stroke on the functional ability of patients. This has laid the foundation for future research efforts that will be directed towards detecting and quantifying clinically meaningful information like detection of emergency events  and assessment of symptom severity  in patients with various mobility limiting conditions. The proposed method is mainly intended for offline processing of video recording. To provide real-time detection of serious events , future research efforts should focus on enabling real-time target tracking and action classification by developing more computationally efficient approaches. In addition, achieving high-resolution temporal localization of actions will be necessary to ensure accurate assessment of clinical events of interest  for certain medical applications. Lastly, the code and models developed during this work are being made available for the benefit of the broader research community (


This study qualitatively identified the organizational identity of a nursing organization and determined the state of organizational identification of staff in hospital wards.Cross‐sectional descriptive survey study.Interviews were conducted using interview guides; a qualitative inductive analysis was performed for the three attributes of organizational identity . The study included three head nurses working in different facilities and three teams comprising three nurses each, who worked under each of the head nurses .Centrality comprised two subcategories: “ward work attributes” and “ward care attributes”. Clear centrality originating from a head nurse showed a strong influence on organizational culture in a hospital ward. As young staff is identified by distinctiveness in wards, it is important to clarify distinctiveness. When centrality and distinctiveness were not clear, enduring was weak. Individual interviews were conducted using an interview guide Appendix  in space3.3A verbatim of the interviews was created from the recorded data, and the portions that related to organizational identity were extracted. Those items similar to descriptions were encoded, and the head nurses and nurses performed a comparative analysis of similarities and differences in the codes using a continuous comparison method. Codes determined to be similar were compiled, placed into subcategories and systematized into the categories of central, enduring or distinctive, following Albert and Whetten . FurtherTo collect homogeneous data, three interviewers carefully loaded the interview guide and shared the contents before starting the interview. Interviews took place in environments where participants were able to speak freely, and before all interviews, the anonymity of the survey results and the abstention on the way were guaranteed. Three authors participated in the analysis of the text, discussing themes and subthemes, thereby increasing dependability. To ensure the credibility of the analysis, the authors continuously discussed until the end of the analysis.3.4Prior to conducting this study, the researchers received approval from the ethics committee for “research on human subjects” at our University, with which the authors are affiliated. In obtaining cooperation from nursing managers and head nurses for their organizations, the researchers presented a research plan and ethical considerations on paper and made introductions to those individuals providing informal consent.44.1All head nurses were in their 40s, and each had worked as a nurse for about 25 years. Nursing staff members were in their 20s–40s and had worked as nurses for 6–25 years. They had worked in their current ward for 1–7 years ” and “a ward where nurses have implemented triage work”. To fulfil these attributes, ward staff are actively encouraged to acquire credentials related to emergency work and lectures are held to communicate information. Centrality attributes were extracted from two primary staff members, such as “a ward with a consistent sense of urgency for responding to emergencies and a sense of preparedness for acute changes” and “a ward with a desire for nursing abilities to respond to crisis situations”. These expressions may be somewhat different, but in content, they are similar to those of the head nurse. Centrality attributes were not extracted from younger staff. Regarding distinctiveness, ward staff viewed their wards as “a place where they could express themselves” and “a place where they stimulated each other through their individual goals”. This perspective was the same for head nurses and ward staff. Regarding the attribute of enduring, head nurses aimed at transferring the skills they had acquired to staff members at the same time as actively working for continuity of cognition. The younger staff members, who received this information, saw this effort to provide them with continuity and “opened up to junior staff members about any confusion they had and proactively communicated with and brought in other staff members by asking for help”.4.4.2Regarding centrality, the head nurse stated the characteristics of nurses that stem from patient attributes; for example, “it is difficult to convey information on nursing because patients have a high degree of independence and are hospitalized for surgeries and tests” and “in this ward, nurses need to have the perspective of working toward a smooth surgery and then spend the rest of the day after surgery without feeling any uneasiness”. Among other means, the head nurse “creates a path by the committee” as a way of promoting this. One of the three hospital staff members said, “this ward has many independent patients as well as patients who won't be having surgery”. These were somewhat similar to the comments of the head nurse, although the other staff members at this hospital did not remark concerning centrality. Regarding “distinctiveness”, the head nurse said each nurse submits personal goals and conducts a self‐assessment and did not say anything that was different from the other wards. This mid‐level staff member was critical of the policies and methods of the head nurse. The staff member had a strong relationship with staff colleagues and had worked in that ward longer than the head nurse and, therefore, had abundant information about small efforts made by younger staff. The staff member was aware of the distinctive environment of the ward that had been handed down from the previous head nurse.Regarding “enduring” attributes, the head nurse made no proactive efforts and followed what the previous head nurse had done. Ward staff members discussed activities for ensuring continuity of knowledge, such as “staff members pass along information in study groups and we have lively Q&A sessions” and “the atmosphere allows for voluntary participation in study groups if asked”.4.4.3The head nurse in this ward stated the attribute of time management regarding centrality and gave examples of efforts to quantify time management and be careful about work efficiency to manage time as ways of promoting centrality. Two of the three staff members did not say anything about centrality, although one mid‐level staff member mentioned as a nursing attribute gained from patients in the ward that “patients are elderly and have lower cognitive and awareness levels, which makes much of their communication with nurses very poor” and “in this ward, we are very busy with all the assistance we provide for bowel movements and urination”. Regarding distinctiveness, the head nurse mentioned activities for rewarding the staff's careful time management. Ward staff members mentioned the strong impact of policies created by the head nurse, such as “team members talk to each other and try to finish their work in the allotted time”, and “work is done efficiently, and everyone goes home on time”. Regarding the enduring attribute, the head nurse expressed thoughts about the ideals of establishing systems conceived and executed by nurses and having leaders make decisions and generate results. However, she gave no specific examples of actual practices. Ward staff members mentioned examples of the enduring attribute such as “when I joined the ward, everyone was nice enough to teach me when I asked, so I want to do the same for the new staff” and “my seniors told me to do things a certain way and so I will do the same”.4.5In examining the comments of the nine individual ward staff members, the researchers found quantitative differences in their comments according to age. No such differences were seen for “distinctive” and “enduring”. Moreover, where the policies and thinking of the head nurses were aligned with the thinking of the ward staff, the comments of the nurses who worked in the same ward tended to be relatively similar in quality and quantity to the comments of the head nurses. However, two mid‐level staff members who did not agree with the policies of the head nurse made comments that differed qualitatively from those of the head nurse and tended to quantitatively emphasize different points.55.15.1.1The organizational identities of the three head nurses were evaluated in reference to the hospitals' visions, nursing principles and basic policies. The results revealed that the extracted organizational identities identified from each head nurse were influenced by the organizational visions and nursing principles of each hospital. The core traits of the organizational identity extracted from the head nurse of Ward A were consistent with the organizational visions of the hospital. The organizational visions and basic policies of Hospital A (advocating safe provision of highly sophisticated medicine and acute‐phase treatment) were congruous with the duties performed by Ward A (which is an intensive care unit). Consequently, the environment at Ward A was conducive to forming an organizational identity that was consistent with the hospital and nursing department. However, the head nurse of Ward C had visions that differed from the visions of the hospital and nursing department, with core traits peculiar to the individual being