Classification performance improves slightly when crowds are presented individually, but not enough to out-perform random guessing. We find that untrained individuals have an idealized view of human crowd behaviour which is inconsistent with observations of real crowds. Our results suggest a possible framework for establishing a minimal set of collective behaviours that should be integrated into the next generation of crowd simulation models.The accuracy and believability of crowd simulations underpins computational studies of human collective behaviour, with implications for urban design, policing, security and many other areas. Accuracy concerns the closeness of the fit between a simulation and observed data, and believability concerns the human perception of plausibility. In this paper, we address both issues via a so-called ‘Turing test’ for crowds, using movies generated from both accurate simulations and observations of real crowds. The fundamental question we ask is ‘Can human observers distinguish between real and simulated crowds?’ In two studies with student volunteers ( Put simply, do simulated crowds appear ‘lifelike’ in terms of their overall behaviour? To answer this question, we took a number of observed crowds moving through a space, and constructed simulations of them that accurately matched the statistical properties of the real crowds . We then presented the observed and simulated crowds , and asked participants to identify the real crowds.Crowd simulations  are now employed in many different domains, from events planning and management , to urball-being . An impoThe rest of the paper is organized as follows: in §2.en masse, and encompasses a diverse range of crowd types, from large, mainly static crowds at sporting events or concerts [simulation [The study of human crowd dynamics  is motivconcerts , to tranconcerts , or at rconcerts . As urbaconcerts ), we wilconcerts . A numbemulation .fluid dynamics [entity-based approach, which treated crowds as individual ‘particles’ [agent-based methodology, in which individuals are treated as semi-autonomous actors [accuracy and believability. Here, we define the accuracy of a simulation in terms of its validity [Early attempts to understand crowd behaviour were rooted in the physical sciences, using metaphors and mathematical tools from dynamics , and moddynamics . Subsequrticles’ ,18, alons actors . As crowvalidity –23; how believability is subtly different, and concerns the human perception of whether or not a crowd’s behaviour is plausible. We emphasize that we do not concern ourselves with ‘cinematic’ believability . Rather, we are interested in whether or not observers are capable of detecting characteristic patterns of behaviour that are specific to real crowds, and which may not be present in simulated crowds.The issue of Our testing framework may be thought of as a limited form of the famous ‘Turing test’, named after Alan Turing, and described in his landmark paper on artificial intelligence . Turing Our overall aim is to explore how a Turing-like test may be used to examine assumptions and preconceptions about the behaviour of human crowds, and to establish the features of real crowds that must be emulated by a simulation in order for it to be valid and/or ‘pass’ the test. This is motivated by a widely acknowledged need for crowd simulations to include more ‘lifelike’ features derived from individual and social psychology (such as group-level behaviours and indecision) –30, whic3.in-person (as opposed to online) participants. The first trial tested the ability of participants to distinguish between real and simulated crowds, and the second trial tested the ability of a different set of participants to identify real crowds in a sequence of movies.Our experimental methodology was based on that of , but witn = 384), we showed all participants six pairs of randomly ordered movies of 30s duration . In each pair, one movie showed the movement of a real crowd, and the other showed the output of a crowd simulation with the same statistical properties as the real crowd , we used the same set of movies as in the first trial, but this time they were individually presented, in a random order, and participants were asked to classify each movie as either ‘Real’ or ‘Simulated’. In order to prevent possible bias, both sets of participants were disjoint.For the first trial . However, this dataset has been used in a large number of studies of pedestrian movement/tracking, including [We used data on real pedestrians from the University of Edinburgh School of Informatics . This puncluding –34, imponcluding ).FigureIn what follows, we use the term ‘clip’ to specifically refer to a time-limited sequence of trajectory data (whether taken from the Edinburgh dataset or from the output of a simulation), as opposed to a movie visualization. We wrote a utility to search the Edinburgh dataset and extract clips of a specific duration containing a specific number of individuals. This allowed us to ensure that the ‘real’ and ‘simulated’ crowds contained the same number of individuals for any single comparison.3.2.−1. When we simulated these scenarios (see next section), the mean speed of agents was higher (1.63 m s−1), due to the fact that simulated agents were rarely impeded, did not encounter bottlenecks, and were free to accelerate up to their maximum speed. However, as we will see from our results, this did not affect the perception of the simulated crowds.In order to calibrate our simulation , we selected 20 clips at random from the Edinburgh dataset (each of 60 s duration), and calculated the average walking speed of pedestrians observed traversing the Forum. The distribution of speeds is shown in For the comparison experiments, we randomly selected six clips taken from the Edinburgh dataset (the number of clips is the same as in ); each w3.3.In order to produce the simulations to accompany each Edinburgh clip, we simulated pedestrian movement using the Vadere package . This pacrowd motion model. This defines the rules of interaction between individuals (e.g. avoidance), and between individuals and their environment , as well as route choice behaviour and differential walking speed. Many different crowd motion models exist [social forces. Inspired by the fluid flow paradigm of Henderson [A crucial component of the simulation is the ls exist , but perenderson  and otheenderson  is a micenderson , PedSim enderson , SimWalkenderson  and Massenderson , and it enderson ,23, and enderson  recommenWe added small amounts of noise to the simulated trajectories in order to replicate noise in the real crowd data. As the Edinburgh individuals were detected by an overhead camera running at 9 fps, occasional faulty detections caused very short-term errors in the extracted trajectories. Once rendered, this caused individuals to appear to rapidly ‘flick’ between two headings. As we had no reliable way to quantify the  amount of noise in the trajectories, we adjusted this by eye until the apparent noise in the simulated data matched the noise level observed in the real data. At any time-step, a simulated agent had a 15% chance of temporarily ‘flicking’ their heading by a randomly selected value up to 45° (without changing their trajectory). Importantly, as we will see from the results, the addition of this noise had no effect on how the simulated crowds were perceived.A second artefact of inaccurate detections was that some trajectories had missing sections for several time steps; once rendered, these individuals would temporarily disappear from the frame and then reappear. To fix this, we automatically detected such situations and interpolated coordinates for the missing time-steps when parsing the Edinburgh dataset. We also increased the number of frames per second of both sets of trajectories , from 9 to 72, by interpolating coordinates. This enabled smooth video playback for the purpose of comparisons. Finally, pedestrian trajectories sometimes include ‘swaying’ motions resulting from the gait of individuals; however, we did not see this in the Edinburgh data.3.4.The trajectories of both the simulated and real individuals in each pair of clips were rendered in a uniform fashion, using a tool coded in Java. This allowed us to produce ‘top-down’ visualizations of both real and simulated clips that were identical in appearance, with individuals represented as filled circles, and headings depicted by an arrow .Figure patterns of behaviour in the crowd. Additionally, at least one study has shown that crowds that are viewed from the top down are perceived as being just as realistic as those viewed from eye level [The use of abstract, simplified shapes and a top-down, two-dimensional presentation is relatively common in crowd studies ,43–47, aye level .3.5.polarization and nearest-neighbour distance (NND). The first metric is particularly useful for describing the existence of large groups who might be moving together along the same heading (e.g. from a lecture towards an exit), while the second metric is used for estimating overall crowd density.In order to assess the accuracy of our simulations, we calculated several statistical properties for both their outputs and the Edinburgh observations on which they were based. We used two metrics (as in ); polariN is the number of individuals in the frame, θi is the heading of each individual.Polarization measures the level of ‘order’ in a crowd, in terms of the heading alignment of members. Polarization is zero when the crowd is completely disordered (everyone is pointing in a different direction), and has a maximum value of 1 when all members of the crowd have the same headingN individualsdi is the nearest neighbour distance between point i and the closest individual in the frame, as