Neck muscle weakness and head drop are well recognised in patients with Amyotrophic lateral sclerosis (ALS), but an objective characterisation of the consequent head movement impairment is lacking. The aim of this study was to quantitatively characterise head movements in ALS compared to aged matched controls.We evaluated two groups, one of thirteen patients with ALS and one of thirteen age-matched controls, during the execution of a series of controlled head movements, performed while wearing two inertial sensors attached on the forehead and sternum, respectively. We quantified the differences between the two groups from the sensor data using indices of velocity, smoothness and movement coupling (intended as a measure of undesired out of plane movements).P < 0.05, Cohen’s d > 0.8), reduced smoothness and greater presence of coupled movements with respect to the controls. A significant reduction of angular velocity  in extension, axial rotation and lateral flexion was observed when patients were asked to perform the movements as fast as possible.Results confirmed a general limitation in the ability of the ALS patients to perform and control head movements. High inter-patient variability was observed due to a wide range of observed functional impairment levels. The ability to extend the head backward and flex it laterally were the most compromised, with significantly lower angular velocity (This pilot study is the first study providing a functional objective quantification of head movements in ALS. Further work involving different body areas and correlation with existing methods of evaluating neuromuscular function, such as dynamometry and EMG, is needed to explore the use of this approach as a marker of disease progression in ALS. Amyotrophic lateral sclerosis (ALS), also known as motor neurone disease is a degenerative disease primarily of motor neurones that leads to progressive muscle weakness. The consequences in terms of motor function differ depending on the extent to which upper and lower motor neurons are affected by the degeneration . The onsA quantification of the interaction between neck muscle weakness due to ALS and consequent functional limitation, to the authors’ knowledge, has only been performed by testing muscle weakness with manual muscle testing and by assessing the ability to perform ADL using a clinical scale . The maiIn an attempt to investigate the ability of different cohorts of participants to perform head movements, a number of researchers have measured both the velocity and the smoothness of these movements –10. The An additional feature of potential interest for a quantitative assessment of specific residual abilities is the so-called coupling of the movements . Pure heThe aim of this pilot study was to quantitatively characterise head movements with regard to velocity, smoothness and coupling in ALS compared to aged matched controls.A cohort of thirteen individuals affected by neck muscle weakness due to ALS  participated in the study. The severity of the disease was assessed in patients by using the ALS Functional Rating Scale-Revised (ALSFRS-R). The ALSFRS-R is a validated ordinal scale, commonly used in clinics to estimate a patient’s degree of functional impairment . The scaThe assessment was performed using two inertial magneto units (IMUs) , extension (E), axial rotation  and lateral flexion , starting from their own neutral position (NP) and looking ahead. To make sure they were well familiarized with the protocol, all participants were asked to practice the sequence of movements before the acquisition session started. All movements were performed first reaching the maximum amplitude , then at maximum speed (i.e. the participants were asked to move their head as fast as possible). The first condition was used to evaluate participants’ ability to perform head movements while they endeavoured to reach their maximum range of motion in each direction, but still in a controlled state. The second condition was used to evaluate participants’ ability to perform head movements in a less controlled state. Each movement was repeated three times. The participants with ALS were asked to perform the movements at maximum speed only if they felt comfortable with doing it. The assessment took approximately 30 minutes.Data were analysed using custom procedures written in MATLAB . Prior to the analysis, signals were filtered using a 4th order zero-lag Butterworth filter. The cut-off frequency value was then conservatively set to 10 Hz, after having checked the frequency content of signals collected. Thereafter, IMUs orientation was estimated in order to align the sensor placed on the forehead with the sensor placed on the sternum and remove orientation errors that could occur due to their placement. A functional calibration approach, described in detail in previous studies , 16, wasEvery movement (M) was sub-divided in two phases: movement away from neutral position (M1) and movement back to neutral position (M2), as they involve different groups of muscles. For each movement the end of the first phase was detected when the angular velocity first crossed the zero , which coincided with the moment when the direction of the movement is reversed .m), peak angular velocity (ωp), normalized jerk (NJ), and ratio of movement coupling (RMC). ωm and ωp were calculated using the signal recorded by the tri-axial gyroscope. To calculate ωm the signal was averaged through the duration of the movement while, to evaluate ωp, its peak value was considered.The following parameters were