observed. While Hospital C as an organization advocates providing medical services contributing to the safe living of people in the community, the primary policy of the nursing department was the innovation in and the improvement of medicine, welfare and nursing. This suggests that the core traits of the head nurse of Ward C were shaped by the basic policy of the nursing department. The basic policies of the nursing department were originally intended to achieve the organizational vision of the hospital. However, in this case the head nurse appeared to have adopted only the basic policy, which was detached from the organizational vision. The organizational vision of the nursing department of Hospital B was more abstract and conceptual than that of the other two hospitals, with no basic policy presented for the nursing department. The fact that the head nurse of Ward B exhibited ambiguous core traits for the organizational identity could be attributed to the abstract and hard‐to‐understand nature of the nursing department's initial vision.These results suggest that head nurses need to fully comprehend the organizational visions and nursing principles of their hospital to ensure that the identities of their ward are consistent with these visions and principles. Moreover, to ensure that the entire organization shares and functions towards the same goal, it is essential for the organization to educate the staff members on mutually understandable organizational visions, nursing principles and basic policies.5.1.2Takahashi and Yoshimura  examinedThe two head nurses responsible for the general wards had characteristics of centrality that are of completely differing qualities, despite not having as many differences in work as the HCU. Centrality is a fundamental quality of an organization and the foundation of identity. Differences seen in the two general wards examined in this study were similar to those found in Albert and Whetten . The fun5.2Head nurses establish the direction of ward activities that embody centrality, and this direction manifests as distinctiveness in the ward. Ward staff members reflect this same distinctiveness. For example, wards with head nurses who extracted the central attribute of time management are careful in managing time and ward staff members approach this practice by viewing the following actions as distinctive: “talking to other team members and making sure work is done on time” and “working efficiently and everyone going home at the appointed time”. However, the ward with a head nurse who mentioned nursing skills required for emergency work in an HCU as an attribute of centrality had the distinctive attribute of “a ward with staff members who set challenging goals for training and obtaining credentials, such as academic conferences and study groups; take on challenges; and move forward in their efforts”. Multiple staff members had actually earned the credentials required for emergency work. It was found that the organizational identities for these types of head nurses lay the foundation for centrality and are manifested through the distinctiveness of the ward. Then, through enduring, these attributes are passed on to ward staff members. Rousseau  divided Meanwhile, the head surgical nurse whose centrality was unclear did not appear to do much to strengthen centrality or to help it continue. When centrality is vague, the direction a head nurse should take or what should continue to be done is also vague. There are three potential reasons for this. One is that a new head nurse may be in the process of forming an organizational identity and the organizational vision and nursing principle were conceptual and abstract. The final point is that in a general ward, it may be difficult to find signs of centrality. However, we may surmise that the reason such a ward has maintained a good culture is due to the foundation laid by the previous head nurse and that the new head nurse makes no changes out of respect for that. Takao  showed t5.3Concerning the organizational identities of ward staff, differences in centrality can be seen in the work experience of nurses and the organizational identities were not extracted from younger staff in the current study. Corley and Gioia  surveyed5.4Differences in values exist between the head nurses and certain mid‐level staff in two wards, which was reflected in differences regarding how each ward viewed centrality. In the mixed ward, a change in the head nurse caused friction between mid‐level staff and the new head nurse. In the surgery ward, mid‐level staff was hired from another hospital, which led to friction because the head nurse at their previous facility had different values than their current head nurse. Results of the present study showed that a ward may have multiple organizational identities or that friction may occur among certain staff members when a change in the head nurse or the transfer of staff occurs. Sato  observed5.5The results of this study show that creating a stable organizational culture requires the head nurse to have a clear awareness of ward centrality and to communicate that awareness to staff. In comparing the two general wards, it was found that the influence of centrality disseminated by the head nurse was extraordinarily large, which resulted in the creation of a completely different organizational culture in the wards. Establishing a ward environment with a long‐term outlook requires a foundation that is not disrupted by the transfer of head nurses. This further necessitates that centrality be based on hospital nursing principles rather than on the individual values of the head nurse. Moreover, our results underscore how crucial it is that hospital organizations present the importance of presenting organizational visions and nursing principles that are mutually understandable to all staff members. In addition, the function of the clinic or ward has an impact on the ease with which the staff understands centrality. In general wards, with diverse patient needs, there is a higher level of ambiguity in roles compared with an HCU or ICU, surgery rooms, psychiatric wards, paediatric wards and obstetrics wards, with their special functions (Takahashi & Yoshimura, 5.6A limitation of this study is the small number of participants, with three wards that had different personnel, ward functions and nursing structures. An examination of organizational identity in these three wards is important but clarifying the overall picture will require further comparison of wards in different departments and multiple wards in the same facility, as well as further validation of the process of organizational identity formation among head nurses. Another limitation was the fact that we did not collect data on turnover rates at the surveyed hospitals and wards. Turnover is a critical piece of information when assessing organizational identity, environment and workplace relationships, a factor that needs to be explored in future studies. Further, this study was conducted in a limited region of Japan. Organizational identities and identification are likely to be affected by the underlying culture. Healee and Inada  examinedThere are no conflicts of interest to declare.


PurposeExamine the factors improving performance on national medical licensing board examinations.RationaleAccreditation Council for Graduate Medical Education (ACGME) accredited residency programs report the United States Medical Licensing Examination (USMLE) Step 1 and Comprehensive Osteopathic Licensing Examination-USA (COMLEX-USA) Level 1 scores as the most important criteria in selecting candidates to interview.Hypotheses(1) Certain resources are superior for exam preparation.(2) Certain practice tests better assess exam preparedness.(3) USMLE performance will correlate with the COMLEX-USA.MethodsOne-hundred and two (102) medical students were surveyed regarding preparation for and performance on COMLEX-USA Level 1 and USMLE Step 1.ResultsUSMLE-specific question banks were positively correlated with performance on COMLEX-USA Level 1 and USMLE Step 1 while COMLEX-specific question banks showed no correlation. National Board of Medical Examiners (NBME) Comprehensive Basic Science Self Assessment (CBSSA) and National Board of Osteopathic Medical Examiners (NBOME) Comprehensive Osteopathic Medical Self-Assessment Examination (COMSAE) practice examinations were positively correlated with performance on the USMLE Step 1 and the COMLEX-USA Level 1. Scores on USMLE Step 1 and COMLEX-USA Level 1 were highly correlated. Students who took USMLE Step 1 performed better on COMLEX-USA Level 1 than those who did not.ConclusionCOMLEX-specific resources may not adequately prepare students for COMLEX-USA Level 1. Students studying for COMLEX-USA Level 1 may benefit by preparing for USMLE Step 1. Each year, both the number of U.S. medical schools and their respective class sizes continue to grow, dramatically outpacing the expansion and related availability of postgraduate year (PGY)-1 medical residency positions . In the This trend of continued growth in the domestic medical graduate pool has served as a catalyst for the increasing competition that all applicants face in attempting to match into a residency program. The literature is replete with surveys and analyses of criteria that are predictive of success in both interviewing and matching at prospective residency programs. Consistent throughout much of this material is the conclusion that performance on the first component of national medical licensing board examinations - either United States Medical Licensing Examination (USMLE) Step 1, published by the National Board of Medical Examiners (NBME), for US-MD students, international medical graduates, and osteopathic medical students, or the Comprehensive Osteopathic Medical Licensing Examination of the United States (COMLEX-USA) Level 1, published by the National Board of Osteopathic Medical Examiners (NBOME) for osteopathic medical students - is a standardized comparison tool that proves vital in both