calculated by the standard distance formulaNearest-neighbour distance (NND) measures the level of ‘clustering’ in a crowd. The average NND for a single ‘frame’  is calculated from the sum of nearest-neighbour distances of all In order to confirm that we did not introduce implementation-specific bias by choosing a specific software platform, we compared the outputs of Vadere and JuPedSim , an alteThese results confirmed that crowd simulations in Vadere and JuPedSim display similar properties in terms of both NND and polarization, so we selected Vadere as a representative example of crowd simulation packages in general .real crowds, which confirmed that they are essentially indistinguishable in those terms. In Importantly, the statistical properties of the simulations also matched the general properties of the 3.6.identify the real crowds when they were presented alongside the simulated crowds, and the second trial tested the ability of participants to classify crowds as either ‘Real’ or ‘Simulated’. We define ‘score’ in terms of correct identification/classification of the real crowd; so a score of zero means that a participant failed to identify/correctly classify any of the real crowds. All trials took place at the beginning of a class, for which prior permission was obtained from the tutor. Students were informed about the nature of the experiment, and told that they were under no obligation to participate. Answer sheets were distributed, which consisted of a simple numbered list of tick-boxes. Participants were asked to optionally specify their age and gender. At the end of the trial, participants were also asked to provide some optional narrative notes on any distinguishing features they noticed that allowed them to tell the real crowd from the simulated crowd. Each trial  took around 10 min.We performed two trials; the first trial tested the ability of participants to 4.4.1.We recruited 384 undergraduate students from Northumbria University, distributed over nine groups taken from a mixture of computer science and engineering courses. Of the participants who supplied their details, the gender distribution was 78.83% male, 18.66% female, 2.5% non-binary/other and the average age was 20.7 .http://drives.media/google857, and the real crowds are A, A, B, A, B and B .For each pair, the real and simulated videos were randomly assigned to position A (left) or B (right), and these were combined side-by-side into a single video. Individual videos did not ‘loop’, and were made up of the first 30 s of the real and simulated crowd clips in each pair. The total duration of the video, showing a total of six comparisons, was 3 min 18 s (including a 3 s pause between each pair). The video is available at The mean score for participants, across all comparisons, was 1.6 out of 6 (26.7%). That is, participants performed significantly less well than if they had guessed at random. The overall distribution of scores is shown in partition all six pairs of videos into two sets. This answers, in the affirmative, the question concerning the ability of individuals to distinguish between real and simulated crowds, even when they have very similar statistical properties.If the real and simulated crowds were genuinely indistinguishable , then we would expect roughly 3% of participants (around 12 people) to either guess none correctly, or to guess all six correctly. What we actually found was that over 40% of participants  obtained a score of either zero or six. That is, those individuals were able to correctly partition videos along the lines of ‘real’/‘simulated’, but were unable to correctly classify  the crowds. This is a much stronger version of the result obtained in [However, a highly striking result is that the most common score, by far, was zero. A significant proportion of participants (36.46%) failed to identify a single real crowd. Only 3.65% of participants obtained a perfect score of 6. The important implication of this is that participants were reliably able to ained in , where pWe now briefly explore secondary features of our findings for the first trial. The results for each comparison are shown in In terms of variation across groups , Group 14.2.individually, in a randomized order, and participants were asked to classify each one as either ‘Real’ or ‘Simulated’. For this additional trial, we recruited 156 engineering Masters students from Northumbria University, taken from a single unit cohort. Of the participants who supplied their details, the gender distribution was 93.59% male, 3.85% female, 2.56% non-binary/other and the average age was 23.77.In order to check for bias that might be introduced by showing movies side-by-side, we performed a second trial (with different participants) using exactly the same movies as before; however, this time, the movies were presented For this trial, the mean score was 4.47 out of 12 . The distribution of scores is shown in To summarize, we found that the identification task was considerably more difficult when videos were presented side-by-side, as opposed to individually. However, neither mode of presentation allowed participants to perform better than random guessing. Taken together, the results of both trials suggest that off-the-shelf simulations ‘fail’ the crowd Turing test, in that they actively ‘mislead’ untrained experts into believing that real crowds are actually simulated, and vice versa. We now consider why this might be.4.3.In this section, we analyse the free text supplied by participants. We focus, in particular, on the large number of participants in the first trial who scored zero, as (a) they consistently misidentified the real crowd, and (b) the number of comments supplied by participants in the classification trial was relatively low, and they were generally consistent with the comments made by participants in the first trial. We highlight themes and specific comments that may shed light on the assumptions and preconceptions held by these individuals, that led them to consistently ‘flip’ the real and simulated crowds in their perception.changes of movement in the real crowd, which many participants incorrectly attributed to the simulated (fake) crowd. Versions of this included ‘Fake changed direction too quickly’, ‘Fast change suggests fake’, ‘Generated crowd had too much random movement’, ‘Real seemed to change direction gently’. Although the average speed of the simulated agents was higher than that of the real people, participants singled out rapid movement in the Edinburgh  videos as indicative of artificiality . Overall, 72 participants mentioned a variant of this type of observation. The underlying assumption here is that real people move smoothly, at a uniform speed, and do not tend to deviate much from their chosen path.The first theme that emerged concerned rapid or ‘random’ avoidance; many participants incorrectly assumed that real people would avoid close contact with one another, whereas the simulated individuals would ‘overlap’ or collide. Representative quotes included ‘Simulated people collided, real crowds avoided each other’, and ‘People overlapping’. In reality, the opposite is true, as the real dataset contains multiple instances of individuals coming into close proximity. Moreover, the social forces model explicitly tries to keep individuals apart unless close proximity is unavoidable, so the behaviour (distance keeping) that participants attributed to real people was actually an in-built feature of the simulation. This theme was mentioned by 22 participants.A second common theme concerned perceived intentionality and group-level behaviour; many participants believed that ‘On the whole, people have relatively smooth and intentional paths’ , ‘Real crowds don’t really stand around’ , and ‘The real ones knew where they were going’ . Variations on this theme were mentioned by seven participants. The interesting thing here is that participants (incorrectly) ascribed clear human intentionality and purpose to the simulated agents , and failed to acknowledge it in the actual humans that were observed.Perhaps the most profound observations concerned Overall, we found that participants believed that individuals in crowds are orderly, purposeful, respectful of personal space, and consistent and uniform in their speed and direction. In fact, all of these characteristics were features of the simulation. Participants also failed to recognize features of real crowds, such as rapid changes in speed or direction, close proximity of individuals, and stationary groups/individuals, all of which were discounted by participants as being ‘glitchy’ or ‘unrealistic’.5.In this paper, we presented a Turing test for crowds that allowed us to investigate issues of believability in crowd simulations by comparing them with visualizations representing data obtained from real pedestrians. We performed trials with over 500 university students, and found that, while the students were generally able to discriminate between ‘real’ and ‘artificial’ crowds, they were unable to correctly label them.We acknowledge several potential limitations of our study; the use of students as test subjects is the subject of ongoing debate , and theIf (as we might expect) the experts are able to reliably identify the real crowd, then this immediately suggests a mechanism for ascertaining the minimal set of crowd features that are necessary to ‘pass’ the test. If, for example we identified that ‘group-level movement’ was a ‘flag’ for the experts, we might include such a behaviour in the simulation and re-run the trial with a second group of experts. If the experts are then less able to tell the difference between real and simulated crowds, then we might conclude that group-level behaviour constitutes an important feature that should be included in simulations. This would represent a formalized methodology for implementing a number of recommendations that have been recently made by a number of crowd scientists, who call for the integration into software of a wider range of psychological and interpersonal processes –30. Thes