used to quantify the head movements: mean angular velocity (ωThe jerk (J) was initially computed as the first time derivative of the linear acceleration measured by the tri-axial accelerometer. Then, a time-integrated squared jerk was calculated and normalized with respect to the mean absolute acceleration and duration of the movement, using the following equation :NJ=12Taovements .i is the axis around which the primary movement is performed, j and k are the other two main anatomical axes and Ai, Aj, and Ak are the areas under the angular velocity time-curves measured along those axes.As described in the introduction, a pure primary movement would entail a rotation in only one of the three main anatomical planes. In this case, the direction of the angular velocity would coincide with the direction of the main anatomical axis perpendicular to the anatomical plane in which the movement is performed and the relevant angular velocity signal would be the highest among the three recorded ones. The presence and amount of coupled movements, on the contrary, entails higher values also of the other angular velocity components. The presence of coupled movements was hence quantified using the following ratio:σC are the mean and the standard deviation values of the parameter P measured in the control group.Finally, in order to evaluate the deviation of each specific parameter measured in patients from the reference data obtained in the control group, a Z-score was used, calculated as :ZPi={PCCS) was calculated for each patient, as associated to the performance of a specific movement:By summing all the scores obtained for different parameters, a composite score ) for a single measurement was used . AccordiNormality of the data was verified for each parameter and movement using a Shapiro-Wilk test and parametric (independent t-test) or non-parametric (Mann-Whitney U-test) tests were then consistently adopted to quantify differences between the two groups. In both cases, statistical significance was set at an alpha level of 0.05. Cohen’s d was also computed and used as an indicator of the effect size. According to the interpretation scale reported in literature , the effAdditionally, Spearman’s rank correlation coefficient (ρ) was calculated to evaluate the relationship between the Z-scores computed for each patient and his/her ALSFRS-R score. Statistical significance for the correlation between the Z-score and the ALSFRS-R score was set at an alpha level of 0.05.All participants performed the head movements to reach the maximum amplitude. Among the 13 ALS participants, only a subgroup of 9  was able to perform the head movements when asked to reach their maximum speed See .ICC values obtained for all movements, in trials performed at both maximum amplitude and maximum speed, are given in m was significantly lower in the patient group in the extension and in the axial rotation both from  and back  to the neutral position and also in the lateral flexion back to neutral position . Similar results were observed in the ωp, where significantly lower values were measured in the ALS group, for the same movements  and for the lateral flexion from neutral position . A significant reduction of movement smoothness was observed in ALS patients in the extension , flexion back to neutral position  and lateral flexion  movements. A higher presence of coupled movements was observed in the ALS group in all movements , except for the lateral flexion from neutral position. As highlighted in A comparison between the typical signals obtained from a control individual and an ALS patient  in the ALS group in extension, axial rotation and lateral flexion from the neutral position  of movement smoothness in any of the movements performed, while the presence of coupled movements was significantly higher  in the flexion and in the axial rotation movements, both from and back to the neutral position.The results concerning the trials performed reaching the maximum speed, are shown in CS values obtained for the E1 movement in the maximum amplitude task. CS obtained for each patient in E1, performed reaching the maximum amplitude, as a function of the patient’s ALSFRS-R scores. The evident absence of a correlation between the two quantities was confirmed by the non-significance (p = 0.548) of the Spearman correlation coefficient.The aim of this pilot study was to quantitatively characterise head movements with regard to velocity, smoothness and coupling in ALS compared to aged matched controls. Despite the relatively small number of participants enrolled in this study, which represents a drawback of investigating a rare pathology and a limitation of this work, reported results demonstrated a reduced ability of patients tested to perform head movements. In particular, the observed movements in ALS, when performed at a self-selected speed, appeared to be characterized by a reduced mean and peak velocity, a reduced smoothness in a subset of movements and a higher presence of coupling movements in almost all the movements, compared to controls. In order to draw stronger conclusions on the clinical meaning of the proposed method, further studies involving a larger number of patients are needed.Despite their limited ability, the patients managed to perform the chosen tests, which were minimally invasive for them. The level of agreement between the three repetitions performed for each movement and parameter was satisfactory overall, with ICC values ranging from moderate to high, except in a few cases. This is a very encouraging result and