the screening and ranking of candidates for residency positions in the United States -5. Addit, formative testing) as a more efficacious manner in which to encode long-term memory when compared to elaborative processes (often consisting of passive repetition). While traditional schools of thought have presupposed that the retrieval of information such as that completed during testing scenarios only served to assess previously acquired knowledge, recent work suggests that retrieval practice can serve as a mnemonic enhancer and generate greater long-term retention than would elaboration [In consideration of this necessity to excel in medical licensing board examinations, medical students are inclined to be rigorous, persistent, and strategic in their approach to preparation. Recent research in the fields of learning and cognition has generated evidence to better inform students and educators about the methodology most likely to lead to success in taking high-stakes examinations. In particular, a great deal of work has been conducted on assessing the use of retrieval practice  and performance on licensing examinations, in addition to evaluating retrieval practice efficacy amongst various commercial preparation products that were marketed to target preparation for either the USMLE or the COMLEX-USA. Finally, we explored the independent correlation between performance on the USMLE and COMLEX-USA examinations.The aim of the present study was to examine several factors in national medical licensing board examination preparation that have the potential to directly influence performance outcomes. We sought to evaluate the association between the use of retrieval practice examination preparation methods  students elected to complete the authors’ survey. This population of students both prepared and sat for the COMLEX-USA Level 1 while 58 also both prepared and sat for the USMLE Step 1 during the 2016-2017 academic year. Survey participation was solicited via e-mail, with voluntary participation. The survey was open during the months of July and August of 2017. Responses were de-identified and no additional demographic information was collected in order to maintain the anonymity of the participants.The survey was composed of five sections. Section 1 of the survey sought to elucidate the month the student began preparation, question banks used, question mode , question organization (randomized or organ system-specific), number of questions completed in each question bank, and number of questions repeated in each question bank. Section 2 was composed of questions pertaining to the tools used for study plan organization, flashcard use , video resource use , and book use . Section 3 consisted of questions about Comprehensive Osteopathic Self-Assessment Examinations (COMSAE) Forms A-E (date taken and corresponding score) and COMLEX-USA Level 1 . The final question of this section inquired as to whether or not the student prepared for USMLE Step 1. If this question was answered in the affirmative, participants were directed to Section 4 while those participants answering in the negative were directed to Section 5. Section 4 was composed of questions regarding NBME Comprehensive Basic Science Self-Assessments (CBSSA) 12-13 and 15-19 (date taken and score) and USMLE Step 1 . Section 5 consisted of inquiries into residency specialty interest and how well the college curriculum prepared students for COMLEX-USA Level 1 .Linear regression was used to evaluate the relationships of continuous variables . Survey responses were also analyzed using unpaired t-tests comparing parametric variables. Statistical analysis was performed using the R Statistical Programming Package . This stUSMLE and COMLEX-USA relationshipFifty-eight students (57% of participants) reported taking both USMLE Step 1 and the COMLEX-USA Level 1. Performance outcomes for these examinations were strongly correlated (r = 0.78) and can be found in Figure Question banksThe total number of questions that students completed was positively correlated with performance on the USMLE Step 1 (r = 0.30) and COMLEX-USA Level 1 (r = 0.29). The number of questions answered in banks marketed for preparation for the USMLE, such as UWorld, USMLE Rx, and Kaplan USMLE, was positively correlated with performance on both USMLE Step 1 (r = 0.38) and COMLEX-USA Level 1 (r = 0.42). The number of questions answered in banks marketed toward preparation for the COMLEX, such as Truelearn COMBANK (question bank for COMLEX-USA), COMQUEST (question bank for COMLEX-USA), and Kaplan COMLEX, was poorly related to performance on the USMLE Step 1 (r = -0.03) and negatively correlated with performance on COMLEX-USA Level 1 (r = -0.22) . Students who completed Truelearn’s COMBANK in timed mode did better on COMLEX-USA Level 1 than those using it in tutor mode  (Table Practice examinationsNBME CBSSA practice tests were consistently positively correlated with performance outcomes of USMLE Step 1 r = 0.53-0.80) and COMLEX-USA Level 1 (r = 0.55-0.73). Students’ highest performing NBME CBSSA was correlated with both the USMLE Step 1 (r = 0.82) and COMLEX-USA Level 1 scores (r = 0.74). Students’ performance on a COMSAE taken nearest to their USMLE Step 1 and COMLEX-USA Level 1 examination was positively correlated with the USMLE Step 1 (r = 0.41) and COMLEX-USA Level 1 score (r = 0.61)  was the only resource whose total completion was related to higher scores on the COMLEX-USA . Total completion of video resources was not related to performance outcomes on the USMLE Step 1  are required to take USMLE Step 1 while all osteopathic medical students are required to take COMLEX-USA Level 1, with the option to also take USMLE Step 1 in order to apply for medical licensure in the United States. Certain medical residency programs require that USMLE Step 1 and occasionally USMLE Step 2 CK be taken by osteopathic medical student applicants, while others will accept COMLEX-USA Level 1 and 2CE scores alone. This had led to an interest in the correlation between scores on the two examinations. A previous small-scale study determined the Pearson correlation coefficient between COMLEX-USA Level 1 and USMLE Step 1 scores to be 0.83 (p<0.001) . Our stuSeveral third-party companies offer practice questions for medical student board examination studying. The present study assessed which question banks students used, the number of questions completed, and the outcome of their performance on both USMLE Step 1 and COMLEX-USA Level 1. Consistent with our expectations, it was found that the number of practice questions students completed correlated positively with scores on both USMLE Step 1 and COMLEX-USA Level 1. Additionally, these results demonstrated that students who used question banks in timed mode performed better than students who completed these question banks in tutor mode or timed-tutor mode. It is worth noting that in this study, questions banks marketed toward preparation for USMLE Step 1 had a modestly stronger correlation with COMLEX-USA Level 1 scores than with USMLE Step 1 scores . Interestingly, the data collected in this study demonstrated a negative correlation between the number of questions completed in banks marketed toward preparation for the COMLEX-USA Level 1 (r = -0.22) and COMLEX-USA Level 1 scores. This finding was particularly noteworthy given that some products, such as Truelearn COMBANK, advertise the applicability of its product to COMLEX-USA Level 1 in much of their marketing materials and student testimonials -16. OstePractice examinations and self-assessments designed by the NBME and NBOME are tools used by medical schools and medical students in order to assess preparedness for the licensing examinations. While this study was not designed to assess the differences between NBME CBSSA and NBOME COMSAE, the strength of the correlation between scores on NBME CBSSA and the performance outcomes on COMLEX-USA Level 1 suggests that further research is needed in order to identify those self-assessments that will most reliably predict preparedness for these licensing examinations. While the COMSAE is described as a self-assessment for osteopathic medical students, the present data suggest that osteopathic medical students may not be best served in assessing their future examination performance as a direct function of their COMSAE scores.Sketchy Micro, a microbiology review resource, was the only video resource that was related to an increase in score on COMLEX-USA Level 1. The completion of video resources did not appear to be related to the USMLE Step 1 score. Despite this finding, the present study may not have been adequately powered to reliably observe the relationship between the use of video resources and USMLE Step 1 and COMLEX-USA Level 1 performance.This study was limited by being a convenience sample rather than a randomized trial of different resources. Due to the study population and the subject matter, it would be difficult to design such a trial where students would be encouraged to complete one resource and avoid others. Additionally, the study was limited by being self-reports of exam scores and exam preparation rather than information gathered through a data pull. This was done specifically to ensure the consent of participants in what data was and was not available, however, it remains a limitation of the above work.This study demonstrates that resources written for the USMLE Step 1 exam are effective at preparing students for the COMLEX-USA Level 1 exam, and that performance on USMLE Step 1 is highly correlated with COMLEX- USA Level 1. This study also demonstrates the need for both medical schools and students to evaluate the resources they purchase for board examination preparation, especially those that claim to be designed for COMLEX-USA Level 1. Additionally, a collaboration between LCME- and COCA-accredited medical schools and longitudinal studies is needed in order to evaluate the resources and study methods used by medical students to optimize their performance on these examinations.