Residents living and dying in long-term care (LTC) homes represent one of society’s most frail and marginalized populations of older adults, particularly those residents with advanced dementia who are often excluded from activities that promote quality of life in their last months of life. The purpose of this study is to evaluate the feasibility, acceptability, and effects of Namaste Care: an innovative program to improve end-of-life care for people with advanced dementia.This study used a mixed-method survey design to evaluate the Namaste Care program in two LTC homes in Canada. Pain, quality of life, and medication costs were assessed for 31 residents before and 6 months after they participated in Namaste Care. The program consisted of two 2-h sessions per day for 5 days per week. Namaste Care staff provided high sensory care to residents in a calm, therapeutic environment in a small group setting. Feasibility was assessed in terms of recruitment rate, number of sessions attended, retention rate, and any adverse events. Acceptability was assessed using qualitative interviews with staff and family.The feasibility of Namaste Care was acceptable with a participation rate of 89%. However, participants received only 72% of the sessions delivered and only 78% stayed in the program for at least 3 months due to mortality. After attending Namaste Care, participants’ pain and quality of life improved and medication costs decreased. Family members and staff perceived the program to be beneficial, noting positive changes in residents. The majority of participants were very satisfied with the program, providing suggestions for ongoing engagement throughout the implementation process.These study findings support the implementation of the Namaste Care program in Canadian LTC homes to improve the quality of life for residents. However, further testing is needed on a larger scale. As the Canadian population continues to age, more people will die in long-term care (LTC), with estimates as high as 52.3% of residents dying in their LTC home by the year 2020 , 2. WithEfforts to promote quality of life for residents with dementia have been neglected, particularly for those with advanced dementia. Moreover, rates of pain in this vulnerable population can be as high as 83%, since pain is often under-recognized or and undertreated –17. PoteSome residents with advanced dementia are at risk of being marginalized. “Silent residents”  experienA new program, called Namaste Care, has great potential to improve quality of life, dignity, and comfort for LTC residents by engaging them in meaningful and therapeutic activities throughout the later stages of the disease trajectory –27. EmerWhat are the feasibility, fidelity, and acceptability of the Namaste Care intervention in Canadian LTC?2.What is the potential effect of the Namaste Care intervention on quality of life, pain, medication use, and medication costs in residents with moderate to end-stage dementia over 6 months?This study used a mixed-method approach which combined both quantitative and qualitative methods to address the various research questions that, in combination, addressed the same overriding study goal . Since tA qualitative descriptive design was used for the post-implementation component (acceptability of the intervention), to explore perceptions about the intervention, to retrospectively examine perceived effects, barriers and facilitators to implementation, strategies to improve implementation, and sustainability of the intervention. Ethical approval for the study was approved by two universities .This intervention study was conducted in two, not-for-profit LTC homes: one in southern Ontario, a 127-bed facility (site 1), and a second one in Saskatchewan, a 60-bed facility (site 2). Both homes had a high proportion of residents with moderate to severe dementia and strong leadership investment in this project. Inclusion criteria for residents were as follows: over the age of 65, a diagnosis of dementia, English speaking, and a score of less than 40% on the Palliative Performance Scale (PPS) ) and median (minimum-maximum) for continuous variables and count (percent) for categorical variables Table . The ana SAS 9.2 .Table 1For the acceptability component of the study, the qualitative software program Dedoose  was usedThe average age of participating residents was 86.4 (SD = 9.3) years. The majority were female (87.1%) and widowed (63.3%). Participants had lived in LTC for an average of 3.6 (SD = 3.8) years. The average Charlson Comorbidity Index (CCI) score was 4.3 (SD = 1.7), with the most prevalent conditions (besides dementia) being rheumatic or connective tissue disease (71.0%), hypertension (67.7%), and depression (35.5%).n = 28) and volunteers (n = 6) who were interviewed were female (94%) and the median age was between 45 and 54 years of age (n = 29). They had been working with LTC residents with dementia for an average of 14.8  years. Out of the ten family members interviewed, four were female and six were male. The median age within the sample of family members was between 55 and 64 (n = 10) years, and their loved one had been a resident in LTC for 2.9  years.For the acceptability interviews, the majority of staff  88.6% of residents who were eligible consented to participate or their proxies consented on their behalf Fig. , (b) 90.Intervention fidelity was also assessed in terms of the average percent of residents who received the components of Namaste Care at every session they attended Table . The majt = 0.86, p = 0.40; see Table t = 0.82, p = 0.42). Further, medication use remained relatively constant (measured by the MQS). Of note, there was a statistically significant decrease in antidepressant use . Medication costs decreased slightly from baseline to post-intervention . Each of these themes is described in more detail below.Like there seems to be … a higher level of consciousness for the people that are here. Like they seem to be more able to recognize you, talk with you and you know even if they don’t talk but a gesture or whatever they can do. That level seems to be quite a bit higher with those people. I think it’s possibly because they are a little bit more satisfied (son)Our study findings found positive experiences and benefits of Namaste Care as described by health care providers, volunteers, and family members. There are a number of “positive moments” where both family and staff described residents’ mood as improved during and after attending Namaste Care. During Namaste Care, participants described “in-the-moment” changes where Namaste Care seemed to “bring out the personality” of the residents, whereas before, staff and family felt residents were previously unaware of their surroundings. Some participants made comments that they felt residents were more alert in the Namaste Care room and engaged more with staff and family. A son of a resident stated:I remember the care aides bringing in one resident … they said she was very sad, quiet, and very emotional that day. They weren’t sure if she should be there and I said, “sure bring her in … and I would say after lotioning and talking, and the music going and doing her hair and makeup, she started talking nonstop and she was laughing. By the end of it she was singing out loud with me. (PSW/CA)The majority of participants interviewed described how the Namaste Care program appeared to improve residents’ mood. For example, a personal support worker/care aide stated:Family members expressed similar comments, stating:We all seem to agree that mom seems to be less anxious … .I had never seen mom smile like that -this huge big smile on her face. (daughter)Another family member stated:But mom enjoyed it and from observing other residents that were involved I could see where they really enjoyed it. Especially when you watched the smiles on their faces, and the enjoyment of the music. Some of them I had never seen them smile before or even had movement and all of a sudden they were tapping their toes and enjoying the music and doing a bit of exercises, and seemed very happy there (daughter)The change I’ve seen in her is that she will look you in the eye when you come in the room, and she will smile … I’ve just seen it continue from there. She laughs at us, and she has a smile. She sits with her eyes open and just a calm look on her face. She doesn’t smile all the time but she has her eyes open and she’s pleasant. (volunteer)A volunteer in the Namaste Care room commented on similar observations of residents. For example, one volunteer stated,Now that Dad’s gone we had talked about possibly moving her to another LTC home where we both live. But we know that, that’s [Namaste Care] is not available there and that’s why … that’s a big reason why I’m wanting to keep Mom here. Because we know that it’s a good program. (child)For some family members, the Namaste Care program had an impact on their views of the LTC home itself, where one participant describes how it helped them decide where to locate the resident:Not like under pressure. I can come every other day and not feel bad, cause I know she has this going on. (daughter)Our study found that the majority of family interview participants expressed how participating in the Namaste Care program helped them feel more empowered and engaged in caring for residents who have advanced dementia. Some of the quotes from family members include:I can see that it’s very helpful. It’s something I would like to see continue. I think, wow, if