supports progression towards the definition of a reliable quantitative approach to overcome the current limitations of the MMT and HHD, reported in the introduction. In addition, the proposed approach might be used to measure specific neck muscle impairment, currently not provided by clinical scales such as the ALSFRS-R, which could be used in the longitudinal assessment of changes or to drive personalised intervention, such as the choice of a cervical orthosis.Mean and peak velocities were significantly reduced in the ALS group in a subset of movements in trials at maximum amplitude and in trials at maximum speed. Those results confirmed that angular velocity is a viable parameter to identify and quantify movement impairment in ALS patients, as previously reported in patients affected by cervical dystonia . The redThe movements performed by the ALS patients, when reaching the maximum amplitude, were significantly less smooth in extension, flexion back to neutral position and lateral flexion, as illustrated by the curves presented in The smoothness results obtained in trials performed reaching the maximum amplitude were not confirmed in trials performed reaching the maximum speed. The presence of lower jerk values in movement performed at higher speed was consistent with experimental values found in previous studies . The difValues obtained for the RMC in trials at maximum amplitude showed a higher presence of coupled movements when the exercises were performed by ALS patients, as can be observed by comparing two typical angular velocity signals from a control individual and an ALS patient . The scoThis is the first study providing a functional objective quantification of head movements in ALS. The reported results demonstrate that head movements in ALS patients, compared to age–matched controls, are characterized by reduced smoothness and velocity and by increased presence of coupling movements, which are consistent with weakness of neck extensor muscles. The ratio of movement coupling described in this study is a viable functional parameter. Further work involving different body areas and correlation with existing methods of evaluating neuromuscular function, such as dynamometry and EMG, is needed to explore the use of this approach as a marker of disease progression in ALS.


The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times.Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies.E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network.The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods  even when only a small number of processors is used.The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.The online version of this article (doi:10.1186/s12859-016-1452-4) contains supplementary material, which is available to authorized users. Computational simulation and optimization are key topics in systems biology and bioinformatics, playing a central role in mathematical approaches considering the reverse engineering of biological systems –9 and thRecent efforts have been focused on scaling-up the development of dynamic (kinetic) models –25, withScatter search is a promising metaheuristic that in sequential implementations has been shown to outperform other state of the art stochastic global optimization methods , 44–50. the combination of a coarse-grained distributed-memory parallelization paradigm and an underlying fine-grained parallelization of the individual tasks with a shared-memory model, in order to improve the scalability.an improved cooperation scheme, including an information exchange mechanism driven by the quality of the solutions, an asynchronous communication protocol to handle inter-process information exchange, and a self-adaptive procedure to dynamically tune the settings of the parallel searches.Here we significantly extend and improve this method by proposing a new parallel cooperative scheme, named self-adaptive cooperative enhanced scatter search (saCeSS) that incorporates the following novel strategies: E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing a very significant reduction of computation times with respect to previous methods  even when only a small number of processors is used. Therefore, we believe that this new method can play a key role in the development of large-scale dynamic models in systems biology.We present below a detailed description of saCeSS, including the details of a high-performance implementation based on a hybrid message passing interface (MPI) and open multi-processing (OpenMP) combination. The excellent performance and scalability of this novel method are illustrated considering a set of very challenging parameter estimation problems in large-scale dynamic models of biological systems. These problems consider kinetic models of the bacterium Here we consider the problem of parameter estimation in dynamic models described by deterministic nonlinear ordinary differential equation models. However, it should be noted that the method described below is applicable to other model classes.p (unknown model parameters) that minimizes the mismatch between model predictions and the measurements. Such a mismatch is given by a cost function, i.e. a scalar function that quantifies the model error .Given such a model and a measurements data set , the objective of parameter estimation is to find the optimal vector The mathematical statement is therefore a nonlinear programming (NLP) problem with differential-algebraic constraints (DAEs). Assuming a generalized least squares cost function, the problem is:p to minimize Find nε