Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them. The natural clustering of normal activities is discovered through a self-tuning spectral clustering algorithm with unsupervised model selection on the eigenvectors of a modified similarity matrix. Hidden Markov Models (HMMs) are employed to model each cluster of normal activities and form feature vectors. One-Class Support Vector Machines (OSVMs) are used to profile the normal activities and detect abnormal activities. To validate the efficacy of our method, we conducted experiments in real indoor environments. The encouraging results show that our method is able to detect abnormal activities given only the normal training samples, which aims to avoid the laborious and inconsistent data labeling process. The world population is aging rapidly. As time goes on, the proportion of the elderly relative to the total population has increased, and continues to increase, especially in developed countries . Thus, hrobust to the change of environment, especially the light illumination;protective to the residents’ privacy;convenient to use, especially for the elderly.Traditionally, abnormal activity detection approaches use cameras to obtain the data of full human body movements . HoweverBearing those factors in mind, a Pyroelectric Infrared (PIR) sensing paradigm offers a promising alternative to the optical and wearable counterparts . PIR senHowever, there are some challenges facing the PIR based sensing system for abnormal behavior detection. The first one is the design of sensor nodes, which are required to capture the spatio-temporal characteristic of the human motion. Furthermore, as the data generated continuously by ambient PIR sensors, there is an increasing demand to analyze those ever-growing sensing data automatically, with little human intervention. Most importantly, the problem of abnormal activity detection is computationally challenging . Here, wIn this paper, we propose a PIR-based sensing system for anomaly detection. We design a PIR sensor node that can capture the spatio-temporal feature of human motion effectively. The key to achieve this target is by leveraging the visibility modulation of each sensor to enhance spatial resolution. We employ the reference structure tomography (RST) paradigm  to segmeThe rest of the paper is structured as follows: Traditionally, cameras have been used for human activity classification and abnormal activity detection . The proet al. [et al. [Wearable sensors is another paradigm for anomaly detection. Yin et al.  propose  [et al.  propose  [et al. .PIR sensing is a promising choice besides camera-based and wearable-based sensing. In , three PTo capture the spatio-temporal feature of human movement, the monitored region is segmented into discrete sampling cells . By leveet al. [SensFall. To achieve fall detection, the normal and abnormal training samples had to be collected beforehand. In other words, it was the supervised machine learning paradigm [PIR sensors are also used to detect abnormal activities, especially fall detection. In , PIR senet al.  proposedparadigm . Howeverparadigm  because In this paper, we propose a PIR sensor based sensing paradigm for abnormal activity detection in an unsupervised fashion. To avoid the laborious and inconsistent manual data labeling process, we propose using the self-tuning spectral clustering algorithm to discover the number of normal activities automatically. The KL divergence is employed to measure the similarity between each pair of normal training samples and construct the similarity matrix. HMMs are then utilized to profile each cluster of training samples, and OSVM is trained to detect abnormal activities. The details of our method will be elaborated on in the following sections.In this subsection, we review the design of our sensing model. The task of the sensing model is to capture the discriminative spatio-temporal feature of the human activities.L discrete non-overlapping sampling cells, denoted as The schematic diagram of our sensing model is shown in M sensors located in the measurement space. The visibility function jth PIR sensor:Assume that there are jth PIR sensor is given byith sampling cell. The output of the Equation (1) can be equivalently represented in a matrix form asThe human body can be regarded as an infrared radiative source to the surrounding environment. In comparison with the whole object space, the human body is sparsely distributed. Thus, the change of infrared radiation induced by human motion takes place only in a few sampling cells. This can be regarded as a compressive sensing problem , and theβ is less than that of the original cone. These two types of masks provide two degrees of freedom (DOF) spatial partitions.To implement the sensing model described in the previous subsection, which segments the object space into discrete sampling cells, we employ two kinds of masks. These masks play the role of reference structure, which modulates the FOV of PIR sensors. The first type of mask, Type I, is a fan shape, as shown in V is shown in In our system implementation, the performance of our system will improve as the number of PIR sensors increases . BecauseC is determined automatically, and the normal traces are grouped accordingly. In the second phase, each class of activity is modeled by an HMM. The equal-length feature vectors are constructed based on the likelihood output of training samples generated by these C HMMs. The OSVM is then trained for abnormal activity detection. It shows clearly that the spectral clustering algorithm is the core of our approach. The key components of our approach are explained in detail in the following sections.Based on the implementation of our sensing model, human activity under the object space will generate PIR data streams correspondingly. The measurement of PIR sensors are segmented by the Short-Time Energy method automatically ,26. GiveTo profile the normal activities in an unsupervised fashion, we employ the spectral clustering method to cluster similar sequences. However, because the lengths of these sequential data are different and vary greatly in value, it is a challenging issue to model these data for better similarity measures.π is the initial state probability distribution, A is the state transition probability distribution, μ is the mean vector, and Σ is the covariance matrix.Since the training sequences are generated by a hidden mechanism associated with human’s underlying activities, it is reasonable to model these sequences using a generative model . In thisith training sequence M PIR sensors,jth PIR sensor at time t, N HMMs, one for each individual sequence The lgorithm , we fit jth sequence, ith sequence, and To calculate the distance between each pair of these sequences, a probabilistic model-based framework for sequence clustering is proposed in . The likjth column of After the likelihood matrix A popular paradigm is to obtain likelihood-based distances between each pair of sequences . Based oWe regard the likelihood of each of the sequences under the trained models as samples from the conditional likelihoods of the models given the data, which embeds information from the whole data set . This gijth column of N models can be regarded as a set of “sampled points” from the model space Λ surrounding the HMMs that actually span the data space. Thus, these N trained models become a good discrete approximation According to the definition of likelihood matrix If we normalize the likelihood matrix This interpretation leads to the Kullback–Leibler (KL) divergence, which is a natural choice for the measurement of the dissimilarity between two pdfs. The discrete case of the KL divergence formulation is as follows:Thus, the distance between the sequences Distances defined this way are obtained according to the patterns created by each sequence in the probability space spanned by different models, and the distance measured between two sequences σ is the scaling parameter controlling the kernel width.Before applying a spectral clustering algorithm, the distance matrix σ is commonly specified manually, or numerous iteration has to be run for a range of σ [σ may not work well for all the data. Thus, instead of selecting a single scaling parameter, we propose calculating a local scaling K is independent of scale and is a function of the data dimension of the embedding space.The value of nge of σ . Howeverpoint di . The simThus, the scaling parameters for each pair of G with vertices G, where each element G into a distinct sub-graph.After the similarity matrix C. One method to discover the number of clusters is to analyze the eigenvalues of the normalized Laplacian matrix C. However, eigenvalues depend on the structure of the individual clusters, and no assumptions can be placed on their values [It is a tricky problem to specify the number of clusters given in  shows thr values . Once noC automatically is to analyze the eigenvectors of Laplacian matrix An alternative approach to discover the number of clusters atrix La . Assume C, is taken as the one providing the minimal cost.Let Define a diagonal degree matrix Find Recover the rotation lgorithm .According to Equation , grade tTake the alignment result The spectral clustering algorithm that we apply is similar to the one proposed in . The algIn our experiments, because the voulunteers will emulate five kinds of activities, N training traces into C clusters, which correspond to C different types of activities.After applying the spectral clustering algorithm, we can group the N normal traces given the model parameters To train an OSVM, we need to transform the training samples that are of variable lengths into a set of fixed-length feature vectors. Again, we apply HMMs to model these normal activities, one for each cluster. For each learned model with the corresponding parameters C-dimensional feature vector This is calculated by applying the standard forward-backward algorithm . In thisN training traces into a set of feature vector R can be minimized:After transforming the The slack variables grangian , the objR, the testing sample is considered abnormal.This quadratic programming (QP) problem can be solved using standard optimization techniques . To deteTypically, the training samples are not spherically distributed in the input space. Thus, the original data points are first mapped into a feature space so that a better data description can be obtained. Instead of requiring an explicit mapping function from the input space to the feature space, the solution can be obtained by replacing all the inner products Equation  by a kerIn our context, due to the noisy and nonlinear characteristic of the PIR sensors, the decision boundary of the OSVM is quite complex. Thus, we apply the Gaussian Radial Basis Function (RBF) kernel for the OSVM, which is defined as follows:SC+OSVM—The method proposed in our study, mainly including self-turning spectral clustering and One-Class SVM.SC+iForest—The difference between this method and the SC+OSVM is that we use isolation forest to replace One-Class SVM for abnormal detection. Isolation forest is an alternative algorithm for abnormal detection .OneHMM—All the normal training samples are modeled by only one HMM, which corresponds to not applying spectral clustering to the unlabeled samples. A threshold is set to distinguish normal and abnormal activities.In order to evaluate the performance of our proposed method, experiments were carried out on a real data set collected from a wireless sensor network. Our proposed method is referred to as SC+OSVM in the experiments. Two other approaches were also used for comparison. We list these three methods as the following:The experiments were carried out in a real indoor environment. The monitored region covered by the sensor node was a cone with a 3 m radius. The sensor node is with seven PIR sensors, each of them equipped with fresnel lens arrays and a mask, as shown in There were eight volunteers that participated in our experiments, including three females and five males. The height of them ranges from 1.64 m to 1.80 m, and the weight of them ranges from 50 kg to 70 kg. Each volunteer emulated five kinds of activities, including falling, sitting down, standing up from a chair, walking and jogging. Every activity was emulated ten times by each volunteer at a self-select speed and strategy, as shown in The performance of the abnormal human-activity detection methods can be evaluated in terms of two rates, detection rate and false alarm rate. The detection rate is computed as the ratio of the number of correctly detected abnormal activities to the total number of abnormal activities. The false alarm rate is computed as the ration of the number of normal activities that are incorrectly detected as abnormal activities to the total number of normal activities.Based on the confusion matrix shown in The performance of an ideal abnormal human-activity detection algorithm should have a high detection rate and a low false alarm rate. Therefore, we evaluate the performance of the algorithms using an Receiver Operating Characteristic (ROC) curve, which plots the detection rate against the false alarm rate. In addition, we compute the area under the ROC curve (AUC) to compare these algorithms. AUC is a better measurement than accuracy in the evaluation of learning algorithms ,38, espeν was set to 0.01.In