I get to this point I would like something like this to be in place. I go away from here feeling such joy, you know? It’s not all about me but I’m getting the joy from just doing and helping. I can see that it’s making a difference. When you get a smile from somebody that is so sweet. (daughter)I’ve only been doing it the 4 weeks, and I find that I usually get up excited in the morning to come, even the first day. I didn’t even know what to really expect, but it is something that seems to touch my heart to be able to help out this way. (daughter)Our study findings, based on field notes and staff interviews, highlighted perceptions about the barriers and recommendations for improvement when implementing Namaste Care in LTC, in particular areas around staffing, training, timing of program, and adverse events that occurred during the implementation of Namaste Care.When the program was first implemented, the LTC homes found it difficult to execute with the current contingent of staff. We originally thought that the program could be achieved with nurses and personal support workers running the program. When we had meetings with the LTC homes, we found that more delineation of roles was needed and that the LTC homes preferred to have personal support workers and recreation staff implement the program. In order to successfully implement the program, we had housekeeping porter residents to and from the Namaste Care room, dietary helped with the tracking and distribution of liquids, and housekeeping was scheduled to help launder residents’ Namaste Care blankets. One reoccurring barrier to Namaste Care that was brought up was staff burden over time. This involved the fact that the program does not require any extra staffing and simply redistribution of staff members. Many staff members, including recreation therapists, identified that they felt they are already overworked and do not have enough time to do any more. The personal support workers/care aides did not like to leave their co-workers on the floor alone while they went to Namaste Care for safety reasons  and fear they were neglecting the other residents in the home.Being that is a very busy time of the morning, and getting people there you know with the care aides it is hard to get people there in the morning, and we don’t have the staff (recreation therapist)As the program was being implemented, we quickly realized that a training program needed to be established for new staff who would be implementing the program. As a result, we developed a staff training toolkit and posted videos of Joyce Simard’s training sessions on the LTC homes online learning portals. In this way, staff were able to access background training materials before shadowing staff in the Namaste Care room.The Namaste Care program was originally designed to run for 4 h a day, 7 days a week. Due to insufficient staffing on the weekends, it was immediately realized that the program could only be run from Monday to Friday. Although the program originally ran for 2 h in the morning and 2 h in the afternoon, this changed to 1.5 h each in the morning and afternoon for one of the sites. The decrease in time was caused by staff shortages. The program’s time was also impacted when it had to shut down due to infection control outbreaks. Program closure was implemented in order to ensure that diseases were not spread between floors or buildings. The time of the program for individual residents was also adapted for individual resident preferences. Some residents preferred to attend only in the afternoon, as they liked to sleep in. Other residents who were prone to bedsores only attended in the morning or afternoon in order to decrease the chance of bedsores.Another barrier or challenge that staff participants described was related to adverse events such as incidence of skin breakdown. This issue was raised at both sites:well it doesn’t hurt them, the residents. Except there are some that can’t go twice a day because they have skin break down, I mean they just can’t handle it body wise (PSW/CA)This study demonstrated that implementing the Namaste Care program in Canada was feasible but required sessions to be shortened and some shifting of staff roles to help implement it, which in some cases was very challenging. Our study findings show that, with current staffing levels, implementing Namaste Care the way it was intended  placed a great deal of demand on staff. However, staff and family members highly endorsed Namaste Care, demonstrating its acceptability in LTC. Finally, our study showed positive trends for improved outcomes, such as resident quality of life, and decreased pain and medication use.Although this study showed that Namaste Care could be implemented within “real-world” conditions with shortened sessions, the feasibility of implementing Namaste Care in LTC could be greatly enhanced with support from others, for example, family members, students, and volunteers. Without the addition of hiring extra staff, our study findings highlighted several conditions that need to be in place to allow this to happen. Based on our initial interviews with LTC staff that occurred before we implemented Namaste Care, staff reported that they should be involved in decision-making to adjust the program launch and have more choice in its design and selection of residents who would be appropriate for it , 33. We Most importantly, our study findings highlighted that in order for Namaste Care to be successfully implemented, staff need to make it a priority. To do this, staff need to be supported by the leadership within the LTC home to make it a priority. This may include shifting other tasks assigned to staff to offset the demands of implementing Namaste Care, or prioritizing other resources  to help implement it. If not, Bunn et al. suggest that Namaste Care may require additional resources to implement it, particularly at the initial launch . AndersoIt was clear that some of the components of Namaste Care were implemented more often than others for residents, such as listening to music, having hands and face washed, being given a massage, or drinking a beverage. These more commonly implemented activities are consistent with those that were identified from a realist review and stakeholder interviews as being the core elements of Namaste Care . A progrOur study findings revealed positive trends in study outcomes with implementing Namaste Care, although only decreased use of antidepressants was statistically significant. Our qualitative findings support the quantitative outcome findings, in that many positive moments were described by staff and family members during Namaste Care. These moments, including residents speaking, being more interactive, smiling, and not seeming depressed or “emotionally hurt” have been reported in other Namaste Care research as well . It is iDespite these positive trends in our study outcomes, we did observe some adverse events  that occurred in our study participants, but we are unsure if these events occurred due to implementing Namaste Care or whether they would have occurred anyways. Still, these adverse events are concerning. In light of these findings, more focused attention is needed to minimize them in future work which could include (a) using special chairs for high-risk residents who may be prone to skin breakdown and (b) regular skin assessments for residents that are included as a component of daily Namaste Care activities.Our findings demonstrated that Namaste Care contributes to person-centered care for residents with advanced dementia, consistent with other literature . Davies Although the qualitative interview findings with family members revealed resounding support for Namaste Care, our quantitative data, one of our feasibility indicators (family visits), showed limited family involvement during the Namaste Care sessions. Qualitative findings showed that Namaste Care reassured family in that they knew the resident was receiving meaningful activity/engagement, which allowed them to “take a break” or some respite time which can be positive. Alternatively, perhaps Namaste Care could provide an opportunity for some meaningful engagement between families and residents, as opposed to situations where family visitation is distant and stressful, resulting in decreased frequency and duration and leaving people with dementia to enjoy limited to no social interaction outside of those provided during the course of routine clinical care –58. AdvaThere were some limitations to this study. First, our small sample limited the power to show any statistically significant changes in the outcome measures. However, we have determined confidence intervals which will be used to calculate estimated sample sizes in future study, consistent with a goal of conducting definitive studies. Also, the two homes where Namaste Care was implemented were very enthusiastic about its implementation which likely contributed to our positive findings related to feasibility. It may be less feasible to implement Namaste Care in other homes who have less buy-in and support for the program.In summary, this feasibility study provided initial support for implementing Namaste Care in LTC homes who are enthusiastic about the program. Positive findings, including decreased antidepressant use and positive feedback from families and care providers, provide preliminary support for its effectiveness and its potential to improve the quality of living and dying for residents with dementia living in LTC. Future work is needed to explore how to engage and support family members in Namaste Care in meaningful activities with residents. In doing so, efforts may result in both improved quality of living for residents with advanced dementia and their family members who support them.