is the number of experiments, W is a scaling matrix that balances the residuals.where In addition, the optimization above is subject to a number of constraints: f is the nonlinear dynamic problem with the differential-algebraic constraints (DAEs), x is the vector of state variables and xo are their initial conditions; g is the observation function that gives the predicted observed states . The RefSet is the analogous concept to the population in genetic or evolutionary algorithms but its size is considerably smaller than in those methods. A consequence is that the degree of randomness in scatter search is lower than in other population based metaheuristic and the generation of new solutions is based on the combination of the RefSet members. Another difference between scatter search and other classical population based methods is the use of the improvement method which usually consists of local searches from selected solutions to accelerate the convergence to the optimum in certain problems, turning the algorithm into a more effective combination of global and local search. This improvement method can of course be ignored in those problems where local searches are very time-consuming and/or inefficient.Scatter search (SS)  is a popfive-step template  based on the upper and lower bounds. Thus, two solutions are “too close” to each other if the maximum difference of its components is higher than a given threshold, with a default value of 1e-3. This mechanism contributes to increase the diversity in the RefSet thus preventing the search from stagnation.RefSet members (lines 13-23). The new solutions resulting from the combinations are generated in hyper-rectangles defined by the relative position and distance of the RefSet members being combined. This is accomplished by doing linear combinations in every dimension of the solutions, weighted by a random factor and bounded by the relative distance of the combined solutions. More details about this type of combination can be found in [Solution combination: This step consists in pair-wise combinations of the found in .RefSet update: The solutions generated by combination can replace the RefSet members if they outperform their quality (line 53). In order to preserve the RefSet diversity and avoid premature stagnation, a (1+ λ)[RefSet member that defined the hyper-rectangle where the new solution was created. In other words, a solution can only replace its “parent”. What is more, among all the solutions generated in the same hyper-rectangle, only the best of them will replace the “parent”. This mechanism avoids clusters of similar solutions in early stages of the search which could produce premature stagnation. a (1+ λ) evolutioRefSet solution has not been updated during a predefined number of iterations, we consider that it is a local solution and replace it with a new random solution in the RefSet. This is carried out by using a counter (nstuck) for each RefSet member (lines 54-59).Extra mechanisms: eSS includes two procedures to make the search more efficient. One is the so-called “go-beyond” strategy and consists in exploiting promising search directions. If a new solution outperforms its “parent”, a new hyper-rectangle following the direction of both solutions and beyond the line linking them is created. A new solution is created in this new hyper-rectangle, and the process is repeated varying the hyper-rectangle size as long as there is improvement (lines 24-49). The second mechanism consists in a stagnation checking. If a local.n1 function evaluations), and the rest. Once the first local search has been performed, the next ones take place after local.n2 function evaluations from the previous local search. In this case, the initial point is chosen from the new solutions created by combination in the previous step, balancing between their quality and diversity. The diversity is computed measuring the distance between each solution and all the previous local solutions found. The parameter balance gives more weight to the quality or to the diversity when choosing a candidate as the initial point for the local search. Once a new local solution is found, it is added to a list. There is an exception when the best_sol parameter is activated. In this case, the local search will only be applied over the best found solution as long as it has been updated in the incumbent iteration. Based on our previous experience, this strategy is only useful in certain pathological problems, and should not be activated by default.Improvement method. This is basically a local search procedure that is implemented in the following form (see Algorithm 2): when the local search is activated, we distinguish between the first local search  where the eSS is executed isolated and sparse individual exchanges are performed among islands to link different subsets. This solution drastically reduces the communications between distributed processes. However, its scalability is again heavily restrained by the small size of the reference set in the eSS method. Reducing the already small reference set by dividing it between the different islands will have a negative impact on the convergence of the eSS. Thus, building upon the ideas outlined in [RefSet, while they cooperate modifying the systemic properties of the individual searches.In the case of the enhanced scatter search method, finding parallelism in the sequential algorithm is straightforward: the majority of time-consuming operations  are located in inner loops (e.g. lines 13-23 in Algorithm 1) which can be easily performed in