our experiments, because the output of the sensor node was a seven-dimensional data stream with continuous values, as shown in Experiments were conducted to compare the performance of all three of the algorithms. We randomly selected 240 normal samples for training. The other 80 normal samples and all the 80 abnormal samples were randomly mixed together for testing. We also conducted experiments to investigate the effect of varying the number of training samples on the performance of the three algorithms. In these experiments, we kept the amount of testing data unchanged and reduced the number of training samples. To explicitly compare the performance of the three algorithms, we computed the AUC values by calculating the area under the ROC curves depicted in Another observation is that the performance of OneHMM will not be improved as the number of training samples increases. This is because the dissimilarity between different activities will degrade the classification ability of the HMMs; a single HMM to model all normal activities is not discriminative enough. By contrast, after applying the self-turning spectral clustering, each type of normal activities will be profiled by an HMM; it will obviously improve the performance of the OSVM.In this paper, we propose a novel approach for detecting a human’s abnormal activities. By employing the FOV modulation for PIR sensors, the human activity is encoded into low-dimensional data streams, which can be used to extract the tempo-spatial feature of the human motion. A self-turning spectral clustering algorithm is used to cluster the training samples with modified KL distance. The HMMs are trained to profile each cluster of activity. One-class SVM is setup to classify whether the testing samples are abnormal or not. A major advantage of our approach is that it does not need abnormal samples for training in advance. This is critical in real deployment because it is unrealistic to train the system by providing all kinds of abnormal activities. Another advantage is that our training procedure is an unsupervised learning fashion, which does not need to specify the number of kinds of normal activities. In other words, it is not necessary to label the training samples. This advantage will facilitate the mass deployment in different locations, and it can greatly reduce the human labor spent on training sample preprocessing. We demonstrate the effectiveness of our approach using real data collected from PIR sensors attached to the ceiling of the monitoring region. It shows that, as the number of training samples increases, the performance of our system will improve accordingly.In the future, we wish to continue in the direction of detecting abnormal activities from continuous data streams. We will investigate how to incorporate the location information with the motion information to improve the performance of our system. A robust and reliable abnormal activity detection system is the most important prerequisite of the home-based assisted living paradigm.


In oncology drug development, it is important to develop low risk drugs efficiently. Meanwhile, computational methods have been paid more and more attention in drug discovery. However, few studies attempt to discover the mutual gene modules shared by the drug and disease association. Here we introduce a novel method to identify repositioned drug for breast cancer by integrating the breast cancer survival data with the drug sensitivity information. Among the 140 drug candidates, we are able to filter 4 FDA approved drugs and identify 2 breast cancer drugs among 4 known breast cancer therapeutic drug in total. The goal of drug repositioning is to discover new association between indications of diseases and known drugs based on known associations . Drug re50) from the Developmental Therapeutic Program (DTP http://dtp.nci.nih.gov/) database. Combining with the prognosis modules and drug sensitivity modules, a repositioning framework for breast cancer is built. As a result, we have identified 12 compounds related to breast cancer. Interestingly, Not only could they help in treatment, but some of them could also have caused the disease.Roughly speaking, both human diseases and drug mode of action have a module basis on gene expression level. The rapidly developed microarray technique generates a huge amount of large-scale gene expression profiles. The gene expression data are both applied in cancer diagnosis and therapy. To identify the phenotype relevant gene modules could help us understand the mechanism of diseases and provides opportunities to develop new therapies. It is important to investigate the drug induced gene modules, and the differential expressed functional gene modules that influenced by diseases, especially the shared associated gene modules of drugs and disease phenotypes. Few analyses addressed the above questions in a systematic view. Gottlieb et al. presented a prediction method that based on the observation that similar drugs are indicated for similar diseases, and then discovers new associations by imposing the known "drug-disease" connections. Cheng et al. proposed a network-based inference method to predict new target for known drugs by using drug target bipartite network topology similarity ,6. With Here we proposed a systematic framework to identify the potential candidate drug for breast cancer and the associated mechanism module. The framework consists of three parts: 1) Identifying the prognosis module. The prognosis module is selected based on the statistical differences between the good outcome and bad outcome of the patients in three breast cancer clinical trials. (2) Generation of the sensitivity module network of drugs. The sensitivity module network of drugs is used to interrogate the mechanism of drug action. (3) Integration of the two results to search for the potential candidate drug. In the last step, we integrated the disease gene modules with the anti-cancer drug sensitivity module to filter the most significant potential anticancer treatment for breast cancer as shown in Figure  IdentifyThe tumor progression associated information is collected from three breast cancer datasets , Cellular Component (GOCC) and Molecular Function (GOMF). The annotated Gene Ontology Term was considered as a gene module.n samples. Then the Kolmogorov-Smirnov (KS) statistic is employed to test whether the expression of the gene set is enriched among the whole gene expression (N) in each sample. The KS is calculated as following formulas: [To determine the universal prognosis gene modules that represent breast cancer pathologic information, gene set enrichment analysis is performed on three different breast cancer survival datasets, with the purpose of selecting the gene sets that express significantly enriched in the survived patients. First, the gene sets were adopted from GOCC and GOBP. For each breast cancer expression dataset, we have ormulas: t is the number of the genes in the gene set, j is the th jgene according to the ranked expression in the gene set, N is the total number (13698) in the gene expression profile, V(j) is the ranked position of the th jgene, and KS score represents the enrichment score of each gene set in each sample. The result of this analysis is a matrix generated by the enrichment score of each gene module in each sample.where For each disease dataset, we used the t-test (as shown in formula (4)) to find whether the gene set has significant differential enrichment scores between the good outcome and bad outcome. And then we selected those gene sets with significant P-value (<0.05) among three clinical trials.x stands for the average enrichment score of the survived patient, y stands that of the patient with bad outcome, n is the number of the survived patients, and m is the number of the rest of the patients.where in vitro drug screen project [50 value, which is the compound's concentration that causes 50% cell growth inhibition and was obtained from DTP. Since the GI50 value is represented the drug's chemo-activity, the gene-drug correlation is established based on the correlation of gene expression and drug activity across 60 cell lines. The sensitivity module is consisted of only the significant gene that has P-value<0.05 as the compound sensitivity associated gene.Here we measure the drug sensitivity signature based on National Cancer Institute (NCI60)  project . The sub project ,19. The The drug-disease link is established based on the P-value of the hyper-geometric test (5) to determine whether the gene module (from the selected prognosis gene modules) has a significant overlap with the sensitivity module of the drug.M is the total number of genes in the whole profiles, N is the number of the prognosis gene modules, m is the number of the sensitivity module of the drug, and n is the number of the overlap between the prognosis module and the sensitivity module.where As shown in the final step of Figure The performance of the drug identification is assessed by the Effect Score which is the number of prognosis gene modules with significance divided by the half number of the identified prognosis gene modules. According to the ES, we estimated our performance by counting on the number of positive drug in the ranked drug list.50 value of each drug with the NCI60 profiling. After this process, we gathered 140 compounds sensitivity gene sets. The genes which have significance connection between the biological response pattern (GI50) and the baseline gene expression, though may not be directly linked to the primary drug targets, they should be close to the pathway where the mechanism of action taking place. Thus these genes can indicate the key biological processes of drug efficacy and represent the sensitivity genes of a compound which can serve as an effective tool for probing the compounds mechanism of action.To assess the potential application of this approach for identifying compounds, we generated the sensitivity module for each anti-cancer drug by applying Pearson correlation coefficient on the GIIn order to identify the tumor progression associated gene modules, we collected three datasets of breast cancer, GSE2034 , GSE7390In order to investigate whether a drug has strong effect on the gene function module, we used hyper geometric test on drug sensitivity module with the identified breast cancer prognostic associated gene module. The corresponding P-value of the hyper geometric test of each gene module was cut off by 0.05 as significance threshold. By ranking the number of the associated gene module, the FDA approved drugs such as Paclitaxel and Etoposide, Haloperidol, Mitoxantrone shows connections with more than half of the gene modules. Paclitaxel is a mitotic inhibitor used in cancer chemotherapy . And it Etoposide is also a topoisomerase inhibitor but haven't been reported to treat breast cancer . Our resSeveral not FDA approved drugs was also found has strong association with breast cancer. For example, Ellipticine was ranked also has 18 modules, and it was also reported that can act as an inhibitor to breast cancer. However, it fails for its side effect during the development . Also, cFor comparison, we used gene signature instead of gene module in our method. The prognostic gene signature was extracted from GSE2034. We chose 76 genes that are reported in Wang's work  as the mIn this study, we introduced a new pipeline to interrogate the transient cellular state under drug conditions by prognosis gene modules. Different from other methods which directly map the expression profiles of drug treatment to disease, our method was used to identify the cellular responses of drugs and gene modules that correlated with tumor progression through patients' survival information. We have identified 30 significant biological processes related to breast cancer prognosis gene modules. By integrating two results of gene modules, we provided valuable prediction information of breast cancer potential treatment. Among the drug library, we identified 12 drugs for breast cancer treatment. 4 of them are FDA approved treatment drugs, which shows the efficient of our result.We provide a novel work to investigate on the drug sensitivity module by using the prognostic related gene module annotation and use the connection to discover new association between the drug and disease. Our work proved that the sensitivity module of drugs could be used to not only identify the drug to treat the disease, but also reveal the drug's potential side effect.This method provides a new pipeline to identify the repositioned compound for diseases. However, there are several parts that could be improved in our future research. (1) By adopt with different cancer information, we could investigate more prognostic related gene modules. (2) The gene module could be extended according to the definitions of Protein-Protein-Interaction-Network level, or pathway information, or miRNA regulation. 3) From the disease annotated drug sensitivity module, such as the Mitoxantrone in Figure  From theThe authors declare that they have no competing interests.The work presented here was carried out in collaboration between all authors. Lida Zhu and Fuxi Zhu defined the research theme. Lida Zhu designed methods and experiments, carried out the laboratory experiments, analyzed the data, interpreted the results. Lida Zhu and Fuxi Zhu co-wrote the paper.