We searched for food compounds which can increase the expression levels of Mg2+ transport carriers including transient receptor potential melastatin 6 (TRPM6) channel and cyclin M2 (CNNM2). Sodium citrate (SC) increased the mRNA levels of TRPM6 and CNNM2 in renal tubular epithelial NRK-52E cells. The SC-induced elevation of TRPM6 was inhibited by U0126, a mitogen-activated protein kinase kinase (MEK) inhibitor, but the CNNM2 was not. SC increased the levels of p-ERK1/2 and p-c-Fos, which were inhibited by U0126. SC induced alkalization of culture medium. Both SC and alkalization enhanced Mg2+ influx, which was inhibited by U0126 and introduction of TRPM6 siRNA. The reporter activity of TRPM6 was increased by SC and alkalization, which was suppressed by mutation in an AP-1-binding site. The SC-induced elevation of p-ERK1/2 and p-EGFR was inhibited by diphenylene iodonium, a nicotinamide adenine dinucleotide phosphate (NADPH) oxidase inhibitor, and erlotinib, an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor. SC did not change the level of acetyl histone H3, but increased the association of c-Fos with the promoter region of TRPM6. These results suggest that SC increases TRPM6 expression and Mg2+ influx mediated by the activation of NADPH oxidase and an EGFR/ERK/c-Fos pathway in the renal tubules.A chronic magnesium deficiency may be one of the causes of lifestyle-related diseases such as hypertension and diabetes. Serum Mg Over 300 enzymes including oxidative phosphorylation and glycolysis require Mg2+ for their activity. Mg2+ deficiency may be a risk factor for lifestyle-related diseases such as hypertension, diabetes mellitus, and hyperlipidemia -2-oxoethoxy]-6-[bis[2-[(acetyloxy)methoxy]-2-oxoethyl]amino]-2-benzofuranyl]-(acetyloxy)methyl ester (Mag-fura-2 AM), and U0126 were from Cayman Chemical , Adooq BioScience , Enzo Life Sciences , ThermoFisher Scientific , LC Laboratories , respectively. Anti-actin, anti-phosphorylated ERK1/2 (p-ERK1/2), anti-c-Fos, and anti-p22phox antibodies were from Santa Cruz Biotechnology . Anti-p-EGFR, anti-ERK1/2, and anti-c-Fos antibodies were from Cell Signaling Technology . Anti-EGFR, anti-acetyl-histone H3, and histone H3 antibodies were from GeneTex . Anti-CNNM2, anti-NADPH oxidase (NOX) 4, and anti-TRPM7 antibodies were from Bioss Antibodies , ProteinTech , and Novus Biologicals , respectively. Peroxidase-labeled antibodies to mouse IgG, rabbit IgG, and goat IgG were from SeraCare Life Sciences . All other reagents were of the highest grade of purity available.Calcium citrate (CC) and SC were purchased from Wako Pure Chemical Industries . Diphenylene iodonium (DPI), Erlotinib, 5-(NRK-52E cells (IFO50480), derived from normal rat renal tubules, were obtained from Japanese Collection of Research Biosciences . The cells were grown in Dulbecco’s modified Eagle’s medium as described previously . Cells wR) according to the equation, R = 2−(Ct(drug treatment) −ΔCt(vehicle)).Total RNA was isolated from cells using TRI reagent . Reverse transcription was carried out using a ReverTra Ace qPCR RT kit . Quantitative real-time PCR was performed using a KOD SYBR qPCR Mix . The reaction conditions were an initial 60 s denaturation at 95 °C, followed by 40 cycles of amplification (15 s of denaturation at 95 °C and 60 s of extension at 60 °C). Primers used for PCR are shown in Cytoplasmic extracts, which include plasma membrane and cytosolic proteins, were prepared as described previously . The alig for 1 min, the pellet was washed four times with RIPA buffer. The immunoprecipitants were solubilized in a sample buffer for SDS-PAGE.In immunoprecipitation assay, the cytoplasmic extracts were incubated with protein G sepharose beads and anti-NOX4 antibody at 4 °C for 16 h with gentle rocking. After centrifugation at 6000× TRPM6 isoform a gene [NM_017662.4] was prepared as described previously [The promoter region of the human eviously . A Renileviously .2+]i was determined using a Mg2+-sensitive fluorescent dye, Mag-fura 2 AM, as described previously i is represented as arbitrary units relative to a reference value measured at 0 s. The increase in fluorescence values of Mag-fura 2 for 150 s (ΔA.U.) was compared in each group.The change in i) in a time-dependent manner  has been identified in Bacillus subtilis and E. coli DH5 cells. A mammalian subtype of CitM has not been cloned and we do not know whether CitM is expressed in mammalian renal tubules. However, the involvement of CitM in the SC-induced elevation of Mg2+ influx in NRK-52E cells may be excluded because the function of CitM is inhibited in buffers that are more alkaline than pH 7.5 [SC is commonly utilized as a chelating agent, emulsifier, and pH adjuster in many food applications. Sodium and citrate feature a high degree of safety because they are abundantly contained in various foods. In clinical therapy, SC is widely used as prevention and treatment of calcium oxalate stones. Serum citrate is filtrated at the glomeruli and then reabsorbed from renal tubules about 65–90% . Only 10n pH 7.5 .2+ and Ca2+ in a patient with nephrolithiasis is improved by being treated with Mg2+ and Ca2+ supplementation plus citrate salts [2+ influx in NRK-52E cells. In animal models, metabolic acidosis, which is induced by oral NH4Cl loading, induces reduction of TRPM6 mRNA levels and enhances urinary Mg2+ excretion [3 treatment, induces opposite effects. Micropuncture studies showed that metabolic alkalosis increases Mg2+ transport in the DCT [2+ deficiency using animal model.There is a case report showing that the renal wasting of Mgte salts . Mild hyte salts . These rxcretion . In cont the DCT . UrinarySome acid-sensing mechanisms have been identified including acid/alkali-sensing receptor, kinases, pH-sensitive ion channels, and the bicarbonate-stimulated adenylyl cyclase . Extrace2+ influx mediated by the activation of NADPH oxidase and EGFR/ERK/AP-1 pathway in NRK-52E cells. While the regulatory mechanism of CNNM2 expression was unclarified, SC increased the mRNA and protein levels of CNNM2. These results suggest that SC increases TRPM6-mediated Mg2+ influx in the apical membrane and CNNM2-mediated Mg2+ efflux in the basolateral membrane, resulting in the elevation of transcellular Mg2+ reabsorption in the DCT. SC may be a novel magnesiotropic food factor for preventing chronic Mg2+ deficiency.In the present study, we found that SC increases TRPM6 expression and Mg


A semi-continuum model for fluid flow in saturated-unsaturated porous medium in one spatial dimension is presented. The model is based on well-established physics, measurable parameters and material characteristics. The porous material is characterized by porosity, intrinsic permeability, main wetting and draining branches of the retention curve, and the saturation dependence of the relative permeability. The fluid is characterized by its density and dynamic viscosity. The only physics involved is the mass balance of fluid in porous media together with the Darcy-Buckingham Law for fluid flow in unsaturated porous media. The model is a cellular automaton based on the Macro Modified Invasion Percolation concept of dividing the porous medium into blocks which are not infinitesimal and are assumed to retain the characteristics of a porous medium. The cellular automaton repeats three successive rules: saturation update in each block, pressure update in each block, and flux update between neighboring blocks. The model tracks the evolution of the relative saturation, the fluid capillary pressure, and the fluid flux. The model is shown to reproduce qualitatively and quantitatively all features of one dimensional saturation overshoot behavior reported in the literature. The continuum mechanics based models lead to partial differential equations which are mathematical formulations of the balance of mass, momentum, and energy. The most used model connected to porous media flow is the so called Richards’ Equation (RE)2.Traditionally, porous media flow is described in the framework of continuum mechanics3. All of the regimes share the following setting: The porous medium is homogeneous, i.e. it does not contain any macropores, cracks, or preferential channels. The porous medium is unsaturated, i.e. some of the pores are filled with wetting fluid and some with gas. Gravity and capillary forces both play important roles and neither can be neglected.However, there are several persistent and important flow regimes in unsaturated homogeneous porous media (UHPM) which are not easily captured by continuum-mechanics based modelingThe so-called finger flow, or fingering effect, rates among the most intriguing of such regimes. The regime can be reached e.g. as follows: Let us start with a sample of initially dry homogeneous porous medium. Wetting fluid is supplied to one point at the upper boundary of the sample at a small constant rate. Under certain conditions (see below), a single (macroscopic) finger forms and proceeds downwards at almost constant speed see Fig. .Figure 1The proceeding finger leaves an under-saturated trace. Subsequent infiltration follows the path wetted by the first finger. The key feature of this regime is the non-monotonicity of the saturation: At certain points (through which the finger tip passes) saturation is a non-monotone function of time, first it increases abruptly as the over-saturated fingertip arrives, and then it gradually decreases again as the under-saturated fingertail passes. This effect is called the saturation overshoot.et al.4, Liu et al.5 and Selker et al.6. Comprehensive experimental work was done by DiCarlo et al.9. The main experimental results can be summarized as follows:Fingering accompanied by saturation overshoot is observed in wide range of homogeneous porous media types–soils, sands, and artificial glass beads, uniformly or randomly packed. It is observed for wide range of flow rates, and for wide range of initial saturation levels.The overshoot effect is observed in three-dimensional, two dimensional (Hele-Shaw cells) and one-dimensional (narrow tubes) settings.The finger behavior depends on the initial saturation of the matrix. With increasing initial saturation, the fingers first become more narrow and faster, then they widen and slow down and the saturation overshoot decreases. The overshoot phenomenon disappears when the initial saturation exceeds a certain limit. For initial saturation close to the residual moisture limit, the fingering regime disappears and diffusion-like front forms with no overshoot.The saturation overshoot magnitude (i.e. the difference between the saturation in the tip and the saturation in the tail) increases with increasing