parallel. However, since the main loop of the algorithm (line 7 in Algorithm 1) presents dependencies between different iterations and the dimension of the combination loop is rather small, a fine-grained parallelization would limit the scalability in distributed systems. Thus, a more effective solution is a coarse-grained parallelization that implies finding a parallel variant of the sequential algorithm. An island-model approach  can be ulined in , here weCurrent High Performance Computing (HPC) systems include clusters of multicore nodes that can benefit from the use of a hybrid programming model, in which a message passing library, such as MPI (Message Passing Interface), is used for the inter-node communications while a shared memory programming model, such as OpenMP, is used intra-node. Even though programming using a hybrid MPI+OpenMP model requires some effort from application developers, this model provides several advantages such as reducing the communication needs and memory consumption, as well as improving load balance and numerical convergence .Thus, the combination of a coarse-grained parallelization using a distributed-memory paradigm and an underlying fine-grained parallelization of the individual tasks with a shared-memory model is an attractive solution for improving the scalability of the proposal. A hybrid implementation combining MPI and OpenMP is explored in this work. The proposed solution pursues the development of an efficient cooperative enhanced Scatter Search, focused on both the acceleration of the computation by performing separate evaluations in parallel and the convergence improvement through the stimulation of the diversification in the search and the cooperation between different islands. MPI is used for communication between different islands, that is, for the cooperation itself, while OpenMP is used inside each island to accelerate the computation of the evaluations. Figure ndiverse solutions, in the combination loop to generate new solutions, and in the go-beyond method . Thus, we have decided to perform all these evaluations in parallel using the OpenMP library.The most time consuming task in the eSS algorithm is the evaluation of the solutions . This task appears in several steps of the algorithm, such as in the creation of the initial random Algorithm 3 shows a basic pseudocode for performing the solutions’ evaluation in parallel. As can be observed, every time an evaluation of the solutions is needed, a parallel loop is defined. In OpenMP, the execution of a parallel loop is based on the fork-join programming model. In the parallel section, the thread running creates a group of threads, so that the set of solutions to be evaluated are divided among them and each evaluation is performed in parallel. At the end of the parallel loop, the different threads are synchronized and finally joined again into only one thread. Due to this synchronization, load imbalance in the parallel loop can cause significant delays. This is the case of the evaluations in the eSS, since different evaluations can have entirely different computational loads. Thus, a dynamic schedule clause must be used so that the assignment can vary at run-time and the iterations are handed out to threads as they complete their previously assigned evaluation. Finally, at the end of the parallel region, a reduction operation allows for counting the number of total evaluations performed.islands). For this cooperation to be efficient in large-scale difficult problems, each island must adopt a different strategy to increase the diversification in the search. The idea is to run in parallel processes with different degrees of aggressiveness. Some processes will focus on diversification  increasing the probabilities of finding a feasible solution even in a rough or difficult space. Other processes will concentrate on intensification  and speed-up the computations in smoother spaces. Cooperation among them enables each process to benefit from the knowledge gathered by the rest. However, an important issue to be solved in parallel cooperative schemes is the coordination between islands so that the processes’ stalls due to synchronizations are minimized in order to improve the efficiency and, specifically, the scalability of the parallel approach.The coarse-grained parallelization proposed is based on the cooperation between parallel processes  that perform a sequential eSS each. The master process is in charge of the cooperation between the islands. The main features of the proposal scheme presented in this work are: In the following subsections we describe in detail the implementation of the new self-adaptive cooperative enhanced Scatter Search algorithm (saCeSS), focusing on these three main features and providing evidences for each of the design decisions taken.Some fundamental issues have to be addressed when designing cooperative parallel strategies , such asPromising solutions obtained in each island are sent to the master process to be spread to the rest of the islands.The cooperative search strategy proposed in this paper accelerates the exploration of the search space through different mechanisms: launching simultaneous searches with different configurations from independent initial points and including cooperation mechanisms to share information between processes. The exchange of information among cooperating search processes is driven by the quality of the solutions obtained. promising. The accumulated knowledge of the field indicates that information exchange between islands should not