Coordinate based meta-analysis (CBMA) is used to find regions of consistent activation across fMRI and PET studies selected for their functional relevance to a hypothesis. Results are clusters of foci where multiple studies report in the same spatial region, indicating functional relevance. Contrast meta-analysis finds regions where there are consistent differences in activation pattern between two groups. The activation likelihood estimate methods tackle these problems, but require a specification of uncertainty in foci location: the full width half max (FWHM). Results are sensitive to FWHM. Furthermore, contrast meta-analysis requires correction for multiple statistical tests. Consequently it is sensitive only to very significant localised differences that produce very small p-values, which remain significant after correction; subtle diffuse differences between the groups can be overlooked. In this report we redefine the FWHM parameter, by analogy with a density clustering algorithm, and provide a method to estimate it. The FWHM is modified to account for the number of studies in the analysis, and represents a substantial change to the CBMA philosophy that can be applied to the current algorithms. Consequently we observe more reliable detection of clusters when there are few studies in the CBMA, and a decreasing false positive rate with larger study numbers. By contrast the standard definition (FWHM independent of the number of studies) is demonstrated to paradoxically increase the false positive rate as the number of studies increases, while reducing ability to detect true clusters for small numbers of studies. We also provide an algorithm for contrast meta-analysis, which includes a correction for multiple correlated tests that controls for the proportion of false clusters expected under the null hypothesis. Furthermore, we detail an omnibus test of difference between groups that is more sensitive than contrast meta-analysis when differences are diffuse. This test is useful where contrast meta-analysis is unrevealing. A very popular method of performing a meta-analysis (MA) of functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) data is coordinate based meta-analysis (CBMA). There are various approaches Here we focus on the activation likelihood estimate (ALE) based method, which is possibly the most widely known of the CBMA schemes. The ALE method models the uncertainty of the reported foci using a Gaussian function with specified full width half max (FWHM) The FWHM parameter, which is often set at ≈10 mm, has a major effect on the results Here a new FWHM scheme is introduced. This is motivated by the reasonable requirement that CBMA of a small set of studies should ideally produce results commensurate with those produced if the number of studies were increased. It redefines the FWHM as a density clustering parameter, rather than a specification of the uncertainty of the reported foci used by current ALE algorithms.The correction for many correlated statistical tests is a problem for contrast meta-analysis that has not yet been addressed We previously detailed a CBMA method that employed a false cluster discovery rate (FCDR) control scheme that has the particularly interpretable aim of limiting the proportion of the significant clusters expected under the null hypothesis. The control problem is further tackled by substantially reducing the number of statistical tests by testing only at the reported foci  a new definition and method for setting the FWHM parameter, 2) a description of the contrast meta-analysis algorithm and subsequent correction for multiple correlated comparisons at the cluster-level, and 3) an omnibus test of difference between groups.Statistical significance in the ALE method is judged relative to a null distribution of ALEs, generated by permutation of the foci throughout a grey matter (GM) mask While our algorithm  has been detailed previously Foci separated by a distance www.nottingham.ac.uk/research/groups/clinicalneurology/neuroi.aspx.The software is available to download and use freely from The FWHM can affect the results of ALE based CBMA Each study in the CBMA reports foci of activation, some of which are common to a proportion of the studies, while others are due to some study specific aspect. Where there is better than chance agreement across studies about the activation peaks, the foci form clusters of higher than average density. Between the clusters, the study specific foci form a lower than average density noise. Identifying clusters of high density points in the presence of noise can be tackled using the density-based spatial clustering in applications with noise (DBSCAN) Since the density clustering problem is analogous to CBMA, it is proposed that the FWHM parameter be redefined to be analogous to the Eps parameter in density clustering. The aim is to increase the FWHM for small numbers of studies such that the within-cluster foci can overlap, and reduce the FWHM for larger numbers of studies to prevent the study specific foci joining the clusters. To achieve this it is proposed that the characteristic volume occupied by each foci N is the total number of studies, and This constitutes a redefinition of the FWHM parameter. It no longer represents spatial uncertainty in the location of the foci, but rather it is a density parameter similar to Eps, used in the DBSCAN www.BrainMap.org) from the BrainMap database The effect of varying the FWHM between 6 mm and 18 mm is visually assessed, using LocalALE, in three sets of fMRI data: 1) the pain data (47 experiments) used in The mean effect of FWHM on the clustering under the null hypothesis is also investigated; under the null hypothesis it is expected that large clusters do not form on average. Foci are randomised throughout a grey matter mask, as detailed in rameter  ) is obtawww.BrainMap.org, and were originally created by searching the BrainMap database www.brainmap.org) are compared; GingerALE is used to demonstrate that the sensitivity to FWHM is not specific to our LocalALE method. It is expected that the clusters in the RA and OFC should be similar in the small and full datasets.Two large data sets used previously Finally a numerically generated pseudo experiment is created. Each pseudo study in the experiment has 10 foci , which are placed either within one of three clusters, or at random with uniform probability within the GM mask but outside of the clusters. The experiment is performed twice: a) with the proportion of studies reporting in the three clusters being 40%, 50%, and 60%, to reflect the proportion ranges observed in most significant clusters from the pain, Stroop, and n-back experiments, and b) with the proportion of studies reporting in the three clusters being 20%, 30%, and 40%, to consider the impact of less consistent activations. Foci that are truly members of the   using  ) estimatTrue and false positive rates are explored quantitatively for this numerical experiment as a function of the number of studies (10 to 150 studies); 100 averages are performed for each number of studies. The true positive rates are the proportion of true cluster foci that are declared as cluster members, while the false positive rates are the non-cluster foci declared as members of a cluster. Both true and false rates are expressed as a proportion of the total number of true cluster foci to make them easy to compare. If the clustering analogy is valid for our CBMA experiment, it is expected that with FWHM = 10 mm there will be fewer true positive results for few studies compared to Contrast meta-analysis attempts to find differences in activation pattern between two groups of studies. The results are clusters of foci where there is localised significant difference in ALE between the groups. The null hypothesis is that there is no difference between the groups, so a permutation (of the group variable) test is employed. Following on from our LocalALE algorithm, tests for differences are performed only at the foci in the method reported here; instead of at each voxel. It also employs the false cluster discovery rate (FCDR) control of false positive results, as detailed previously in A & B, containing Studies are separated into two groups, A, permutation i, at location r isB. The difference in ALE between the two groups isk, and for a particular focus For a particular permutation, E is true, and zero otherwise. A small value of It is hypothesised that the groups pplement ; the algContrast meta-analysis looks for differences in activation patterns, between groups, by location. But such analysis requires very significant differences; since the p-values need to be very small to remain significant after controlling for many statistical tests. An omnibus test can provide evidence of pattern differences when contrast meta-analysis produces no significant results. Such a test may be useful for detecting differences that are subtle, but spread across substantial regions of the activation pattern.A log likelihood value can be computed using the p-values from k. The magnitude of this will be small under the null hypothesis and larger when the data are critical of the null hypothesis. The distribution of This test is performed including all foci in the experiment.To explore the two different scenarios considered above  numerical experiments have been devised.A and {−34, 10, 16}mm in group B. A further eight clusters are reported similarly by both groups. All foci that form part of a cluster have a random spatial perturbation as described for the FWHM numerical experiment. From the pain and n-back experiments, about 50% of studies report at the site of the most significant clusters. Therefore, each of the clusters in this experiment contains foci from half of the studies, and half of the foci in each study are distributed randomly, and with uniform probability, throughout the GM mask.The first experiment involves two groups of studies with a cluster reported at {34, 10, 16}mm  in group The two clusters at A the clusters involve foci (with the random perturbation used in the first experiment) from 50% of the studies, and half of the foci in each study will be randomly distributed, with uniform probability, throughout the GM mask. Group B is similar, but the proportion of studies reporting at each cluster is lower. The differences between the studies are then subtle, and spread across the activation pattern. Results are reported in a table indicating number of studies, proportion of studies reporting at clusters, and significances by contrast meta-analysis and the omnibus test.The second experiment involves up-to sixteen clusters reported by both groups. In group The contrast meta-analysis and omnibus tests are performed using y axis gives FWHM estimates of around 7 mm, 8 mm, 12 mm, and 18 mm for these experiments. Given the number of studies in the experiments, and using An estimate of y axis at 0.5) are 29 mm, 29 mm, 29 mm, and 31 mm for these four experiments.These results are not specific to LocalALE, as we have shown in A and group B report some, or all, of these clusters. In group A 50% of studies report in each cluster, while a smaller percentage of studies in group B report at each cluster  FWHM, or the FWHM suggested by Eickhoff et. al. Our proposed method of estimating the FWHM aims to allow overlapping of the high density foci that form clusters, but prevent overlapping of the low density study-specific foci between the clusters. We use an empirical estimate of FWHM based on that which just starts to cause overlapping of