The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the “intelligence” nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance. The name  to date . The iniems (ES) . The fieems (ES) . This silgorithm . Later iinterest  explorininterest . Finallyinterest .During these years, AI has achieved great success in many different fields including robotics, speech recognition, facial recognition, healthcare, and finance . ImportaOur paper is organized as follows. In the next section, we discuss the desired and current status of artificial intelligence including the definition of “intelligence” and strong AI. Then we clarify frequently encountered misconceptions about AI. Finally, we discuss characteristics of methods from artificial intelligence in relation to machine learning and statistics. The paper is completed with concluding remarks.We begin our discussion by clarifying the meaning of artificial intelligence itself. We start by presenting attempts to define “intelligence” followed by informal characterizations of AI as the former problem is currently unresolvable.From the name “artificial intelligence” it seems obvious that AI dealswith an artificial–not natural - form of intelligence. Hence, defining ‘intelligence’ in a precise way will tell us what AI is about. Unfortunately, currently, there is no such definition available that would be generally accepted by the community. For an extensive discussion of the difficulties encountered when attempting to provide such a definition see, e.g., .human intelligence to define machine intelligence formally. The resulting measure is given byπ is an agent, K the Kolmogorov complexity function, E the set of all environments, µ one particular environment, π  ” . The latce (AGI) .Since there is no generally accepted definition of “intelligence” AI has been characterized informally from its beginnings. For instance, in  it is stFeigenbaum further specifies that “One group of researchers is concerned with simulating human information-processing activity, with the quest for precise psychological theories of human cognitive activity” and “A second group of researchers is concerned with evoking intelligent behavior from machines whether or not the information processes employed have anything to do with plausible human cognitive mechanisms” . Similarintelligent and smart behavior rather than on simple questions as represented, e.g., by classification or regression problems as discussed in statistics or machine learning. This also means that AI is not explicitly data-focused but assumes the availability of data which would allow the studying of such high-hanging questions. This relates also, e.g., to probabilistic or symbolic approaches  definition of “intelligence” nor do we have one succinct informal definition of AI that would go beyond its obvious meaning. Instead, there are many different characterizations and opinions about what AI should be .Given this deficiency it is not surprising that there are many misconceptions and misunderstandings about AI in general. In the following section, we discuss some of these.In this section, we discuss some frequently encountered misconceptions about AI and clarify some false assumptions.AI aims to explain how the brain works. No, because brains occur only in living  beings and not in artificial machines. Instead, fields studying the molecular biological mechanisms of natural brains are neuroscience and neurobiology. Whether AI research can contribute to this question in some way is unclear but so far no breakthrough contribution has been made. Nevertheless, it is unquestionable that AI research wasinspired by neurobiology from its very beginnings  learning algorithms that adjust the parameters of methods via learning rules. However, when implementing AI methods certain problems may require an optimization of the method in combination with computer hardware, e.g., by using a GPU, in order to improve the computation time it takes to execute a task. The latter combination may give the impression that AI is a technology but by downscaling a problem one can always reduce the hardware requirements, demonstrating the principle workings of a method, potentially for toy examples. Importantly, in the above argument we emphasized the intellectual component of AI. It is clear that AI cannot be done with a pencil and piece of paper, hence, a computer is always required and a computer is a form of technology. However, the intellectual component of AI is not the computer itself but the software implementing learning rules.AI makes computers think. From a scientific point of view, no, because similar to the problems of defining “intelligence” there is currently no definition of “thinking”. Also thinking is in general associated with humans who are biological beings rather than artificial machines. In general, this point is related to the goals of strong AI and the counter argument by Searle .Why does AI appear more mythical than machine learning or statistics? Considering the fact that those fields serve a similar purpose (see above) this is indeed strange. However, we think that the reason therefore is twofold. First, the vague definition of AI leaves much room for guesswork and wishful thinking which can be populated by a wide range of philosophical considerations. Second, the high aspirations of AI enable speculations about ultimate or futuristic goals like “making machines think” or “making machines human-like”.Making machines behave like humans is optimal. At first, this sounds reasonable but let us consider an example. Suppose there is a group of people and the task is to classify handwritten numbers. This is a difficult problem because the hand writing can be difficult to read. For this reason, one cannot expect that all people will achieve the optimal score, but some people perform better than others. Hence, the behavior of every human is not optimal compared to the maximal score or even the best performing human. Also, if we give the same group of people, a number of different tasks to solve, then it is unlikely that the same person will always perform best. Altogether, it does not make sense to make a computer behave like humans because most people do not perform optimally, regardless of what task we consider. So, what it actually means is to make a computer perform like the best performing human. For one task this may actually mimic the behavior of one human, however, for several tasks this will correspond to the behavior of a different human for every task. Hence, such a super human does not exist. That means if a machine can solve more than one task it does not make sense to compare it to one human because such a person does not exist. Hence, the goal is to make machines behave like an ideal super human.When will the ultimate goals of AI be reached? Over the years there have been a number of predictions. For instance, Simon predicted in 1965 that “Machines will be capable, within twenty years, of doing any work a man can do”  methods from AI (nor from machine learning or statistics) can be mathematically derived from a common, underlying methodological framework but they have been introduced separately and independently. In contrast, physical theories, e.g., about statistical mechanics or quantum mechanics, can be derived from a Hamiltonian formalism or alternatively from Fisher Information .Maybe the most interesting insight from Current domain of artificial intelligence, machine learning and statistics Finally, if one considers also novel extensions for all base methods from AI, ML and statistics one can summarize the current state of these fields as follows:This means that all fields seem to converge to simple question for high-dimensional data.(1) currently, no generally accepted definition of “intelligence” is available. (2) the aspirations of AI are very high focusing on ambitious goals. (3) general AI methods do not provide neurobiological models of brain functions. (4) addition: Also deep neural networks also do not provide neurobiological models of brain functions. (5) the current most successful AI methods, i.e., deep neural networks, focus on simple questions  and high-dimensional data. (6) AI methods are not derived from a common mathematical formalism but have been introduced separately and independently. In this paper, we discussed the desired and current status of AI and clarified its goals. Furthermore, we put AI into perspective alongside machine learning and statistics and identified similarities and differences. The most important results can be summarized as follows:Finally, we would like to note that the closeness to applications of AI is certainly good for making the field practically relevant and for achieving an impact in the real world. Interestingly, this is very similar to a commercial product. A downside is that AI also comes with slogans and straplines used for marketing reasons just as those used for regular commercial products. We hope our article can help people look beyond the marketing definition of AI to see what the field is actually about from a scientific perspective.


Information is a physical entity amenable to be described by an abstract theory. The concepts associated with the creation and post-processing of the information have not, however, been mathematically established, despite being broadly used in many fields of knowledge. Here, inspired by how information is managed in biomolecular systems, we introduce writing, entailing any bit string generation, and revision, as comprising proofreading and editing, in information chains. Our formalism expands the thermodynamic analysis of stochastic chains made up of material subunits to abstract strings of symbols. We introduce a non-Markovian treatment of operational rules over the symbols of the chain that parallels the physical interactions responsible for memory effects in material chains. Our theory underlies any communication system, ranging from human languages and computer science to gene evolution. Many concepts related to the treatment of information have ordinarily been used for centuries, but only rigorously defined within the context of information theory by the end of the 1940s . ExampleThe appropriate introduction of operational rules to construct bit strings is linked to the use of the concept of proofreading and, more importantly, to the establishment of conditions for useful editing . These cBiomolecular engines that process genetic information work under non-equilibrium conditions , but notWe previously formulated a thermodynamic framework for physical systems that carry information in the presence of memory effects  with genX with alphabet X and C in the exponent. Q is a normalization factor, as determined from C is recovered from the probability distribution by taking the logarithm to base a, namely, The probability distribution, C in the context of a string of symbols, as characterized by a directional, stochastic chain with memory [We next explain the convenience of expressing probabilities as in Equation . In parth memory . Let ν=xDefinition (Correctness)Let ν be a stochastic sequence of symbolic, random variables  correctness, Equation , which, Since the probability of a chain can be written as :(2)pν≡PrThe correctness is therefore an additive property of the subunits within the chain.R is associated with the thermal energy level, namely k is the Boltzmann constant and T the temperature. This suggests the modeling of function C as a strategy to introduce ad hoc the operational rules in purely symbolic systems, like in human communication. In this case, each individual contributes differently to the correctness since his/her own capacity to assimilate the operational rules of a specific language entails different protocols for their application, as reflected in the probabilities of Equation . Specifically, a stochastic sequence, R, the above formalism leads naturally to what is expected for probabilities, namely that The fact that N the number of sequences and The probability of a particular configuration in directionally-constructed stochastic chains  can now fined as :(5)Cν′ν≡Q the standard normalization. As with partition functions [In contrast, if we do not restrict how to access each final configuration ,19, the unctions ,19, the w and r, respectively.The formalism given by Equation  involvesA”, and the entropy, “H”, for single chains. Depending on whether we are writing or proofreading and editing, these functions read: A” and “H” in Equations ≡Rlons read: Aν(w)≡Rlo)≡RlogaQ,Hν(w)≡−loC in the absence (superindex w) or presence (r) of revision.Respective functionals can be constructed by taking ensemble-averages: ≡RlogaQ;1H(w)=−logC(w)≡Cνw,C(r)≡Cνr;A(w)≡Rlog)≡RlogaQ;H(w)=−logThe analogue of the energy conservation for ensemble-average phenomena yields:quations . The demquations –13) are are(13)Auations (C(w)=∂∂Bl∂∂BlogaQ;H(w)=∂∂RAThe following inequalities hold : (16)A.Condition 2 (Effective proofreading necessary and sufficient condition).The equalities take place when there exists no memory (see the independence limit theorem ). Note tCorollary 1 (Effective editing necessary condition and effective proofreading sufficient condition).Corollary 2 (Ineffective editing sufficient condition and ineffective proofreading necessary condition).Corollaries 1 and 2 are consequences of Conditions 1 and 2 after the use of Equation .We envision a system, either natural or artificial, that computes information by assembling characters in the same way as a so-called Turing machine and according to adopted rules, as characterized by the correctness. The characters are symbolic elements from an alphabet set, with the independence of the fact that they might have material reality, like atoms or molecules in a physical realization of the system. The alphabet, In the following, we model the copy of information in a binary-alphabet classical system .The edition potential difference  is alwayn), These appear to be the general trends for the absolute value of the correctness potential difference: We have shown that information strings can be studied in analogy with the Hamiltonian treatment of stochastic chains with memory. We have introduced the correctness, which parallels the concept of energy, and have formulated conditions for effective proofreading and editing. When considering thermodynamics in a physical realization of an information system, it is important to note that time is implicitly included in our formalism, either by conceiving of indefinitely long intervals or by addressing this coordinate in the evolution of the correctness function.Revision, as introduced in this report, entails an equilibrium thermalization in the physical analogy, hence comprising an infinite number of proofreading and editing rounds. The problem of considering one or a finite number of finite-time revisions involves a non-equilibrium modeling analogue.This work represents a round trip: from information theory to stochastic thermodynamics, non-Markovian dynamics and molecular biophysics, and back. This trip affords for the first time the introduction of writing, proofreading and editing in information theory, with a sufficient degree of conceptualization to be used in social and natural sciences, including the physics of stochastic systems and nanoscale engineering. Our formalism enables semantic roots to bit sequences, which are important in gene evolution analysis and in context-sensitive error correction algorithms for computational linguistics, currently based on statistical occurrences.