be too frequent to avoid premature convergence to local optima [On the one hand, a key aspect of the cooperation scheme is deciding when a solution is considered l optima , 65. ThuRefSet to be replaced with the incoming solutions, that is, with promising solutions from other islands, should be carefully decided. One of the most popular selection/replacement policies for incoming solutions in parallel metaheuristics is to replace the worst solution in the current population with the incoming solution when the value of the latter is better than that of the former. However, this policy is contrary to the RefSet update strategy used in the eSS method, going against the idea that parents can only be replaced by their own children to avoid loss of diversity and to prevent premature stagnation. Since an incoming solution is always a promising one, replacing the worst solution will promote this entry to higher positions in the sorted RefSet. It is easy to realise that, after a few iterations receiving new best solutions, considering the small RefSet in the eSS method, the initial population in each island will be lost and the RefSet will be full of foreign individuals. Moreover, all the island populations would tend to be uniform, thus, losing diversity and potentially leading to rapidly converge to suboptimal solutions. Replacing the best solution instead of the worst one solves this issue most of the times. However, several members of the initial population could still be replaced by foreign solutions. Thus, the selection/replacement policy proposed in this work consists in labeling one member of the RefSet as a cooperative member, so that a foreign solution can only enter the population by replacing this cooperative solution. The first time a shared solution is received, the worst solution in the RefSet will be replaced. This solution will be labeled as a cooperative solution for the next iterations. A cooperative solution is handled like any other solution in the RefSet, being combined and improved following the eSS algorithm. It can also be updated by being replaced by its own offspring solutions. Restricting the replacement of foreign solutions to the cooperative entry, the algorithm will evolve over the initial population and still promising solutions from other islands may benefit the search in the next iterations.On the other hand, the strategy used to select those members of the RefSet appeared to be stuck. In the cooperative scheme this strategy may punish the cooperative solution by replacing it too early. In order to avoid that, a nstuck larger than that of other members of the RefSet is assigned to the cooperative solution.As described before, the eSS method already includes a stagnation checking mechanism (lines 54–59 in Algorithm 1) to replace those solutions of the population that which cannot be improved in a certain number of iterations of the algorithm by random generated solutions. Thus, diversity is automatically introduced in the eSS when the members in the star topology, is used in this work, since it enables different components of the parallel algorithm to be tightly coupled, thus quickly spreading the solutions to improve the convergence. The master process is in the center of the star and all the rest of the processes (slaves) exchange information through the master. The distance between any two slaves is always two, therefore it avoids communication delays that would harm the cooperation between processes.An important aspect when designing the communication protocol is the interconnection topology of the different components of the parallel algorithm. A widely used topology in master-slave models, the The communication protocol is designed to avoid processes’ stalls if messages have not arrived during an external iteration, allowing for the progress of the execution in every individual process. Both the emission and reception of the messages are performed using non-blocking operations, thus allowing for the overlap of communications and computations. This is crucial in the application of the saCeSS method to solve large-scale difficult problems since the algorithm success heavily depends on the diversification degree introduced in the different islands that would result in an asynchronous running of the processes and a computationally unbalanced scenario. Figure The adaptive procedure aims to dynamically change, during the search process, several parameters that impact the success of the parallel cooperative scheme. In the proposed solution, the master process controls the long-term behavior of the parallel searches and their cooperation. An iterative life cycle model has been followed for the design and implementation of the tuning procedure and several parameter estimation benchmarks have been used for the evaluation of the proposal in each iteration, in order to refine the solution to tune widespread problems.First, the master process is in charge of the threshold selection used to decide which cooperative solutions that arrive at the master are qualified to be spread to the island. If the threshold is too large, cooperation will happen only sporadically, and its efficiency will be reduced. However, if the threshold is too small, the number of communications will increase, which not only negatively affects the efficiency of the parallel implementation, but also is often counterproductive since solutions are generally similar, and the receiver processes have no chance of actually acting on the incoming information. It has also been observed that excess cooperation