foci between different studies under the null hypothesis . This isThe experiments depicted in We have quantitatively analysed the true and false positive rates associated with FWHM estimates using numerical simulation  and 8. TWe have estimated the parameter Control of false positives in our contrast meta-analysis algorithm is achieved using FCDR; a cluster-level control scheme. Cluster-level schemes have been incorporated into CBMA algorithms previously, and are preferred since they control at the level of interest (clusters) rather than at the voxel-level, but not into algorithms performing contrast of the ALE; indeed no method of control, other than conservative p-value threshold, has previously been described The contrast meta-analysis and omnibus test for differences between two groups were demonstrated using numerically generated experiments. The first experiment showed the ability of contrast meta-analysis to find local differences, if those differences were very significant. The omnibus test was also able to detect such differences, and with greater sensitivity, but without specifying where the differences are. A second experiment showed that when there are multiple subtle differences between groups, the omnibus test again had more power to detect it than contrast meta-analysis; as expected. Both methods are more sensitive with higher numbers of studies, more significant local differences, or more widespread subtle differences.Lack of spatial difference in contrast meta-analysis experiments is not a good indicator that there is no difference between the groups being compared because the test is not sensitive to diffuse subtle differences. The omnibus test is more powerful, and should be used where the contrast meta-analysis produces no results. If the omnibus test is not significant, it is more likely that any real difference between groups is small. If it is significant, it can indicate widespread subtle differences between the groups that are undetectable by contrast meta-analysis.The FWHM parameter used in ALE coordinate based meta-analysis algorithms is a source of heterogeneity between CBMA results. The meaning of the parameter has been redefined here from being the spatial uncertainty of the reported foci, to a parameter similar to that employed in a density clustering algorithm that works analogously to CBMA. This definition helps reduce the observed heterogeneity. More importantly, fixing the FWHM can paradoxically result in increased false positives as the number of studies increases, while the proposed The many tests used to compare the activation patterns between two groups necessitate a correction for multiple comparisons. We have detailed a contrast meta-analysis algorithm and correction for multiple tests that controls for the proportion of clusters expected under the null hypothesis, the false cluster discovery rate, and takes explicit account of the correlated tests. However, the contrast meta-analysis is not sensitive to diffuse differences between groups. We have therefore detailed an omnibus test that can provide evidence of differences in activation pattern between two groups even when contrast meta-analysis is unrevealing.File S1Cluster finding algorithm.(DOC)Click here for additional data file.


An assessment of the predictive capacity of the model using independent validation data showed a significant correlation (rs = 0.64) between predicted and known age at test sites. Application of the model provides valuable insights into the distribution of vegetation age-classes and fire history in the study region. This is a relatively straightforward method which uses widely available data sources that can be applied in other regions to predict age-class distribution beyond the limits imposed by satellite imagery.Understanding the age structure of vegetation is important for effective land management, especially in fire-prone landscapes where the effects of fire can persist for decades and centuries. In many parts of the world, such information is limited due to an inability to map disturbance histories before the availability of satellite images (~1972). Here, we describe a method for creating a spatial model of the age structure of canopy species that established pre-1972. We built predictive neural network models based on remotely sensed data and ecological field survey data. These models determined the relationship between sites of known fire age and remotely sensed data. The predictive model was applied across a 104,000 km Pinus forests of the United States of America and Canada . Th. Th50]. Neural network regression  was usedThe modelling process used 60% of the training sites (of known and predicted ages) to build the model, 20% of sites to halt training and mitigate overfitting, and the remaining 20% of sites (which had no part in the model generation) to validate the model . The modTo assess the accuracy of the predicted vegetation age, we used a validation data set (i.e. data not used in building the remotely sensed model), which was comprised of 20% of the sites. To examine the relationship between the predicted ages of sites we performed a rank correlation (Spearman’s rho) between the predicted age of the validation sites  and the age of sites known and determined from stem diameters. To further assess the accuracy of the remotely sensed model, we fitted a simple linear model in R v.3.1.1  and calcThe artificial neural network (ANN) model based on remotely sensed data provided good predictions of the post-fire ages of sites. For the 124 validation sites (sites not included in the model building process), the age estimated from the ANN model was strongly and positively related to the age predicted from field data and sites of known fire age  allows some appreciation of the age of mallee vegetation along roadsides and in small remnant blocks on public and private land . Many roA boundary between satellite images is visible as a straight line in the north-west of the map . There iAn analysis of the total area burnt during different time periods was undertaken from the mapped distribution, to illustrate the current age-class distribution of mallee vegetation in the region . Age-claAn ability to map the age of vegetation beyond the temporal limits of satellite imagery is of great benefit for the management of disturbance-prone systems, particularly those that display long-term successional dynamics. Here, by combining a technique for ageing mallee stems with a neural network model that uses remotely sensed data, we built a spatial model that maps the age-class distribution of vegetation across a region for age-classes of up to 100 years and more.Ctenotus brachyonyx; [Lichenostomus ornatus; [Ningaui yvonneae; [Succession in mallee vegetation remains dynamic for over a century ,56. As tchyonyx; ), bird  and mamvonneae; ) prefer vonneae; .points of high biodiversity value, a map also enables the overall extent of age classes to be calculated at various spatial scales such that managers can have a better understanding of vegetation age-structure in particular landscapes or conservation reserves. The spatial properties of fire mosaics, such as the spatial extent of different fire age-classes, are known to be key drivers of birds [In addition to identifying of birds ,58, smalof birds  and reptof birds  in this The level of correlation obtained during validation of the outputs of the neural network model suggest that there is room for improvement, potentially by incorporating other environmental factors that may contribute to the relationship between pixel reflectance in the satellite image and age of mallee vegetation. These could include the effects of grazing and browsing (including insect attack), rainfall, frost or windstorm.The temporal pattern of age-classes in the Murray Mallee region  predominth century (with the exception of the 1970s), than in the 1920s to 1950s. A similar distribution of age classes was also found by Clarke et al [The extent of fire was less during the second half of the 20ke et al . As the ke et al . The regke et al . The extke et al .Austrostipa spp.), which subsequently fuelled extensive fires across the region [The spike in area burnt in the early 1970s occurred when above-average rainfall produced abundant cover of spear grasses , representing a significant advance in our ability to understand the implications of fire on ecosystem dynamics in the region.The modelling technique described here provides a snapshot of the current age-classes of vegetation within the study area. Each pixel on the map is assigned the year of the most recent stand-replacing disturbance . Currently, this approach does not distinguish areas that have burnt multiple times, which could display different biological characteristics as a result of differing fire history; and it tends to underestimate the vegetation age for the oldest sites (> 85 years). The models could be improved with further work to identify processes that drive change with increasing time; for example, localised mallee death due to severe weather conditions . Recruitment events between fires could also introduce uncertainty into the model, although these appear to be extremely rare ).The approach described here has potential for use in determining age classes of other vegetation types. It could be used to map the temporal distribution of stand ages following any stand-replacing disturbance, including fire, cyclones, landslides or slash and burn agriculture. However, the following assumptions are likely to be necessary for this approach to be successful:an ability to reliably age sufficient sites across the study area to train the modelreliable and consistent recruitment of overstorey following stand-replacing disturbanceminimal recruitment of overstorey between disturbance eventsspectrally distinct changes occurring in the vegetation over time, such that differences in satellite imagery can be detected.Patterns of change in structural characteristics of mallee vegetation over time have been described , and areThis study outlines a method to determine a snapshot of the current distribution of vegetation age-classes in the fire-prone Murray Mallee region over an ecologically meaningful time span, and provides valuable information on the likely fire history of the region. The occurrence of very old mallee vegetation on roadsides and in other small pockets highlights the need for appropriate management of this unevenly distributed, and in places, rare resource. It is likely that these small patches retain important habitat components such as hollows, particularly in the south of the study area where long-unburnt vegetation is scarce. The uneven distribution of age classes suggests that managing mallee vegetation in a coordinated way across state and reserve boundaries will be beneficial. Achieving a desirable distribution of age classes within individual reserves needs to be balanced with maintaining age-class structure and diversity across the entire region.This model does not elucidate the ‘natural’ (pre-settlement) fire regime, nor is it likely that a return to such a regime would be helpful in today’s highly fragmented and modified landscapes. While it is clear that large homogenising fires should be avoided to preserve a diversity of habitats, both within reserves and across the region, identifying spatial and temporal configurations of age classes across the landscape that are more, or less, desirable for achieving conservation goals remains an urgent challenge.S1 Table(DOCX)Click here for additional data file.