flow rate up to a certain value, beyond which it decreases until it disappears completely. However, there is also a lower limit–saturation overshoot is not observed for very small flow rates.Saturation overshoot depends on the shape of the porous matrix grains. The effect is less pronounced for spherical sand grains than for sands with more angular (irregular) shapes. Materials with very similar macroscopic continuum properties exhibit different saturation overshoot patterns.The finger-tip is not always fully saturated, its saturation depends on the flow rate and on initial saturation of the medium.10 report some evidence for velocity dependent behavior.Capillary pressure overshoot is consistent with the saturation overshoot, and the pressure-saturation relation does not seem to depend on the finger velocity, although other sources11.The overshoot behavior depends on the ratio of capillary and gravitational forces captured by the so-called Bond number16. The equation used for UHPM flow is the Richards’ Equation (RE)2 which can be stated in the following form:S is the unknown field of relative moisture content , K stands for the hydraulic conductivity which is assumed to be non-negative and non-decreasing function of the saturation. The function Pw(S) is related to the retention curve by the simple rescaling relationρ is the density of fluid and g is gravity.There have been many attempts to capture gravity-driven fingers and especially the saturation overshoot by continuum mechanics based models, e.g. adding new terms into the RE16 or to use the RE to describe at least some of the features of finger flow6.There have been many attempts to add new terms into the RE in order to describe saturation oveshoot17 and von Neumann18. The field of discrete models, often called cellular automata, was usually considered a part of statistical physics, and had almost no overlap with porous media flow modeling. In the 1970s, a new branch of discrete dynamical systems science emerged, which became known as percolation theory. The most important early contributions can be traced back to Kirkpatrick19 and Stauffer20. It was soon recognized that percolation theory can be used to model immiscible fluid flow in porous media. The theory was used to predict the fractal structure of the percolating clusters of fluids, capture the critical behavior of pressure and hydraulic conductivity dependence on saturation near the percolation threshold, and point out the universality of the various scaling relations21. Lenormand et al. conducted an extensive research in this direction, both experimental and theoretical, which clarified the mechanisms by which individual pores are filled and drained by wetting and non-wetting fluids25, see also the work of Blunt and Scher26 for important contributions to the understanding of collective pore filling mechanisms. Based on these seminal papers, there has been an explosion of theoretical and experimental results which used percolation theory to capture the flow of immiscible fluids in two or there dimensional porous media at the pore level, under various combinations of viscous and capillary forces and the force of gravity. The porous medium is usually modeled as two or three dimensional regular or random network of pores and/or throats, of various types of cross-sectional shapes and various types of connectivity. Usually two (sometimes three) immiscible fluids are allowed to move inside this network. Pores and throats are usually filled with one fluid, or the other, intermediate levels of saturation inside a single pore are seldom considered. These models are typically called Invasion Percolation (IP) models or, if they also include an external force field, Modified Invasion Percolation (MIP).Let us now turn to a completely different possibility of UHPM flow modeling, which we call discrete modeling. The interest in discrete dynamical systems goes back to the work of Ulamsemi-continuum models borrowing the term from the article of DiCarlo et al.27. A semi-continuum model was reported by Glass et al.28 following a series of papers32. Let us note that the authors themselves call the approach “mechanistic modeling”, or Macro Modified Invasion Percolation (MMIP), they never use the term “semi-continuum model”. In their MMIP model, the porous medium is represented as a regular grid of rectangular sites  in two or three dimensions, with certain specified type of connectivity. Each block is a small part of the original porous medium (hence our “semi-continuum” label) completely described by two numbers:It is natural to try to combine the advantages of both the continuum-based and discrete approaches. Let us call these model Pw is the pressure needed for the invading phase to fully percolate the block (that means to form a connected network of filled pores throughout the block so that the block becomes conductive for that phase).Pd is the pressure needed for the defending (retreating) phase to reinvade the block.Saturation overshoot in gravity-driven fingers was experimentally observed by Glass i stands either for w or d, σ is the surface tension between the phases and ϕ is the contact angle. Thus, each block can be assigned a critical wetting radius Rw and a critical draining radius Rd.The pressure can be related to a radius of curvature by means of the formulaRi in Eq.  of not having to worry about the particular geometry of the pores and throats. It is important to note that the radii i in Eq.  do not r33. The model is based on well-established physics only. In the next section, the physics of the model is presented and the resulting cellular automaton is fully described. In the Results section, the ability of the model to reproduce experimental observations is presented. Saturation and capillary pressure overshoot behavior is reproduced, both qualitatively and quantitatively. The dependence of the saturation overshoot on influx and initial saturation is reproduced, too.We want to present a slightly different semi-continuum model in one spatial dimension. This model reproduces qualitatively and quantitatively all of the features of saturation overshoot behavior reported by DiCarlo33. The tube has a cross-section of A [m2], the height of the tube is L [m]. Lets subdivide the tube into small blocks of height dx and cross sectional area A. These blocks represent “pieces” of the original porous medium and they are not to be considered infinitesimal. For a given time, the key physical quantities (see below) are considered constant within a single block. This is a direct reference to the semi-continuum approach of Glass and Yarrington28. The tube now consists of slices  with n = 0,1, … N. The key quantities that we want to track areSi [−] in each block.Saturation Pi [Pa] in each block i.e. the average pressure difference across the menisci (wetting fluid–gas interfaces) in the block. For simplicity, air pressure is set to zero everywhere.Capillary pressure qi,j [m/s] between the blocks i and j. Real fluxes in [m3/s] can be recovered as Aqi,j. Naturally, only fluxes between neighboring blocks are non-zero in this setting.Fluxes Let us suppose a long narrow vertical tube filled with homogeneous porous medium, e.g. 20/30 sand as in the experiments of DiCarlox− axis here. A constant (in time) influx q0 [m/s] at the top boundary (x = 0) is assumed. Zero discharge qL = 0 (i.e. zero flux) at the bottom boundary (x = L) is assumed.Gravity is directed downward along the long axis of the tube, which is called the θ [−] stands for the porosity of the material. This can be understood in the semi-continuum setting as a simple discrete schemedx and dt are discretization parameters. The specific form of the fluxes qij are given by  finger tip is in the imbibition mode while the under-saturated finger tail is in the draining mode. Consequently, no reasonable model of saturation overshoot can ignore hysteresis. Let us use the following very simple approach. Suppose that the material has a well-defined main wetting branch of the retention curve denoted byNext, the pressure in each block has to be updated, because the fluxes are governed by pressure gradients. Hysteresis of the retention curve has to be addressed in this step because it is knownThis means that if a block starts at zero saturation and becomes more and more wet, the capillary pressure in the block will be dependent on its saturation through Eq. . AnalogoS = 0 and S = 1 ends.For any block that starts at unit saturation and becomes less and less wet, the capillary pressure will be given by . A typic33. We adopt the simplest modeling approach and describe this process by a relationKPS. It means that between the main branches, saturation changes with pressure very rapidly, following a line with a very large slope KPS. One may think of the saturation jumping from the wetting to the draining branch discontinuously  but this would cause unnecessary numerical issues in the model, hence this approximation. We believe there is a simple explanation for this rapid behavior: Capillary pressure originates as an average of the pressure drops across the fluid–gas menisci. As a block switches between imbibition and draining, the shape of the menisci changes  which causes almost no measurable change in volume but a dramatic increase in the pressure drop across the menisci. Relation . It is understood that the advancing of the finger tip is where the classical theory fails. The overshoot can be understood as fluid piling up behind the fingertip because the dry medium ahead of the fingertip has insufficient hydraulic conductance thus the flux across the fingertip cannot keep up with the flux in the tail of the finger. Thus, fluid piles up behind the fingertip which increases the hydraulic gradient across the finger tip until the large gradient “matches” the low conductivity and the flux across the fingertip equals the flux in the tail. Then, a stable finger with an oversaturated tip proceeds with constant velocity downwards.1 states:κ [m2] is the intrinsic permeability of the medium, μ [Pas] is the dynamic viscosity of the fluid, ρg is the gradient of the gravitational potential, and P [Pa] is the capillary pressure. Here k(S) [−] stands for the relative permeability which is very sensitive to S and is usually modeled by a power law relationm usually around 3 or 4 .The original Darcy-Buckingham Law for unsaturated porous media flowP is large, and S changes abruptly from small values in front of the fingertip to large values inside the fingertip. We propose the following discrete implementation of the Darcy Law:In view of the two preceding paragraphs, it is crucial how we model the conductance at