may rapidly decrease the diversity of the parts of the search space explored (many islands will search in the same region) and bring an early convergence to a non-optimal solution. For illustrative purposes Fig. aggressive island performs frequent local searches, trying to refine the solution very quickly and keeps a small reference set of solutions. It will perform well in problems with parameter spaces that have a smooth shape. On the other hand, conservative islands have a large reference set and perform local searches only sporadically. They spend more time combining parameter vectors and exploring the different regions of the parameter space. Thus, they are more appropriate for problems with rugged parameter spaces. Since the exact nature of the problem at hand is always unknown, it is recommended to choose, at the beginning of the scheme, a range of settings that yields conservative, aggressive, and intermediate islands. However, a procedure that adaptively changes the settings in the islands during the execution, favoring those settings that exhibit the highest success, will further improve the efficiency of the evolutionary search.Second, the master process is used as a scoreboard intended to dynamically tune the settings of the eSS in the different islands. As commented above, each island in the proposed scheme performs a different eSS. An dimRefSet, defined in line 1 in Algorithm 1).Number of elements in the reference set .Minimum number of iterations of the eSS algorithm between two local searches .Balance between intensification and diversification in the selection of initial points for the local searches  used by the sequential eSS algorithm, and whose selection may have a great impact in the algorithm performance. Namely, these settings are: All these settings have qualitatively the same influence on the algorithm’s behavior: large setting values lead to conservative executions, while small values lead to aggressive executions.good solutions; and (2) for each island, the moment when its last solution has been received, to prioritize those islands that have more recently cooperated. A good balance between these two factors will produce a more accurate scoreboard. To better illustrate this problem Fig. t=2000, process 5 has a large number of communications performed, however, all these communications were performed a considerable time ago. On the other hand, process 2 has just communicated a new solution, but presents a smaller number of total communications performed. To accurately update the scoreboard, the rate of each island is calculated in the master as the product of the number of communications performed and the time elapsed from the beginning of the execution until the last reception from that island. In the example above, process 6 achieves a higher rate because it presents a better balance between the number of communications and the time elapsed since the last reception.Designing a self-adaptive procedure that identifies those islands that are becoming failures and those that are successful is not an easy task. To decide the most promising islands, the master process serves as a scoreboard where the islands are ranked according to their potential. In the rating of the islands, two facts have to be considered: (1) the number of total communications received in the master from each islands, to identify promising islands among those that intensively cooperates with new worst islands is also cumbersome. Those processes at the bottom of the scoreboard are there because they do not communicate sufficient solutions or because a considerable amount of time has passed since their last communication. However, they can be either non-cooperating (less promising) islands or more aggressive ones. An aggressive thread often calls the local solver, performing longer iterations, and thus being unable to communicate results as often as conservative islands can do so. To better illustrate this problem, Fig. t=60, process 4 will be at the top of the scoreboard because it often obtains promising solutions. This is a conservative island. Process 3 will be at the bottom of the scoreboard because at that time it has not yet communicated a significant result. The reason is that process 3 is an aggressive slave that is still performing its first local search. To accurately identify the non-cooperating islands, the master process would need additional information from islands that would imply extra messages in each iteration of the eSS. The solution implemented is that each island decides by itself whether it is evolving in a promising mode or not. If an island detects that it is receiving cooperative solutions from the master but it cannot improve its results, it will send the master a reconfiguration request. The master, will then communicate to this island the settings of the island on the top of the scoreboard.Identifying the The pseudocode for the master process is shown in Algorithm 4, while the basic pseudocode for each slave is shown in Algorithm 5.BestKnownSol), it increments the score of this slave on the board.At the beginning of the algorithm, a local variable present in the master and in each slave is declared to keep track of the best solution shared in the cooperation step. The master process sets the initial threshold, initiates the scoreboard to keep track of the cooperation rate of each slave, and begins to listen to the requests and cooperations arriving from the slaves. Each time the master receives from a slave a solution that significantly improves the current best known