The importance of mobile phones has become one of the new research topics in health professions education due to the ease of access and flexibility. Although novel approaches to health professions education recommend the use of educational technologies, such as mobile applications, a limited number of studies have been conducted with regard to learning anatomy through mobile applications. Considering the increasing needs of medical students for mobile technology to meet their educational needs, wants and desires, we decided to explore the features of an anatomy mobile application.This qualitative study was conducted in two stages of holding focus groups, and an expert panel session. Students of basic Medical sciences, and faculty members of anatomy at Iran University of Medical Sciences formed the research participants. Semi-structured interviews and note-taking were used to collect the data. Moreover, Brown and Clark methods were used for thematic analysis. Finally, four criteria presented by Lincoln and Guba for qualitative studies were used to ensure the credibility, confirmability, trustworthiness and transferability of the data.Based on the data analysis, 37 codes that could be used to design anatomy mobile content for medical students were extracted. These features were categorized into eight main themes of “visual richness”, “scientific comprehensiveness”, “auditory richness”, “affordability”, “user-friendliness”, “self-assessment”, “interactive content” and “user support”.This study explored the features of an anatomy application that can be used by educational app developers. Anatomy departments at Medical Universities, policymakers, and curriculum planners in the field of medical education can also adopt the findings of the present study. The world has recently witnessed drastic changes in teaching methods which pose unavoidable challenges to traditional education systems. Information and communication technology, as a novel phenomenon in the world today, has deeply altered various aspects of education in general and teaching and learning process in particular , 2. In tAnatomy as a basic course for medical students includes different sections with several components. The content of the course focuses on the structure of and the relationship between different parts of the human body . LearninIn anatomy classes in Iran, a given topic is first introduced through a lecture with the aid of slides or a short video clip. Next, the topic is more elaborated through small group learning method with the supervision of an instructor. Then, the students work on anatomical moulage, and virtual dissection table. Finally, they work on a cadaver. Medical students in Iran, as reported in the focus group, mostly use Netter’s Atlas of Human Anatomy , which fThe development of a mobile app on the basis of the local educational needs for learning anatomy would increase students’ interactions, and motivation to improve their learning, and engage them in the process of learning more effectively . The useThe current approach to medical education recommends, the use of educational technologies, including mobile phones because of the potential convenience, and ease of access of these tools . HoweverThis qualitative study was conducted at the school of medicine, Iran University of Medical Sciences (IUMS) in 2019. A purposive sampling was carried out from the population of undergraduate medical students, and anatomy faculty members.It was decided to have Focus Group (FG) and Expert Panel (EP) sessions to collect data for mobile apps features which could be deployed for designing and developing such an app in the future. FG is typically performed because the participants have similar knowledge and ideas on a given topic. FG is believed to provide richer information than individual interview due to its group dynamics and interactions among participants. It shows how the participants feel about or behave towards a topic, and is recommended for generating ideas. It could be used alone or accompanied with other techniques –18. In aThe first FG session was held upon obtaining the student consent form. The participants consisted of nine sixth semester medical students, who had passed anatomy courses  and were familiar with the topics. In the first FG session, a list of their expectations was developed. However, to receive more information and to confirm some data, another FG session was held with eight participants. On the whole, there were 17 participants, 10 males and 7 females, 21–22 yrs.). For the inclusion and exclusion criteria see Table –22 yrs..The trustworthiness of this study was supported by four criteria: credibility, dependability, confirmability, and transferability proposed by Lincoln and Guba . We reco, provided by the research participants whose comments are divided into smaller parts to extract themes. To become familiar with the data, on the basis of Clarke and Braun’s model, the researchers read and re-read the data several times to find the preliminary ideas, and extract codes in the next steps of analysis. Afterwards, the codes were categorized, and then primary or secondary themes were specified for each category. Ultimately, the final or major themes were extracted and defined. Thereafter, the final report was tabulated. For the data analysis, several meetings were held with the research team, including the supervisor (AD), advisors (SB) and (ZS), mediator (MM), and one of the facilitators (SA). In each meeting, the problems were discussed and resolved, the differences were reconciled, and the decisions were made to assist accurate analysis. However, there were some ambiguous points made by the participants. Therefore, member check was performed; the participants were contacted individually through phone calls, social networks, or in person and were requested to explain some confusing points. In the re-check part, the complementary and clear explanations of the participants on ambiguous points were provided.The data resulting from the FG sessions were analyzed by using thematic analysis as the most common technique for data analysis , based oIn the next step, an EP was held with five anatomy faculty members. The supervisor (AD), advisors of the project, a software engineer, the facilitators (SA) and (MK), and the mediator (MM) were present in the session. A summary of the topics was discussed and the goals were made clear to the participants. Moreover, the process of the research was explained, and the report of the FG recorded by the team was presented. Each members of the EP was asked to discuss the themes identified, and comment on them. Then, a polling of agreement was performed by vote on approving or disapproving the items. The discussions were recorded by using a voice recorder and then transcribed verbatim. Furthermore, the facilitator (SA) took notes. The other facilitator (MK) was present for polling the votes. The items were presented by the mediator (MM). If there were any items which needed technical advice for approval, the softer engineer would comment on them. The session took about 50 min, and was held at the department of medical education in the medical school of IUMS. Figure In the analysis of the FG data, 121 ideas or preliminary codes were initially obtained. Then, by eliminating similar, overlapping, or repeated codes, 30 codes were specified. The codes were compared and categorized on the basis of their similarities and differences, resulting in 11 sub-themes which were finally classified under 8 themes. These themes were then discussed in the EP. Analyzing the data of the FG, we were able to identify some codes denoting the same topic; the similar codes were then assigned to one sub-theme.Visual features of the app were very important to the participants; for example, Participant 7 said: “Being three-dimensional makes it great to see all the parts we want”. Similar codes focusing on visual features were titled “appropriate visual design” as a relevant subtheme. Other codes, related to another category, were allocated to the sub-theme “educational clips”. Eventually, upon further analysis of the codes and sub-themes, it was decided to classify these two sub-themes