the finger tip, where ∇geometric mean of the permeability of the respective blocks. The geometric mean a and b is small. It is also possible to use the harmonic mean with similar results. The more common (arithmetic) mean does not behave in this way. Notice that if the saturation vanishes in a block, the flux to/from the neighboring blocks becomes zero. Therefore, the initial saturation in all blocks has to be set to a nonzero value.Thus, for the relative permeability at the finger tip edge, we simply take the dt → 0, dx → 0, the numerical scheme (with geometric or arithmetic mean) converges back to RE which is known35 to be incapable of producing any overshoot. Thus, the issue of the limit of this semi-continuum model is an important one and it is left to the Discussion section.Notice that in the limit dx is chosen and an appropriate time step dt is set (see Discussion). Initial saturation Si is prescribed in each block , the corresponding capillary pressure is computed, and all fluxes are initially set to zero.The size of the blocks q0. The bottom boundary condition is set: the flux out of the bottom block is set and fixed to zero.The top boundary condition is set: the flux into the topmost block is set and fixed to qi,j, saturation Si in each block is updated according to Eq. , kee, keePi iqi,j between neighboring blocks are updated according to , the following parameters are used for the simulation:θ = 0.35 [−],porosity of the material κ = 1 × 10−10 m2,intrinsic permeability of the material μ = 9 × 10−4 Pas,dynamic viscosity of water ρ = 1000 kg/m 3,density of water g = 9.81 m/s2,acceleration due to gravity A = 10−4 m2 ,cross sectional area of the tube L = 40 cm (the tube will be divided into 40 blocks of height 1 cm).length of the tube In this section, we reproduce the experimental results of DiCarlodx is inspired by Glass and Yarrington28 and reflects the requirement for the blocks to be large enough to retain the characteristics of the original porous medium. At the begining, all blocks are assumed to be in imbibition mode. The saturation dependence of the relative permeability is modeled by k(S) = S3. The retention curve in Fig. KPS = 105 Pa.The choice of 33 in the left panel of Fig. Si = 0.003 everywhere. Since we report the results in SI units and assume the cross-sectional area of the tube to be A = 1 cm2, the conversion factor for the influx between the experiment and the simulation is roughly 60 × 100 × 1.272 ≅ 10000. Thus, the experimental influx that was small enough not to cause saturation overshoot (q0 = 8 × 10−4 cm/min) corresponds roughly to q0 = 2 × 10−8 m/s in our simulation. Further, the experimental flux which causes complete flooding of the material (q0 = 11.8 cm/min) with no overshoot roughly matches the same situation in our simulation (q0 = 10−3 m/s). It can be observed that the model is able to reproduce both the dependencies, magnitude of the overshoot and the length of the oversaturated zone.First, we want to demonstrate the ability of the semi-continuum model to capture saturation overshoot in infiltration into initially dry homogeneous porous medium, and the dependence of the overshoot on the influx. The dependence of the oversaturation profile on influx is rather complicated: For a very small influx, there is no visible saturation overshoot. With increasing influx, a distinct overshoot pattern appears. The magnitude of the overshoot and the length of the oversaturated zone increases with increasing influx. If the influx is too large, the fingertip becomes almost completely saturated and the length of the oversaturated zone grows all the way to the upper boundary of the sample. Thus, the overshoot disappears for fluxes which are too large. This rather complicated dependence is well replicated by the semi-continuum model, see the comparison of the experimental data by DiCarlo9 that with increasing initial saturation, the overshoot is less and less pronounced and finally disappears completely, and diffusion-like behavior prevails. This seems to be captured well by the semi-continuum model, see Fig. 33, the overshoot disappears completely for Si = 0.14, for influx comparable to our simulation. This is in a quantitative agreement with our simulation .Let us now investigate the effect of initial saturation on the saturation overshoot. It is knownt = 0 corresponds to the arrival of the finger tip through this point, we obtain behavior depicted in Fig. The capillary pressure overshoot is in agreement with saturation overshoot. If we observe the evolution of capillary pressure at a single point along the tube, and offset the time scale so that t = 0 corresponds to the arrival of the fingertip at this point. We now track the evolution of the capillary pressure at this point. The time series of capillary pressure at this point exhibits visible oscillations after the finger tip passes. This is due to the build up of the saturation in the fingertip and then sudden burst into the block beneath. The solid line in Fig. Let us fix a point 12.5 cm from the upper boundary, i.e. a point in the 13 th block from the top. Let us offset the time so that 33 reports that “When a larger initial water saturation of 0.06 was used, the [saturation] profiles are found to be monotonic at all fluxes, with no saturation overshoot”. However, a careful look at Fig. 33 (not reprinted here) shows that there is, in fact, a small capillary pressure overshoot for initial saturation 0.06 for fluxes higher than 10−1 cm/min. Even for initial saturation of 0.14 where no saturation overshoot was observed, the pressure overshoot is still clearly visible for high enough fluxes. This subtle behavior is well reproduced by our semi-continuum model  and thus it cannot be observed in experiments. This explains the seemingly self-contradictory observation of DiCarlo.The model reveals that, indeed, there is saturation overshoot accompanying 10, although the author expected, in contrast to his own experimental results, that the finger develops immediately at the inflow boundary and then flattens over time and depth.To understand the formation of the finger well, it is convenient to plot the profile of the finger at various time points. Figure 10 : (1) the velocity of the finger tip gradually increases before reaching a steady state at a certain depth, (2) the length of the oversaturated zone of the finger increases with time . Both these trends are correctly captured by the semi-continuum model , the model converges to the RE and, accordingly, the overshoot behavior disappears. This convergence is theoretically clear from the statement of the model and has been tested numerically. Thus, this model is interpreted as a cellular automaton (or Macro Modified Invasion Percolation model) with continuous levels of saturation. We conjecture that the continuous limit of the cellular automaton must be approached in a different way.First of all, it should be noted that the proposed model is not a numerical scheme for solving the Richards’ Equation (RE). RE in its original form (without new terms) was conclusively showndt → 0, dx → 0, one cannot assume that the distribution of the characteristics of the blocks (i.e. their permeability and porosity) stays the same. We conjecture that with decreasing dx, the variance of this distribution has to increase. As the blocks become smaller and smaller, some of them will likely represent a void of the porous matrix (thus becoming very permeable) and others will likely represent the bulk of the porous matrix (thus becoming negligibly permeable). Note that this idea goes directly against the continuum mechanics paradigm! To stress the contrast further, imagine we treated the problem of heat diffusion by the semi-continuum approach presented above. The heat conducting material would be cut up into blocks and heat would flow between the adjacent blocks according to Fourier’s Law. Each block would be described by the same heat conductivity coefficient. Next, the mesh would be refined. Naturally, the heat conductivity coefficients would not be affected by the refinement of the mesh. Taking the limit of the refinements (together with dt → 0) would yield the classical heat equation.In performing the limit variance of the material parameters has to increase. If such a scaling is introduced, we believe a meaningful limiting process dx → 0 of the semi-continuum model can be performed. This cannot be done in one spatial dimension, since the increase in the variance of the characteristics would lead to “topological bottlenecks”, i.e. blocks with permeability low enough to jam the flow completely. In two or three spatial dimensions, these bottlenecks will also form but will be circumvented easily by the flow. Moreover, we believe that these bottlenecks will also produce the rich structure of spatial patterns of finger flow, which is observed in experiments but so far has not been reproduced by any model with continuous saturation. The MMIP model of Glass et al.28 has been so successful because it correctly captures the variance of the wetting and draining pressure across the material. However, since it still treats saturation as a discrete quantity, it cannot be used to reproduce any of the results we present here. Since this paper deals with one dimensional flow, the limiting process is not addressed here.However, in the context of unsaturated porous media flow, the material coefficients cannot stay constant during the limiting process. As the blocks become smaller, the dx, its dependence on time step dt is similar to the behavior of explicit numerical schemes for parabolic partial differential equations. For dt small enough, the solution becomes stable and independent on further decrease in dt. The choice of dt depends mainly on the influx q0 and on the parameter KPS which characterizes the scanning curves in the region between the main wetting and draining branches of the retention characteristics. The time step dt decreases with increasing q0 and KPS.Unlike the dependence of the model on 37 and heavily criticized since then13. Nieber used the averaging process in a numerical solution to RE. That was proven wrong by Eliassi et al.13 who showed that his “numerical solution” was far from the true solution to RE. Thus, by the averaging process, Nieber obtained an incorrect numerical solution to RE. Today we now know that RE is inappropriate for finger flow modeling35. In the present semi-continuum model, the averaging process is not used to obtain a numerical solution to any differential equation. The averaging process is based on the studies of the so called equivalent hydraulic conductivities of spatially varying media38. There