Aim: The Berlin project "Interprofessional teaching and learning in medicine, occupational therapy, physiotherapy and nursing" (INTER-M-E-P-P) pursues the goal of developing and testing interprofessional courses in an exemplary manner, and then implement these into their regular study programs. Method: Under the direction of a steering committee of the participating institutions, professions and status groups, interprofessional courses were designed, carried out and evaluated. Specific to this project are the participation of students in the steering committee, and the accompanying of external supervision. The evaluation integrates the perspectives of all project participants, and combines quantitative and qualitative methods.Results: INTER-M-E-P-P established cooperative structures between the participating universities and programs. Three courses were designed, taught and evaluated in an interprofessional manner. The various curricula, organizational patterns and locations of the study paths led to a great need for resources in regard to planning and implementation. This process can be made difficult by any stereotypes or preconceptions inherent to those doing the planning; however, under external supervision, the individual professional viewpoints can still be broadened and enriched.Conclusion: A sustainable implementation of interprofessional education into the curricula of health science study programs is currently complicated by barriers such as different geographical locations and differing university regulations concerning study and testing. Implementation will require long-term support at the university as well as at political levels. Interprofessional education (IPE) in health professions pursues the goal of enabling interprofessional collaboration (IPC) and contributing to a series of positive effects in the provision of health care: improvement of patients' care and safety, increasing the efficiency and effectiveness of medical teams, as well as promoting satisfaction among the members of interprofessional teams , 2]. No. No2]. NIn Germany, as regards practice and science, IPE has hitherto only been little developed. There are few study programs in the health professions in which multiple professional groups are taught with a focus on IPC . For theSeen internationally, IPE has long been the subject of increased attention and promotion, particularly following the 1988 WHO report, "Learning together to work together for health" . At the In reference to sustainable integration of IPE into health care programs, published research identifies success factors that must be carefully considered when establishing IPE in Germany  project is a joint developmental project between the Charité – Universititätsmedizin Berlin (Charité) – with its new modular curriculum of medicine, the Alice Salomon Hochschule Berlin (ASH) with its bachelor degree program in physiotherapy and occupational therapy, and the Evangelische Hochschule Berlin (EHB) with its bachelor degree program in nursing. The project is also part of the Robert Bosch Stiftung’s program entitled "Operation Team – Interprofessional Learning in Health Care Professions”, which ran from October 2013 through September 2015.The aim of this project is to develop, implement, evaluate and anchor interprofessional course offerings on relevant topics into the curricula of the three participating degree programs. The project strives to give students the opportunity to become familiar with professional fields and profiles in joint courses, to become aware of and reflect on the roles expected of them and the other professions. In addition, students are given a chance to interact interprofessionally as part of the learning process. In terms of the persons, study programs and institutions involved in the development process, it is important to establish sustained cooperation and jointly meet the challenges of establishing IPE.A steering group consisting of representatives from medicine, occupational therapy, physiotherapy and nursing from each of the three institutions was formed as an essential component of the project. Project management was taken over by three professors from the three universities :Principles for supporting patients with limited mobilityTeam conflictsInterprofessional collaboration in rehabilitationTogether with the instructors, teaching manuals were compiled which contained the course objectives and competencies, content and teaching methods. The instructors were given practical and theoretical support as needed regarding content and teaching.As the courses underwent development, there were discussions about the various theoretical frameworks and teaching philosophies of each degree program. These include e.g. the understanding of competence or the principles of construction which belong to curricula. Shared principles for IPC were identified, such as a focus on pertinent and suitable examples of interprofessional situations in the work setting and the abilities to understand, cooperate and reflect. The question regarding a specific IPE teaching method for the participating health professions was raised by the project team, but still remains open.Alongside the task of designing content, there was necessary – from the start of the project – communication about aims and backgrounds of IPE courses within the universities. This internal publicity served to increase the awareness and appreciation of upper-level university administrators, instructors, students and administrative employees, thus improving the conditions for implementing the new course offerings.Evaluation during the project took place on the one hand in terms of the planning and implementation processes, but also regarding the cooperation among those involved. Evaluation occurred in spoken form at regular intervals and every now and then in writing; a supervisor monitored the process. The experience and knowledge gained by the project group was formulated through structured reflection. The supervisor posed open questions as guidance and led methods for reflecting, such as “sitting on a chair” in which each group member individually gives feedback to three questions. The first question addressed positive experiences in working with the team and the communication in the INTER-M-E-P-P project during the previous year. The second question asked about ongoing work in regard to team cooperation and communication, while the third question focused on wishes and desires concerning teamwork and communication in the coming six months. The results were written down, analysed by the group, and agreements were reached about constructive changes.On the other hand, the evaluation covered the newly designed course offerings themselves. These were analysed using qualitative and quantitative methods. At the beginning and end of the course which addressed the principles of supporting patients with limited mobility, the students filled out a survey with open-ended and closed questions. The responses to the open-ended questions were interpreted analytically.A qualitative evaluation of the course dealing with team conflicts took place in which the students responded individually in writing, but also in their specific occupation groups to open-ended questions. In the same manner, the instructors participated in written evaluations, but for organizational reasons this was undertaken via email. Analysis of this qualitative data is still underway.The lecture series on collaboration in patient rehabilitation was analysed informally in spoken form with the participating instructors and the steering committee.The major results are presented in the following sections to provide an overview of the successes and obstacles over the course of the entire project. Further publications will address the details of specific results, for instance those involving the three course offerings.A total of three interprofessional courses were offered to students of medicine, occupational therapy, physiotherapy, and nursing during the 2014/15 winter semester and the 2015 summer semester  affected communication within the interprofessional working group.In the following, exemplary results taken from two of the courses are outlined.The 90-minute course on handling patients with limited mobility was team-taught in five interprofessional groups and taught by one instructor in 16 mono-professional groups consisting exclusively of medical students  course appears necessary.Systematic analysis is still underway regarding the qualitative data gathered on the course covering team conflicts; however, it can already be stated that the participating students and instructors identify confronting stereotypes as a challenge. Pursuing more detailed information on this aspect does appear to be worthwhile.The teaching and learning materials developed for the courses have been reviewed and revised on the basis of the evaluation results, and have been made available to the universities for further use.In this section, we critically discuss the project results in terms of success factors and challenges, as well as comment on the limitations of the project.The central success factors for the project are student participation and project management under external supervision.For Wilhelmsson et al.  the invoReasons for and benefits of including students in INTER-M-E-P-P can be summarized as:A close connection with working practices,An opportunity to introduce unconventional ideas within the group – free from institutional, status-related, or occupational limitations,Knowledge of structural aspects of each degree program that can be used in planning and designing curricular content,Augmentation of course evaluations to gather overall impressions about the attitudes and opinions of students before, during and after the courses, andClose alignment with the needs of the student cohorts towards whom the course offerings are aimed.Collaboration marked by respect represents a great opportunity for project success. At the same time, this requires a very conscious approach to communication, standards, rules and roles, namely matters that are facilitated by supervision.Using supervision as a supportive measure was an important decision on the part of the project group. From the perspective of the supervisor and steering committee, this form of project management and collaboration in project teams (see 2.1) led not only to very intense and long discussions during the working phases, but also to better acceptance and knowledge