under a general theme titled “visual richness”.It should be based on presenting, organs, systems, and region, or if it is made for the students of a university, it will be based on the educational programs. It's much better if it's based on the topics and the lessons that are offered by the anatomy departments.Two codes emerged from students’ emphasis on curriculum, and were assigned to the sub-theme “credible materials and curriculum”. Some other related codes were assigned to the sub-theme “provision of comprehensive scientific content”, as well. Then, it was found that the two sub-themes were similar and could be allocated to the same category; thus, these sub-themes, due to their similarities, formed the theme “scientific comprehensiveness”. The students had different ideas about the auditory feature of the application. Here are three excerpts:It should only be in the form of pronunciation, so that we can understand the correct pronunciation of units, such as nerves or muscles. [Participant 6]In general, if the pronunciation of the units is given it is excellent. [Participant 9]If possible, the sounds are in the form of a link on a separate site so that someone can choose, especially sounds that have long descriptions. [Participant 4]The codes related to the topic of “sound” were allocated to the sub-theme “optional audio feature”. By reviewing the data and the sub-themes, the final theme called “auditory richness” was formed.Other features mentioned by the students included: “the source of the scientific content”, “the extent to which the details are presented”, and “how comprehensive the functions are shown”. Here is what participant 10 said:The price of the program is very important to be reasonable.There were other related codes which were categorized under the theme “user-friendliness”. Moreover, similar codes were categorized under the sub-theme “relevant tests”. Eventually, this category was assigned to the theme “self- assessment”. Some other codes belonging to the same category were titled “interactive instructional design” which was then changed to “interactive content”. There were two other related codes, which were classified as the sub-theme “having a support/guide option” for the theme “user support”. The results are shown in Table Another code belonging to a separate category, “reasonable price”, was put under the sub-theme “economical”, which was later changed to “affordability”, based on the students’ statement about the reasonable price of the application. Here is what Participant 1 said:As for the EP, the recorded session was listened to, and reviewed several times to facilitate the transcription process and to have a good understanding of the content of the codes. After the transcription process, the data were compared with the notes taken during the interviews, and both were examined carefully. Although the EP initially discussed some codes, they eventually confirmed all the codes extracted from the FG. However, they added some new codes (seven codes) to the previous ones . They investigated the status of mobile apps in terms of health-related behaviors and used a framework known as Persuasive Systems Design model to evaluate the features of mobile apps. Consistent with our results, features such as “reliability” and “credibility of the content” were extracted in that study . By refeAnother theme extracted in the present study was “auditory richness”. Considering this theme ensures that the app is rich in terms of sound features. This theme contained a sub-theme entitled “having a sound option”, with three components: “having a loud enough sound”, “not having sound”, and “offering the pronunciations of words”. It means that learners can use the content of the app based on their own preferences. The findings are in agreement with those of the study by Liao et al. (2017) who investigated the essential and attractive functions used for promoting sports skills in mobile apps and found that the features of such apps could influence the quality of the users’ perception . HoweverThe theme “affordability” consisted of a sub-theme of “being economical”, i.e., having an appropriate, low or reasonable price. This sub-theme indicates that the app must be affordable for the users so that it can be easily accessed by all or most of the learners, because students, who are the main users of this app, do not have an income. This finding is consistent with that of the study by Nitsch et al. (2016) who found affordability as an important feature of the apps . HoweverBased on our findings, another theme is “user-friendliness”. The codes belonging to the sub-themes “customization and” and “content design” include: “having a reasonable file size”, “not being time-consuming”, “ease of use”, “containing necessary content”, “providing written explanations”, “having a labeling option”, “having language options”, and “not looking cluttered”. User-friendliness means that everything should be designed on the basis of the end users’ preferences, i.e., the students. This will result in an acceptable app and promote learning. The results of our study are in accord with those of the study conducted by Zilverschoon et al. (2019). They compared the features of electronic apps for teaching 3D anatomy to provide a guideline for the selection of appropriate apps. They found non-commercial apps to be promising in terms of ease of use .The next theme is “self-assessment”. When using this app, the users should be able to assess their own strength and weaknesses and improve their performance. A test or quiz provided at the end of each topic can help learners assess themselves and resolve their weak points. This finding is consistent with the results reported by Chi Yan Hui et al. (2017) who examined the use of mobile apps for helping self-management in patients with asthma. The study was conducted to identify the features related to clinical effectiveness. The data analysis revealed several features, including the features of showing questions and feedback .Another theme was “having an interactive content”. The “zoomability”, “separating different parts”, and “having search option” are the related items in this category. These findings are also emphasized in the study by Louise et al. (2014) who worked on complementing the teaching of anatomy by using an anatomy app. They reviewed 27 anatomy apps and found that features such as “having a zoomability on each anatomical structure” and “ease of separating a structure”, and “explaining each part separately” were positive features highlighted in some popular apps .Based on the findings, “user support” is another theme with the sub-theme of “having a support” or “help option”. The existence of a support or guide in the app allows the users to resolve the problems they encounter while using it. However, few students mentioned that it was not necessary to have such a support, because in the case of an ambiguity, one can easily find the answer from the Internet. Similarly, Crook et al. (2017) investigated the interface of a mobile app for individuals with communication disorders and found that the existence of ready messages for support was a major issue in apps which deserved attention .The findings of the study revealed eight features including “visual richness”, “scientific comprehensiveness”, “auditory richness”, “affordability”, “user-centeredness”, “self-assessment”, “interactive content”, and a “user support”. These findings can assist educational mobile app developers to design anatomy or similar apps in the field of medicine. In addition, departments of anatomy can benefit from the findings of this study to be aware of students’ needs and expectations in anatomy courses. The findings can also help policy-makers and curriculum developers in general, and policy-makers in the domain of e-learning and mobile learning in particular, become familiar with the students’ expectations, and their educational needs, and preferences. Another study, in which participants from other universities are included, is suggested to increase the generalizability of the findings. It is also recommended that a survey study be conducted on the basis of the findings of this study.