is theoretical justification to use the harmonic mean of conductivities (as a lower bound) in case of a medium stratified perpendicular to the flow direction38. This is similar to the situation at the fingertip where an almost saturated block is in contact with an almost dry block beneath. In a series of numerical experiments in a random pore networks, Jang et al.38 report results which are mostly consistent with the averaging process using the geometric mean. Thus, the geometric mean of relative permeability of the neighboring blocks is used in our model.Averaging of hydraulic conductance has been used before33. Materials with identical macroscopic characteristics exhibit different overshoot behavior. It may be possible to model this process if we knew the exact positions and shapes of the grains at the fingertip. However, such detailed knowledge is neither available nor wise to incorporate in a porous medium flow model. Our model accounts for this “burst-and-hold” behavior by the following fast positive feedback: The block beneath the finger tip is dry, thus its conductivity is very low. The flux into the dry block is thus negligible and fluid piles up behind the fingertip. Once the pressure at the front increases enough and the previously dry block starts filling with water, the flux from the finger tip increases very quickly (as the third power of the saturation), making the block even more wet, which in turn increases the flux even more. This positive feedback fills the dry block with fluid almost instantly. This makes the finger “jump” ahead by one block. Notice that modeling the flux between the blocks by means of the geometric average is crucial in this process. It should also be stressed that it is crucial to take into account the hysteresis of the retention curve which prevents the oversaturated fingertip to drain into the undersaturated tail.Experiments show that the behavior of the finger tip edge is crucial for the flow pattern. The overshoot can be understood as fluid piling up behind the fingertip because the dry medium ahead of the fingertip has insufficient hydraulic conductance thus the flux across the fingertip cannot keep up with the flux in the tail of the finger. The detailed mechanism of the fingertip advance matters here. The fluid menisci “jump” from grain to grain, rather than flow in a continuous way. That is why the overshoot behavior so much depends on the shape of the grains, as reported by DiCarloIn view of this burst-and-hold behavior, it is interesting to recall the oscillations in pressure that the semi-continuum model exhibits. We do not know whether this behavior is an artifact of the discrete nature of the model or if it reflect reality. We note that the period of the oscillation is of the order of ten seconds in our model. It may be difficult to detect such fast changes by conventional tensiometers.40. Hoffman41 describes the dependence of the contact angle on the velocity of the flow. Steenhuis et al.39 use this result to predict the capillary pressure in the fingertip for various levels of influx and initial saturation. They assume that water at the fingertip advances by bursting through a single pore with a velocity high enough to cause a decrease in the contact angle. This causes the pressure to build up in the tip of the finger. There is experimental evidence in support of this mechanism42. Whatever the microscopic origin of the capillary pressure is, a semi-continuum model has to capture its effect in terms of quantities that are measurable on the level of the blocks. In our case, the macroscopic manifestation of these pore-scale processes is the low relative permeability between the wet block at the fingertip and the dry block directly beneath.The microscopic origin of the “burst-and-hold” mechanism has been debated for a long time. Capillary pressure arises from the shapes of the water-air interfaces on the pores are dictated by the geometry of the pore space and the incompressibility of the flow. It is probable that velocity dependent effects also play a roleKPS may be an exception–it is not usually assumed that all the scanning curves between the main wetting and draining branch of the retention curve are lines with a large gradient. However, any measurement is difficult here and sometimes an estimate of the gradient of the scanning curves is the only option.Let us stress again that the presented model is entirely based on well-known physical principles and material properties. The coefficient Let us also note that the presented model is in no way “tuned” to capture saturation overshoot. When diffusion-like monotonic behavior is expected, the model captures it well, too  capillary pressure becomes zero and (positive) hydrostatic pressure appears. The hydrostatic pressure is computed using the height of the water column (i.e. the height of fully saturated blocks) above the considered block. Thus, in Eq. 1 and soil hydrology43. From mathematical point of view, the model is a cellular automaton based on the Macro Modified Invasion Percolation concept of dividing the porous medium into blocks which are not infinitesimal and are assumed to retain the characteristics of a porous medium. In discrete time steps , the cellular automaton repeats three successive rules: (1) saturation update in each block based on known fluxes between the neighboring blocks, (2) pressure update in each block based on saturation known from the previous step and the retention characteristics of the material, (3) flux update between neighboring blocks based on the Darcy-Buckingham Law and a geometric mean of the hydraulic conductivity of the two blocks.A one dimensional semi-continuum model of steady infiltration into a homogeneous unsaturated porous medium is presented. The model fully rests on well-known theoretical and experimental concepts developed in soil physicsThe model captures well all the features of one dimensional unsaturated porous media flow , especially finger flow, including the saturation overshoot, capillary pressure overshoot and their dependence on initial saturation of the medium and influx intensity. The shape of the saturation overshoot profile and its evolution in time and space also agrees with observations.The limit of the proposed model for the block size going to zero is a subtle issue and cannot be considered in one spatial dimension for topological reasons. In performing the limit, the variability of the characteristics of the blocks  has to be considered carefully. Extension of the model to two and three spatial dimensions will be considered next, together with the limit for block size going to zero.We believe that the semi-continuum approach has the potential to bridge the gap between discrete models of unsaturated porous media flow and continuum models.


Introduction: When divers are compressed to water depths deeper than 150 meter sea water (msw), symptoms of high-pressure neurological syndrome (HPNS) might appear due to rapid increase in pressure on the central nervous system during compression. The aim of this study was to first operate a new computerized tool, designed to monitor divers’ wellbeing and cognitive function, and to record the results. The second aim was to evaluate the feasibility and validity of the Physiopad software and HPNS questionnaires as a new tool for monitoring divers wellbeing in an operational setting, including sensible visualization and presentation of results.Methods: The Physiopad was operated onboard Deep Arctic (TechnipFMC Diving Support Vessel). The diving work was performed between 180 and 207 msw. The data from 46 divers were collected from the HPNS questionnaires, Hand dynamometry test, Critical Flicker Fusion Frequency test (CFFF), Adaptive Visual Analog Scale (AVAS), Simple Math Process (MathProc test), Perceptual Vigilance Task (PVT), and Time Estimation Task .Result: Diver’s subjective evaluation revealed different symptoms, possibly also HPNS related, which lasted from 1 to 5 days in storage, with the common duration being 1 day. The results from Physiopad battery testing showed no signs of significant neurological alteration.Conclusion: The present study showed that there was no association between subjective measurements of HPNS and neuropsychometric test results. We also confirmed the feasibility of using the computerized test battery to monitor saturation divers at work. The HPNS battery and Physiopad software could be an important tool for monitoring diver’s health in the future. This tool was not used during the Bahr Essalam project to operationally evaluate any HPNS effect on divers as data analysis was performed post-project. With the development of oil and gas industry, the need for offshore commercial underwater work has accelerated. High-pressure neurological syndrome (HPNS) has been reported as a condition that may appear in diving deeper than 150 meters of seawater (msw) due to the rapid increase in pressure on central nervous system (CNS) during compression . HPNS isThe Psychology Experiment Building Language (PEBL) battery is a free software consisting of approximately 50 different validated experimental psychology and behavioral neurology tests to evaluate cognitive function in subjects . SeveralThe aim of this study was to evaluate cognitive function and symptoms of HPNS in operational saturation diving. We also aimed to evaluate for the first time, the feasibility and validity of using computerized package as a new tool for monitoring HPNS and diver’s health.Data were collected during Bahr Essalam project operated by TechnipFMC  on board the “Deep Arctic” diving support vessel (DSV) in the Libyan Sea between March and September 2018. Data collection was performed at work site, all participants were employed by TechnipFMC and fully informed before recruited in the study, and no further written consents were required. The data collections were conducted according to the Declaration of Helsinki principles for ethical human experimentation  and the The saturation period consisted of four phases: compression, storage, decompression, and bendwatch . The diver’s compression rate was 1 msw/min upto 180 msw and 4 msw/min from 180 msw to storage depth. There was 10 min hold at 10 msw, 20 min hold at 100 msw, and 2 h hold at 180 msw. The longest diver compression from surface to 198 msw took approximately 7 h. In addition, there was a minimum stabilization time of 4 h before the divers could start the first bell run. Heliox 98/2 and Heliox 98/1 gas mixtures were used to achieve an oxygen partial pressure of 38 kPa at storage depth. The storage depth was between 170 and 198 msw depending on the work site. During