of the perspectives and working habits of the other professions and degree programs. As a result of her critical thinking skills and solution-based approach, the supervisor was able to contribute to effective and constructive cooperation that focused on the resources available to all parties involved. She made it possible to identify the problems which arose over the course of collaborating, and then to process these on a meta-level. Due to the tight project schedule, even the supervisor was faced with limitations. More time for working through topics together such as the significance of stereotypes and role models within the project group would have been more ideal.Major challenges for the project were seen in integrating IPE into the curriculum, shortages in staffing and time, as well as addressing role models and stereotypes.The curricular integration of IPE into all three degree programs – which was a primary aim from the beginning – could be only partially realized. The three programs differed in respect to the content, structure and scheduling of the modules for which IPE came into question. Coordination of lesson plans has been identified as a challenge in other studies .In addition, the different student cohort sizes posed a challenge that could be met by forming interprofessional groups and mono-professional groups with medical students only.According to Wilhelmsson et al., personal contact in small groups in a nonthreatening educational setting is crucial for a willingness to embrace IPE . Five toScheduling belonged to the main difficulties faced in implementing IPE , i.e. thThe INTER-M-E-P-P project underscores the insight that making IPE a permanent feature at the participating universities will not happen on its own. Constructive project management was possible only as a result of third-party funding of a project coordinator position and three student employees and by the fact that the professors dedicated themselves above and beyond normal expectations.Oandasan and Reeves  remark tOne challenge remains: how do we approach stereotypes? Even instructors are socialized according to occupation, and they hold stereotypes more or less subconsciously. For this reason, it is important that planners and instructors address this as a team under the guidance of a supervisor.During the course itself, enough time must be allotted to cover the topic of role models and to speak about stereotypes.The primary aim of this project was to gather experience with interprofessional courses offered at three universities with three different degree programs and to lay the foundations for including IPE on a permanent basis. The project work took place in the form of action research: the stakeholders involved were not only the constructors of the interprofessional education and the cooperative network, but also the evaluators of their own work. This simultaneous carrying out of developmental work and evaluation led to enormous time pressure during the project, yet also allowed for systematic data analysis to take place afterwards. Some partial results during the project have already been incorporated into subsequent work, without the necessity to publish them as educational research.The INTER-M-E-P-P project was able to identify important concrete possibilities but also limits of IPE for the participating institutions. Comprehensive project management by the project coordinator , constant student participation, and the collaboration on the interprofessional steering committee with external process monitoring (supervision) proved to be very productive.“Berliner Manifest für kooperatives Lernen in der Ausbildung und den Gesundheitsstudiengängen in Berlin”) is currently being drafted, meaning that Berlin is in fact in motion and already off to a good start with the INTER-M-E-P-P project. Until consolidated policies at the university and state levels can be achieved, renewed third-party funding could buy more time to keep IPE alive in the meantime.The question about making the project a permanent part of the programs, and its recognition by the universities both remain central issues. In order to continue the work started here for an integration of IPE into health care curricula in a sustainable manner, it will be necessary to initiate supportive measures on both university and political levels, for instance in the form of agreements by the universities recognizing IPE as a legitimate field for research and development counting toward regular faculty duties. Together with university administrators at the participating institutions, a “Berlin manifest for cooperative learning in education and health care programs in Berlin” (The INTER-M-E-P-P project received a grant from the Robert Bosch Stiftung (project number 32.5.1316.0010.0).The authors declare that they have no competing interests.The first name of the author Mrs. Kaufmann has been corrected.


Plesiosaurians are an extinct group of highly derived Mesozoic marine reptiles with a global distribution that spans 135 million years from the Early Jurassic to the Late Cretaceous. During their long evolutionary history they maintained a unique body plan with two pairs of large wing-like flippers, but their locomotion has been a topic of debate for almost 200 years. Key areas of controversy have concerned the most efficient biologically possible limb stroke, e.g. whether it consisted of rowing, underwater flight, or modified underwater flight, and how the four limbs moved in relation to each other: did they move in or out of phase? Previous studies have investigated plesiosaur swimming using a variety of methods, including skeletal analysis, human swimmers, and robotics. We adopt a novel approach using a digital, three-dimensional, articulated, free-swimming plesiosaur in a simulated fluid. We generated a large number of simulations under various joint degrees of freedom to investigate how the locomotory repertoire changes under different parameters. Within the biologically possible range of limb motion, the simulated plesiosaur swims primarily with its forelimbs using an unmodified underwater flight stroke, essentially the same as turtles and penguins. In contrast, the hindlimbs provide relatively weak thrust in all simulations. We conclude that plesiosaurs were forelimb-dominated swimmers that used their hind limbs mainly for maneuverability and stability. Plesiosaurs are an extinct group of Mesozoic marine reptiles with a global distribution that spans 135 million years. They maintained a unique body plan with two pairs of large wing-like flippers throughout their long evolutionary history, but how plesiosaurs swam has remained a topic of debate for almost 200 years. We address the question of how plesiosaurs swam using a digital, three-dimensional, free-swimming model of a plesiosaur in a simulated fluid. We performed thousands of simulations under different parameters to investigate possible plesiosaur swimming patterns. Our simulations show that the forelimbs provide the majority of thrust, and that the thrust from the hindlimbs is weak. The plesiosaur swims primarily with its forelimbs using an underwater flight stroke, essentially the same as turtles and penguins. During their long evolutionary history , 7, 8, 9. Key are, a fligh, 12, and akin to . Gait hy, asynchr, whereas and humaOur approach uses computer simulation to address the question of how plesiosaurs swam using a three-dimensional plesiosaur model in a simulated fluid. The computational model explores a given range of joint motion to discover the swimming stroke and gait that propels the creature forward the greatest distance. There are two main advantages to using computer simulation to investigate swimming motions of plesiosaurs. First, we can construct a digital representation of the body that accurately matches the known body and limb shapes of a particular species. Second, we can run thousands of trials with different strokes and gaits to explore the space of possible swimming motions. We use an optimization method to search for the highest quality motion for a given range of joint angles. Computer simulation has been used to investigate the motions of several types of modern-day swimmers, including fish –21, tadpMeyerasaurus victor, a small (3.35 meters long) taxon from the Lower Jurassic of Germany, because it is known from an almost complete articulated skeleton (SMNS 12478) with all four limbs preserved in their entirety [Meyerasaurus possesses a generalized morphotype among plesiosaurs, with a moderately long neck, so it can be considered representative of the clade Plesiosauria as a whole, which contains long- and short-necked morphotypes [We constructed a life-sized plesiosaur model based on on SMNS 178 with aon SMNS 1478 with Meyerasaurus is dorsoventrally compressed, information from other plesiosaur specimens was used to estimate cross sections in the vertical plane [Rhomaleosaurus thorntoni [Seeleysaurus guilelmiimperatoris [Hydrorion brachypterygius [Meyerasaurus: Rhomaleosaurus [Meyerasaurus model with 50% greater soft-tissue mass around the base of the limbs was also created to test the effect of a bulkier body outline.Two dimensional cross-sectional data for the body was estimated by tracing around the skeleton in the horizontal plane. Since the holotype of al plane  Fig 1B)Meyerasauhorntoni . The reseratoris  and Hydrterygius . The taieosaurus . The vireosaurus . The lifOur physics simulator (based on previous methods ) represeTo study the forward swimming motion across a wide range of periodic swimming strokes of the limbs, we require a motion representation that is expressive but that is also biologically plausible. We decouple the degrees of freedom at a joint into a dorsal/ventral component, an anterior/posterior component, and a pronate/supinate component . We specify the limb motions of the plesiosaur by describing sinusoidal patterns for each of the three degrees of freedom at a given joint. The limb motion for a given component is specified by three values: the minimum and maximum value of the sinusoid, and the phase of the sinusoid. We use the same frequency (0.5 Hz) for all of the sinusoids across all of the limbs. Since the motion for each degree of freedom is given by three values , nine numbers fully describe the motion of a single limb. We assume that the left and right limbs move in synchrony while the animal is swimming straight, as is the case for penguins, sea lions, marine turtles, and nothosaurs . HoweverAlthough using sinusoidal