Living systems are open systems, where the laws of nonequilibrium thermodynamics play the important role. Therefore, studying living systems from a nonequilibrium thermodynamic aspect is interesting and useful. In this review, we briefly introduce the history and current development of nonequilibrium thermodynamics, especially that in biochemical systems. We first introduce historically how people realized the importance to study biological systems in the thermodynamic point of view. We then introduce the development of stochastic thermodynamics, especially three landmarks: Jarzynski equality, Crooks’ fluctuation theorem and thermodynamic uncertainty relation. We also summarize the current theoretical framework for stochastic thermodynamics in biochemical reaction networks, especially the thermodynamic concepts and instruments at nonequilibrium steady state. Finally, we show two applications and research paradigms for thermodynamic study in biological systems. What is life [How should a living system, e.g., a cell, be described from a physical aspect? In 1943, Erwin Schrödinger provided a systematic point of view in his speech, which explained the basic physical logic of cellular activities. The content, which was quite novel and interesting to people especially those with physical background, was later summarized into a book named Schrödinger’s point of view had great impact on biology and physics. It has been widely accepted now that metabolism, which describes how a living system continuously consumes necessary nutrients and energy taken from environment for life-sustaining, is the essence of living activities. On the other hand, this point of view first explicitly connected biological phenomenon with the theory of statistical physics, hence drew a large group of statistical physicists’ attention to systems far from equilibrium, i.e., nonequilibrium systems. Despite the success in explaining various non-living phenomena, the traditional equilibrium and near-equilibrium statistical physics had long been difficult to use in living system. After Schrödinger proposed his idea, physicists started to realize that open nonequilibrium systems (represented by living systems) are quite complicated and a new angle was needed.Another succeeding revolutionary idea comes from the Brussels School. During 1950s, the founder of Brussels School Prigogine and some other researchers discovered the so-called “minimal entropy production principle” ,3,4 for Since Prigogine and colleges found that it’s impossible to apply the minimal entropy production principle to systems arbitrarily far from equilibrium, they proposed the famous dissipative structure theory ,15: for The system must be open. By exchanging energy with external environment, a system’s ordered steady state is maintained with free energy dissipated and entropy (produced by nonequilibrium activities) expelled. In living systems and other chemical reaction systems, mass exchange is also needed in form of chemical reactantsThe system must be driven far enough from equilibrium. If the system is at or near equilibrium, it would be described by minimal entropy production principle and not be available for a steady ordered state.The nonlinearity in the system must be strong enough. Week nonlinearity would not lead to a complex and non-trivial dynamics.Dissipative structure theory, combined with Schrödinger’s novel idea, pointed out several fundamental requirements for ordered systems including living systems in terms of statistical physics:When the above requirements are satisfied, self-organized steady ordered structure, i.e., dissipative structure, may arise.Prigogine’s theory shed light on the research on thermodynamics for system far from equilibrium and its relation with complex nonlinear systems including living systems. With a series of proceeding work since 1980s on nonequilibrium thermodynamics, it’s now possible to explore the thermodynamic rules within living systems.Modern statistical mechanics is based on stochastic theory, where the dynamics of a system is described by stochastic process ,17. WhenA, its Hamiltonian T, according to equilibrium statistical physics, it corresponds to one certain equilibrium state whose probability of each microscopic state follows Boltzmann distribution, s, B by doing work, e.g., pulling a spring, pushing a piston, or changing the conformation of a protein complex, the Hamiltonian would be changed to B also corresponds to a unique certain equilibrium state with free energy W may also be different. Previous study including the 2nd law actually just stated that the average work done Jarzynski equality describes the relation between the work done and the free energy change during a general isothermal process. When the system is at a unique certain macroscopic state Jarzynski equality is a great breakthrough to 2nd law, and was confirmed by experiments in 2000s ,29,30. FCrooks’ fluctuation theorem describes the relation between the probability of a trajectory in phase space and the corresponding entropy production . Supposeeriments ,32,33.Crooks’ fluctuation theorem, just like Jarzynski equality, is also a breakthrough to the 2nd law. Actually, by considering Jarzynski equality, Crooks’ fluctuation theorem can be expressed in a simpler form:Seifert and some proceeding researchers extend these theories together with definition of some other thermodynamic variables to the motion of single particle. They calculated the entropy production rate in this case and proved the corresponding fluctuation theorem :(4)〈e−Δs Seifert .After these work, statistical physics can be applied to a much wider range of studies. Researchers now are able to discuss the systems not only at or near equilibrium, but also the systems arbitrarily far from equilibrium and systems even small to single particle with external stochastic force, in terms of thermodynamics. Thus, a new branch named stochastic thermodynamics ,38,39,40j and the corresponding entropy production rate on this cycle as j and j. It’s clear that if the entropy production rate With the branch established, recently an inequality named “thermodynamic uncertainty relation” (TUR) was proposed ,25,26,27TUR shows how the stochastic dynamic quantities (fluctuations) are related to thermodynamic quantities (entropy production rates). By increasing entropy production rate, the noise of the dynamics may be suppressed, and vice versa. It also reveals that, it’s impossible to reduce the fluctuation and entropy production rate simultaneously to infinitely small. This relation is attracting more and more attention, and is one of the most important theoretical results in this field in the past years.As introduced above, self-organized dissipative structure will maintain its ordered state for relatively long time, although far from equilibrium. Therefore, thermodynamic rules and properties in such steady states, i.e., nonequilibrium steady states (NESSs), are quite interesting to physicists especially biophysicists. The thermodynamic laws and methodologies in NESS, especially those in biochemical NESS, are of great importance to study the thermodynamic properties of living systems. Here we introduce the current thermodynamic theories in chemical reaction networks.i-th component and In the framework of stochastic process, chemical reactions are considered as a series of Markov processes described by chemical master equations (CMEs) ,42. ConsSimilar for the reverse reaction, after the reverse reaction happens V is the volume and Hence, considering other effects such as volume, the corresponding CME describing the evolution of the system’s probability density itten as (8)dP, a simplified framework can be applied . As is sThe dynamics of this system can be regarded as a single molecule jumping between the three states Equation .In summary, generally the dynamics of a CRN can be regarded the system jump between different microscopic states via Markov processes and can be described by a CME. Actually, such description in terms of stochastic process is proposed much earlier than the research on NESS or stochastic thermodynamics and had already brought in many important applications. For example, the precise simulation of chemical reactions—Gillespie algorithm .How to define the thermodynamic quantities in chemical reaction systems? Although they are well defined in equilibrium statistical mechanics, these definitions are traditionally only proved to hold at equilibrium state. Luckily, some of the definitions can be extend to nonequilibrium systems. The extension is strictly established by Ge and Qian , which ii and j are connected by i and i to j. Mathematically, it can be proved that for a quite wide range of CRN, there exists a unique steady state distribution F and S, it can be determined how free energy and entropy vary over time:Consider a general CRN, where any two microscopic states At steady state eat” Qhk , with thn components can be described by the concentration of each component When the system’s microscopic states are so close that can be described by some continuous variables equation ,46:(21)∂Similar to Equation , it can s(x→) is 22)W˙=kW˙=kPs to the signal molecule play the important role. For example, the key step in the chemotaxis network in or dimer . Such moA natural question is, from the physics point of view, why free energy dissipation is needed during information processing? The hint comes from the development of information theory in modern statistical physics, especially a branch called “information thermodynamics” ,79,80,81The study on the accuracy of specificity and kinetic proofreading is one of the earliest study that applies nonequilibrium thermodynamic concepts to information processing in living systems. This study could trace back to Hopfield’s work in 1974 , which hThis problem arises from the synthesis of complex molecules, such as DNA replication. As is widely known, successful DNA replication is achieved through base paring. For a certain site in the template DNA strand, the affinity of the “correct” base that should be paired to this site is much larger than the “wrong” base. This property that the specific ligand could bind to specific substrate or receptor is the so-called specificity. However, although small, the probability of a wrong base pair is not exactly zero. By calculating the free energy difference between correct and wrong base pairs, researchers found that, if the affinity difference is the only reason leading to specificity, the error rate during DNA replication is around und 10−9 , much smUnder this circumstance, Hopfield proposed a so-called kinetic proofreading model . This moL can bind with receptor R forming the complex L and receptor R. Denoting the ligand concentration by In Hopfield’s work, due to the limitation of the development of thermodynamic theory at that time, he didn’t carefully discuss the relation between the error rate reduction and how far the system is driven out of equilibrium. In a more recent work in 2006, Qian discussed the same question with more details . As is sL (the wrong ligand) in the system with the same concentration. Their structures are similar  inversely depends on the energy dissipation in a period V the system volume, C and As is shown in eriod ΔW:V×DT≈C+W0To understand the origin of this inverse dependence, researchers consider the noisy Stuart-Landau equation that describes a general system near Hopf bifurcation:drdt=ar−cEquation  can be aEquation  holds inIn some biological systems, timing function is accomplished by the collective oscillation phase of a group of oscillating molecules. For such systems, synchronization among different molecular oscillators is of great importance to generate and maintain the correlation of the collective phase, which is critical for macroscopic oscillation accuracy. A recent work shows that the maximal achievable synchrony among a group of identical molecular oscillators is also inversely dependent on the additional energy cost .This resIn this review, we summarize the history and current research status of biological thermodynamics. It’s still a new research branch and hotspot to study the thermodynamics in living systems, which could lead to great fundamental improvement in both physics and biology.In terms of physics, living systems are realistic systems far from equilibrium, which is a good research object for nonequilibrium statistical physics. By studying the biological functions and their thermodynamic cost, as the examples we show above, the availability of the theories from nonequilibrium statistical physics can be examined by realistic cases. Furthermore, with such applications in realistic systems, physicists could accumulate intuitive feelings that which concepts are of more importance, so that they are able to develop more realistic and useful thermodynamic theories and instruments. It’s also possible to adopt experimental tools from biological systems to test physical theoretical results, just like the test for Jarzynski equality ,29,30 anIn terms of biology, theoretical tools from thermodynamics and statistical physics could provide another new angle to understand the general, fundamental laws in living systems. New paradigms can also be established with the new theoretical tools to study quantitative behavior in living systems, such as spatial positioning by self-organization , underst