storage, divers performed work slightly deeper than their storage depth (maximum 8 h bell runs), while two divers worked in the water (maximum of 6 h in-water time), the third diver remained in the diving bell as standby diver. The working depth was between 180 and 207 msw. Decompression rate was 1 m/40 min until 60 msw, 1 m/50 min until 30 msw, 1 m/60 min until 15 msw, and 1 m/80 min until surface. Six hours hold during nights was followed during the entire decompression. The longest decompression from 198 msw to surface took just under 9 days without including bendwatch. After surfacing, the divers stayed on the vessel for at least 12 h for bendwatch. All saturation protocols followed the diving contractor diving manuals, with basis in TechnipFMC document “MOS-GM-DIV-12109 Extended and Deep Diving Procedures.”There were 36 dive teams participating in this study, each team consisted of three divers. They performed a total of 500 bell runs. Divers had 1–3 saturation periods while each saturation period was 28 days for all divers except six divers who completed a period of 20 days. The time off between each saturation period was not the same for all divers, however, it was never less than 28 days; the majority of divers had 37 days off ,B. Data Deep Arctic is equipped with six living chambers, of which four are three-men chambers where divers live during the work period. The two other chambers are six-men chambers, which are utilized during compression and decompression of two teams of three divers when the teams at bottom need changing out .Physiopad package is a compilation of HPNS questionnaires, Hand dynamometry test, Critical Flicker Fusion Frequency (CFFF) test, Adaptive Visual Analog Scale (AVAS), Simple Math Process (MathProc test), Perceptual Vigilance Task (PVT), and Time estimation task . Divers were introduced to the Physiopad package during mobilization, prior to saturation. They were also provided with several instruction videos to assist them to operate the software in the situations where the instructor was unavailable (interim crew changes). Divers were instructed to perform the test every day, starting with a baseline test at surface prior to commencing saturation and as soon as they reached storage depth after compression. The testing period ended the last day (when they had returned to surface). The divers could decide themselves when to perform the testing during their shift, before or after diving. In the analysis, we used the data from Pre-saturation (baseline), Storage, and Post-saturation. The Pre- and Post-saturation session’s data were collected by using tablets  and a stationary computer was used during the saturation session.The HPNS questionnaire consisted of questions related to known HPNS-related symptoms revealed in previous studies ; visual,The Flicker device  was used to assess cognitive function and cortical arousal evaluating visual temporal processing. The device was described previously . CorrelaHand dynamometer measures the maximal isometric hand grip strength . We usedComputerized Adaptive Visual Analog Scale (AVAS) was used to measure (subjective) reported fatigue . The AVAExecutive and cognitive functions of divers participating in the study were measured by The Simple Math Process test, The Perceptual Vigilance Task test, and Time Estimation test . These tIn the MathProc test, the diver is given a simple mathematics test to subtract and/or add single digits and decide if the result is more or less than 5. The diver will receive the next task after answering the previous one. In total, 20 random tasks will appear each time. We measured the time took the divers to answer, number of correct/incorrect answers and total test time. The divers did not receive input regarding correctness of their answers.Divers should follow the command: “click here when the red dot appears as fast as possible.” They can use mouse to click on this button as soon as they observe the red dot. The red dot appears with random delays. Software registers the delay time and the total test time. The task is repeated 20 times. Answers do not appear to the divers.In this test, the ability to estimate the speed of a moving square object when it hits the floor while it is hidden behind the wall was tested. Divers should follow the command: “click here when the square hits the floor,” they can use mouse to click on this button. The task is repeated 20 times.p of the cumulative Chi2 distribution was reported. Mann-Whitney U Test was used to analyze the differences between symptomatic and non-symptomatic groups. Statistical differences with p < 0.05 were considered significant.Statistical analysis was performed using XLSTAT version 2018-1  compatible with MS Excel. All numerical data were tested for normality by using Shapiro-Wilk test and Jarque-Bera test. Kruskal-Wallis honesty test (KWH) for non-paired data and Friedman’s test for paired datasets were used to analyze non-parametric data followed by Steel-Dwass-Critchlow-Fligner procedure for multiple pairwise comparisons where appropriate. The logistic regression was used for predictive analysis and the The demographic data for the tested groups are presented in n = 23) of divers reported different subjective symptoms during all three saturation periods. The proportion of divers in each saturation period who reported symptoms was 37, 35, and 36% in saturation periods 1, 2, and 3, respectively. The distribution for individual reports of different symptoms is shown in p = 0.48), BMI (p = 0.83), years of experience (p = 0.35), or VO2max level (p = 0.36).Fifty percent .The CFFF test was performed once per day and the value was calculated from three consecutive attempts. The CFFF data from just 36 divers during Storage phase in saturation period 1 and 24 divers in saturation period 2 were used in analysis. No differences between groups in different phases were found by KWH . AccordiU = 204, p = 0.32).KWH was used and demonstrated no differences between groups in different phases . Significant difference was also observed between Pre-saturation and Storage in the third saturation period (Wij = 1.13 p = 0.006). No difference in AVAS results between divers with HPNS reported symptoms and non-symptomatic group in any saturation periods was observed .Results showed increase in amount of perceived fatigue during the entire Storage phase compared to Pre-saturation. Friedman’s test did not reveal differences in test’s results in the first saturation period. In saturation period 2, there was significantly higher value in Pre-saturation in comparison to Storage and Post-saturation  and this was already achieved during the first saturation period . In U = 252, p = 0.59).In analysis of the amount of wrong answers and delays for giving an answer, no differences between phases and saturation period were found. Divers demonstrated their ability to learn the task during the study . Similar results were observed between Pre-saturation and storage in saturation period 2 (Wij = 0.788 p = 0.04 for Pre-saturation2 vs. Storage2). No difference in test results between the three different saturation periods was observed .Based on repeated measurement using Friedman’s test, PVT test duration was significantly longer in Pre-saturation compared to Storage and Post-saturation in the first saturation period (observed . No diffWij = 4.55 p = 0.034). No differences in the test results between the three different saturation periods were observed .Based on repeated measurement using Friedman’s test, time-wall test duration was significantly longer in Post-saturation compared to Storage in saturation period 1  was reported while other HPNS-related symptoms were present . HoweverThe results of psychometric tests in this study showed no difference between the saturation phases or saturation periods. These psychometric tests were previously shown as good assessors of cognitive function in divers . The detChanges in divers’ EEG due to HPNS were reported in previous studies . EEG is There were no differences detected between those with subjective symptoms and those without, but no cases of HPNS were medically diagnosed, so the tool proves to be adequate in assessing divers’ efficient work capacity since all divers continue to work during the dive, no one was impeached. Nevertheless, its medical sensitivity must be ascertained after testing it upon subjects with and without medically diagnosed HPNS. We need to emphasize that the result of this study was not used during Bahr Essalam project to operationally evaluate any HPNS effect on divers as data analysis was performed post-project. We were able to collect data everyday without interfering with the diver’s job; however, there are several suggestions to improve the Physiopad software. Tremor is the most known clinical symptom of HPNS . In the While, divers were instructed to perform the test as soon as they reached storage depth after compression, several divers did not follow this instruction. There was inconsistency among divers for the start of the test; therefore we decided to use the data from entire Storage phase. The authors could not give all the instruction to the divers due to the time and operational constraints to stay onboard. The Flicker devices were removed from chambers after 3 months at the start of the project due to the lithium battery restrictions. Thus, we were able to collect the Flicker data during Storage phase just for a short period. The new generation of Flicker device with AA battery and compatible with hyperbaric environment is commercially available now and could be a useful tool for future research, but we did not have access to this new Flicker device during data collection.Moreover, there was a limitation in Phyiopad software related to given IDs. Divers mixed their IDs between stationary computers and tablets many times since the software allows them to log in with new IDs and reset the passwords. This made it difficult to keep track of the individual recordings. Having assigned IDs with predefined password would help with this situation and divers will not be able to log in with any other ID.The datasets generated for this study are available on request to the corresponding author.Ethical review and approval were not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.ØL designed the study, diving technical supervision, and report review. SB managed the data collection. SB and EB conducted the statistical analysis. SB drafted the manuscript. All the authors contributed to final correction and writing.ØL is employed by TechnipFMC in Norway and CB is a founder of I-Phy in Belgium.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.