motions of various angle ranges and phases gives a wide range of possible swimming strokes, the motions of modern-day swimming animals depart from pure sinusoidal motion in at least two ways. Animals such as penguins that use an underwater flight stroke  hold thePlesiosaurus sp. [Plesiosaurus sp. [Plesiosaur limbs contain a single mobile joint located between the propodial and the girdle: the glenohumeral joint in the forelimb and the acetabulum-femoral joint in the hindlimb. The articulation points for these joints in the model are located in the anatomically-correct positions . Neutralurus sp. . In the urus sp. . The widIn life, rotation of these joints was complicated, but for simplicity, they pivot around a single point in the model. Although there are no additional mobile joints in plesiosaur limbs, cartilage and tendons would have allowed dorsoventral flexibility and twisting along the long axis of the limb . This coSince a single swimming motion requires the specification of many different sinusoidal parameters , we use numerical optimization to explore the range of possible plesiosaur swimming motions. Specifically, we use the sample-based method called Covariance Matrix Adaptation  which ha-1) to concentrate them at regions of interest.The simulations used to make these videos not only provide the motion of the plesiosaur model, but also give us the velocity field for the simulated fluid at each simulation time step. This allows us to show not only the plesiosaur motion, but also the accompanying motion of the water. In each video clip, we show the motion of the fluid using particle traces (particle trajectories over the last few time steps) from randomly positioned particles in the virtual fluid. These massless particles are passively advected through the fluid. The particle traces are drawn only at locations with large vorticity  have low aspect ratio flippers [Meyerasaurus model used in our experiments possesses an intermediate morphology with a moderately long neck and moderately large skull, so the results represent a generalized plesiosaur morphotype. Variations in head and neck size could shift the center of mass relative to that of our model, possibly affecting the relative contributions of the forelimbs and hindlimbs during swimming. A longer neck and/or a larger head would increase drag and slow the forward motion in a manner similar to our test with increased limb muscle bulk. It is also possible that the tail contributed to forward thrust during swimming. Although we conservatively extend our general conclusions for Meyerasaurus to all plesiosaurs, our method could be sensitive to substantial changes in bodily proportions, and different plesiosaurs may have swam in different ways. Further experimentation is therefore required to assess how bodily variation might affect locomotion in other types of plesiosaurs.There is great variation in head and neck proportions, flipper aspect ratios and relative limb proportions within the clade . For exaflippers . Head anflippers . The MeyWe simulate the plesiosaur as a set of rigid bodies bound by joints, submerged in inviscid, incompressible fluid flow, governed by the Euler equations . The pleu is the velocity of fluids, ρ is the density, p is pressure and g is gravity. We simulate the fluid using a staggered MAC grid [We simulate the fluid dynamics based on Euler equation (Navier-Stokes equation without the viscosity term), since the viscosity of water is negligibly small.MAC grid  based soMAC grid  to integq, M(q) is the mass matrix, C is the Coriolis and Centrifugal force, τext are the external generalized forces, including the fluid pressure and gravity, and τint are internal torques exerted by the actuated joints. Given a reference swimming stroke, we use Stable Proportional-Derivative controllers [τint to closely track the stroke.The dynamics of articulated rigid body systems (the plesiosaur) is described by the equations of motion in the generalized coordinate:trollers  to compuWe build our two-way coupling solver based on Tan’s two-step procedure . In the 3 region of water), which will cause stair-step boundary artifacts at the interface between the fluid and the animal. This can result in seemingly higher viscosity near the animal’s body. For this reason, we incorporate the variational approach [Our simulator needs to voxelize the plesiosaur onto the grid at each time step, which marks the grid cells that are inside the animal as solid cells and the remaining as fluid cells. Due to the large computational requirement of the two-way coupling simulation, we use relatively coarse grid resolution  between the ray and the model. Since our model is watertight, if the intersection count is even, the cell is outside of the body of the plesiosaur, and thus occupied by the fluid. Otherwise, the cell is inside the creature, and thus it is solid. We implemented a Surface Area Heuristic Kd-Tree [To compute the fluid volume fraction  Kd-Tree  to accelD is discretized volume-weighted divergence operator and u* is the intermediate velocity field before enforcing incompressibility. We use normal stencils of Laplacian and Divergence operators at fluid-fluid faces. We apply Preconditioned Conjugate Gradient solver to solve the system, after which we project the fluid velocity with the following equationu* and u represents the fluid velocity before and after projection. As a result, we simultaneously enforce incompressibility of the fluids, compute dynamics of the solids, satisfy boundary velocity constraints and achieve smoother fluid flow at the solids-fluids interface.Finally, we construct a sparse symmetric positive linear system with the following equations at the fluid-solid faces,Note that our simulated water does not behave exactly the same as real water. Two common issues in numerical fluid simulations, numerical viscosity and voxelization artifacts, affect the accuracy of our two-way coupled simulator. The numerical errors in the simulation can make the simulated fluid more viscous than its real counterpart. This is called numerical viscosity . Even ths as a single point in a 26 dimensional space. Given a motion sample, the plesiosaur/fluid simulator generates a swimming motion through the hydrodynamic interaction. We formulate the quality function q(s) that favors a swimming stroke that leads to a longer swimming distance, and we penalize deviation from swimming straight.Given a plausible range of motions for the front and back limbs, we wish to find the swimming motion that propels the animal the farthest distance in a given amount of time. We also want to favor straight swimming. Since a single swimming motion requires the specification of 26 parameters we formulate our question in terms of optimization. Let us call a specific set of swimming motion parameters a motion sample, and we can think each such motion sample We calculate the swimming distance as the displacement of the plesiosaur’s center of mass (COM) in one swimming cycle projected onto its initial heading direction. The deviation from straight swimming is decomposed into two components: Directional deviation is measured by the displacement of COM that is perpendicular to the initial heading direction. Orientation deviation is measured simply as the orientation change in one swimming cycle. Since the simulation starts with a static plesiosaur submerged in motionless water, we evaluate the objective function only after the first stroke cycle is completed, when the plesiosaur has reached a steady speed. Forelimb-only and all limb optimizations were initiated with the front limbs in the fully abducted position and the hindlimbs in the neutral position. Hindlimb-only optimizations were initiated with the hindlimbs in the fully abducted position and the forelimbs in the neutral position. This forced all of the gait samples to begin with a downstroke, so that no gait was penalized for a slow start that is mid-way through a stroke.s that gives us the highest quality. CMA is a sample-based approach to optimization that uses a Gaussian distribution to guide its selection of motion samples to test. Each iteration of the CMA draws a new set of samples based on the current distribution, and evaluates the quality of these samples using q(s). The mean and the covariance matrix of the Gaussian are then updated according to a subset of sample with higher quality. As more iterations are taken, the covariance matrix narrows down towards the best quality sample. In our case, the best sample is the swimming motion parameters that move the simulated plesiosaur the farthest in a straight line through the water.We used Covariance Matrix Adaptation (CMA) , 45 to sTo converge to the optimal motion, CMA requires many samples to be evaluated. Each sample evaluation requires a full simulation of the specified motion, and each such plesiosaur/fluid simulation requires roughly one hour of computation. We used 31 samples per iteration of CMA, and we found that a typical optimization run converged in about 70 iterations, after which the quality of the motion samples does not improve. This means that a full optimization requires more than two thousand swimming simulations. We made use of a compute cluster with 32 nodes, so that the computations for a single iteration were all calculated in parallel on separate nodes. (One of these computer nodes coordinates the simulations of the other 31 nodes.) Even with the compute cluster, performing CMA optimization for a single set of joint ranges requires three days to run.Although CMA converges to high quality samples, there is no guarantee that it will find the best possible sample in our 26-dimensional search space. This explains why, for the wide joint range, the best forelimb-only swimmer that was found is slightly faster than the all-limbs swimmer . To veriS1 VideoAnimation showing the most efficient swimming motions that were found in each of the three joint ranges . For each joint range, animations are shown for both sets of limbs, for only forelimbs, and for only hindlimbs. White streamlines show the motion of the surrounding fluid.(MP4)Click here for additional data file.S2 VideoAnimation showing the motion of the tips of the limbs for the most efficient swimming motions in each of the three joint ranges. The camera view is locked to move with the plesiosaur model to more clearly show these tip traces. For each swimming motion, both a lateral view and a posterolateral view are shown.(MP4)Click here for additional data file.


Parotidectomy is a surgical procedure associated to functional (Frey's syndrome) as well as aesthetic  complications that can be very disturbing for the patient. Several procedures have been described to primarily avoid or secondarily reconstruct the facial defect and treat the neurological iatrogenic syndrome. Autologous fat transfer was primarily used in 10 cases to avoid such complications. It is an easy technique widely used in cosmetic and reconstructive surgery. This technique gives very satisfying long-term results on the cosmetic as well as on the physiological point of view. Superficial or total parotidectomy is a common procedure associated with some possible complications as well as functional and aesthetic consequences. Among these, Frey's syndrome, also called gustatory sweat syndrome or auriculotemporal syndrome, and a preauricular deformity are common issues that can lead to very disturbing clinical situations. Indeed, Frey's syndrome is characterized by a sweating and a flushing and/or an erythema of the cheek area during mastication after parotid surgery. Aesthetic consequences include a concave facial effect with facial asymmetry  and promAutologous fat transfer, also called fat graft or lipofilling following the operative technique used, is an easy technique widely used in cosmetic surgery to correct folds of the face  or to remodel soft tissue and enlarge or resurface them. This technique was primarily applied in 10 cases of superficial and total parotidectomy, with very good to excellent long-term results on the cosmetic as well as on the physiological point of view.en bloc, in the operative field, at the place of the resected gland . En bloc does here signify that fat was simply deposited in the operative defect and not injected in a multilayered way. A multilayered injection in any other preserved tissue  was indeed not possible or not an option. Prevention of Frey's syndrome implies that fat should be interposed between skin and facial nerve.Ten patients  were operated on from January 2006 to December 2009 for clinically benign tumors of the superficial and/or deep lobe of the parotid gland. Dissection of the parotid was performed under magnification, with dissection and preservation of the facial nerve in all cases. Before closing the operative field, fat was harvested in the lower abdominal wall following Coleman's technique: after infiltration of the site of fat removal with a solution of 1% lidocaine with 1 : 200,000 epinephrine, a blunt tip cannula attached to a 10 cc Luer-Lok syringe is used to harvest fat. Care is taken to avoid mechanical trauma of the fatty tissue; the negative pressure is therefore limited to 5 cc in the barrel of the syringe. Contrary to Coleman, we do not centrifugate the harvested fat but we wash it with physiological salt solution. After washing, fat is put This additional procedure is fast and performed in 5 to 10 additional minutes. This is not too time consuming, especially in case of a two-team approach. The mean operative total duration is 3 hours. A drain without suction is placed at the end of the procedure and a moderately compressive dressing is done. Drain and dressings are taken away on the 2nd postoperative day.Histology showed 3 well-encapsulated malignant tumors . Those last patients were secondarily irradiated. All patients but one (loss of follow-up) are followed every 3 months the first year, and after that once a year, dependent on the compliance of each of them.This 77 year-old woman presents a tumor of the right parotid. Among the medical history, it should be noted that she has had a mastectomy for a breast cancer and a diabetes mellitus. The tumor is 3 cm in diameter, developed in the lower pole of the gland. A preoperative CT scan confirms the parotid location of the tumor and a fine needle biopsy under ultrasonographic control is in favor of a pleomorphic adenoma. She is operated under general anaesthesia, with magnification and neurostimulation of the facial nerve. The superficial lobe is excised, the facial nerve is preserved, and 18 mL of fat is put in the defect. Pathology confirms the preop diagnosis. She suffers no complications. A Minor's iodine-scratch test is performed 6 and 14 months after the procedure and remains negative. Follow-up is 15 months with a very good aesthetic result .This 85 year-old male suffered a tumor at the inferior part of the left parotid gland, confirmed by a CT scan. A total parotidectomy with dissection and preservation of the facial nerve was performed because the tumor affected the deep part of the gland. Ten mL of fat was put in the surgical field (for 51 gr of tissue removed). Pathology showed a Warthin's tumor (or adenolymphoma). A slight facial paresis completely resolved 6 weeks later. Follow-up is 46 months. The cosmetic result is very good even there is a moderate atrophy of the fat graft and no complain of gustatory sweat syndrome is experienced by the patient. At one year, the Minor's iodine-scratch test is negative. A CT scan has been made 4 years after the procedure. While the cosmetic result and the symmetry are good, CT scan show a moderate atrophy of fat Figures  and 4.A 42 year-old woman underwent 3 years ago a superficial parotidectomy for a benign tumor of the parotid gland (Warthin's tumor) with immediate reconstruction by an autologous fat graft (13 mL). After that procedure, the result remained very good on the aesthetic point of view for 11 months, until a weight loss of 17 kg leading to a partial atrophy of the fat graft and subsequently to a clinical preauricular defect at the 19th postoperative month. But the result remains good and clearly better than without any immediate reconstruction . There iSubjectively, all the patients were asymptomatic for Frey's syndrome. Minor's starch-iodine test is used to evaluate potential perspiration of the preauricular skin during mastication. This test consists of the application of an iodine-alcoholic solution on the concerned skin and when dried, application of starch. Then the patient masticates a chewing gum. The test is considered positive if the white powder of starch becomes black, traducing that skin perspirates. The Minor's starch-iodine test was performed 6 months to more than 1 year after the procedure for 8 patients and remains negative for all those patients.The cosmetic results are subjectively considered by the patient and the surgeons as good to very good in all cases (mean postoperative follow-up of 21 months (range: 3–60)). A surprisingly slight to moderate atrophy of the fat graft is clinically observed in the long-term follow-up for all the patients, while more marked for two of the three irradiated patients . This isThe Frey syndrome, also called gustatory sweat syndrome or auriculotemporal syndrome, is characterized by a sweating and a flushing and/or an erythema of the cheek area during mastication after parotid surgery . It affeIt is caused by a regeneration of the cut secretomotor parasympathetic fibers between the facial nerve and the branches of the auriculotemporal or greater auricular nerves, responsible for an aberrant innervation of sweat glands and subcutaneous vessels, leading to the physiopathology of that syndrome. Like Jeong et al. who presented recently a paper on that subject , we feelMany procedures are described to avoid or to treat the postoperative preauricular deformity and/or Frey's syndrome secondary to a parotidectomy; all of them are based on the principle of the interposition of a barrier between the facial nerve and the skin flap of the cheek. Considering autologous tissue, some authors used the sternocleidomastoid muscle flap , 7, a SMAcellular human dermal matrix has also been used , 18, as Some authors used fat tissue: dermis-fat tissue , 20–22 oOthers use a two-stage surgical approach, with dermofat graft and lipofilling for the treatment of established Frey's syndrome and facial depression deformity, secondary to a previous parotidectomy .We developed immediate reconstructive option after a case of secondary correction leading to a long lasting and permanent facial paresis. Secondary procedure can be useful in case of excessive fat resorption. We never did it because all the patients were satisfied with the aesthetic result.Recently, Jeong et al. proposed to use the buccal fat pad . NonsurgAutologous fat graft is an easy technique widely used in cosmetic surgery to correct folds of the face  and in reconstructive surgery to remodel soft tissue, to enlarge or to resurface them. This technique has many advantages: unlimited availability, no additional scarring, no donor site morbidity, little time consuming , and very good long-term results on the aesthetic as well as on the functional point of view. Coleman emphasizes the less traumatic technique possible for fat harvesting and placement, to preserve adipocytes. He insists on the fact that minimal amounts of fat should be transferred, in an intricate nest of tunnels in superimposed layers, maximizing the contact with surrounding tissues and the neovascularization of the adipocytes . ConcernConcerning the cleansing technique, Coleman advocates the centrifugation for many reasons such as removing nonviable fat aspirate components  , 32. HowMoreover, if some authors report no difference in fat preparation techniques, others show increased graft survival rates after washing procedure , 37. en bloc. Following Coleman, this should lead to a very low survival of the graft. Our results show, on the contrary, a very good survival of the graft, leading to good or very good reproducible long-term results on the clinical  and on the radiological points of view. Even if there is a partial resorption of the fat graft, the clinical, functional, and radiological results are very encouraging.On the other hand, concerning the technique of injection, Coleman emphasizes the importance of the multilayered injection technique of a small amount of fat. In the case of a parotidectomy, this option does not exist anymore and we have no other option than to graft the faten bloc use of the fat transfer in the operative field shows an unexpected very good survival of the graft. Even if this series is limited, the results are very encouraging and we think that autologous fat grafting has a place in the choice of alternative options.Among the options to avoid complications of parotidectomy (Frey's syndrome and preauricular deformity), autologous fat transfer represents a very interesting option: unlimited availability of the fat tissue, no additional scarring, no donor site morbidity, not time consuming, very good to excellent, and reproducible long-term results on the aesthetic as well as the functional point of view. Our technique of


The purpose of this study was to use the body painting method to teach hand anatomy to a group of preclinical medical students.Students reviewed hand anatomy using the traditional method and body painting exercise. Feedback and retention of the anatomy-related information were examined by a questionnaire and multiple-choice questions, respectively, immediately and 1 month after the painting exercise.Students agreed that the exercise was advantageous and helped facilitate self-active learning after in-class anatomy lessons. While there was no significant difference in knowledge retention between the control and experimental groups, the students appreciated the exercise in which they applied body paint to the human body to learn anatomy.The body painting was an efficient tool for aiding the interactive learning of medical students and increasing the understanding of gross anatomy. In medical schools, gross anatomy is the branch of biology in which the human body is studied using a cadaver and often requires a great deal of effort for students to memorize the various structures. However, medical students generally have no chance to directly transfer their knowledge from the laboratory to a living body  and it iBody painting, a form of body art where the human skin is painted, has been reported as a useful adjunct to living anatomy, traditional anatomy courses, and clinical skills classes . To use N=96) were invited to participate in this project. All participating students signed individual consent forms, and ethical approval was provided by the Ethics Committee of Walailak University. Non-toxic water-washable body paints of various colors and brushes of different sizes were used for the body painting activity. Before beginning the session, the students performed tests to determine sensitivity to the paints used.First- and second-year preclinical medical students of Walailak University (N=8) for reviewing hand anatomy by different methods. The experimental subgroups had 20 min to paint only one structure – bones, muscles, nerve innervation and dermatome, or blood supply – on the hand of a partner and another 20 min to paint their own hand. These subgroups had an additional 20 min for discussion. Meanwhile, students in the control group studied hand anatomy using a handout and textbook for 1 h. The students’ short-term retention of the anatomy-related information was evaluated in both the experimental and control groups by a set of multiple-choice questions. Feedback was obtained from the experimental group by a structured questionnaire using a six-point Likert scale with agree/disagree categories , the number of students in the experimental group who selected the correct answer was higher than the number in the control group immediately following the body painting session a. The saIn the twenty-first century, many students are becoming dependent on the Internet for receiving information and seeking additional resources. Therefore, the attitude toward and the teaching tools used for the process of teaching basic medical sciences, including anatomy in medical school, should be modified according to changes in behavior patterns. Innovations such as SDL, problem-based learning (PBL), and computer-assisted learning have been discussed as means to understand living and surface anatomy and to replace the dissection of human cadavers . In the The shift of traditional teaching methods to an integrated teaching approach using body painting has long been reported , 9. AparHere, our results correspond with other reports that body painting is a useful tool for teaching anatomy , 13. Wit