solution . While the VTR is usually known in benchmark problems (such as those used below), for a new problem, the VTR will be, in general, unknown. Thus, in such more realistic cases, the recommended practice in metaheuristics is to perform some trial runs and then analyze the convergence curves in order to find sensible values for the maximum number of evaluations and/or execution time.Finally, the saCeSS algorithm repeats the external loop until the stopping criterion is met. The current version can consider three different stopping criteria (or any combination among them): maximum number of evaluations, maximum execution time and a For illustrative purposes, Fig. Problem B1: genome-wide kinetic model of S. cerevisiae. It contains 276 dynamic states, 44 observed states and 1759 parameters.Problem B2: dynamic model of the central carbon metabolism of E. coli. It consists of 18 dynamic states, 9 observed states and 116 estimable parameters.Problem B3: dynamic model of enzymatic and transcriptional regulation of the central carbon metabolism of E. coli. It contains 47 dynamic states (fully observed) and 178 parameters to be estimated.Problem B4: kinetic metabolic model of Chinese Hamster Ovary (CHO) cells, with 34 dynamic states, 13 observed states and 117 parameters.Problem B5: signal transduction logic model, with 26 dynamic states, 6 observed states and 86 parameters.Problem B6: dynamic model describing the gap gene regulatory network of the vinegar fly, Drosophila melanogaster. It consists of three processes formalized with 108-212 ODEs, and resulting in a model with 37 unknown parameters.The proposed self-adaptive cooperative algorithm (saCeSS) has been applied to a set of benchmarks from the BioPreDyn-bench suite , with thnp-eSS), and a previous cooperative synchronous version (CeSS) [np-eSS algorithm consists of np independent eSS runs (being np the number of available processors) performed in parallel without cooperation between them and reporting the best execution time of the np runs. Diversity is introduced in these np eSS runs, alike in the cooperative methods, that is, each one executes a separate eSS using different strategies.Different experiments have been conducted using the saCeSS method, and its performance has been compared with two different parallel versions of the eSS, namely: an embarrassingly-parallel non-cooperative enhanced Scatter Search (n (CeSS) . The np-jPar [It should be noted that the eSS  and CeSSjPar .B3 this cluster could not be used because the execution of B3 exceeds the maximum allowed job length. Thus, another multicore heterogeneous cluster was used for this problem that consists of 4 nodes powered by two quadcore Intel Xeon E5420 CPUs with 16 GB of RAM and 8 nodes powered by two quadcore Intel Xeon E5520 CPUs with 24 GB of RAM, connected through a Gigabit Ethernet network.The experiments reported here have been performed in a multicore cluster with 16 nodes powered by two octa-core Intel Xeon E5-2660 CPUs with 64 GB of RAM. The cluster nodes were connected through an InfiniBand FDR network. For problem value-to-reach (VTR) were performed. The VTR used was the optimal fitness value reported in [The computational results shown in this paper were analyzed from a horizontal view , that isorted in . Also, sThe cooperation between processes in the coarse-grained parallelization can change the systemic properties of the eSS algorithm and therefore its macroscopic behavior. The same happens with the self-adaptive mechanism proposed. Thus, the first set of experiments shown in this section disables the fine-grained parallelization, since it does not alter the convergence properties of the algorithm, to evaluate solely the impact of the coarse-grained parallelization, as well as the self-adaptive mechanism.VTR, the mean and standard deviation execution time of all the runs in the experiment and the speedup achieved versus the non-cooperative case (10-eSS). In these experiments, the computational load is not shared among processors. Therefore, the total speedup achieved over the np-eSS method depends on the impact that the cooperation among processes produces on achieving a good result, performing less evaluations and, hence, providing a better performance. We compare the CeSS method, that exchanges the information based on a time elapsed, and where the information to be exchanged is the complete RefSet, and the proposed saCeSS method, that exchanges the information driven by the quality of the solutions through a star topology using asynchronous communications and, thus, avoiding communication delays. Additionally, to better evaluate the efficiency of the self-adaptive procedure proposed, Table Table ive case 0-eSS. In10-eSS and CeSS, both in terms of number of evaluations and execution time. As regards the CeSS method, the results can be explained both because the synchronization slows down the processes, since it implies more processes’ stalls while waiting for data, and because of the effectiveness of the information exchanged. The results of the saCeSS show that the self-adaptive approach improves the previous results even more. The main goal of this approach is to reduce the impact that the initial choice of the configurable settings may have in the evolution of the method. For instance, one issue of the CeSS algorithm is the selection of the migration time (τ), that is, the time between information sharing. On the one hand, this time has to be long enough to allow each of the threads to exploit the eSS capabilities. On the other hand, if the time is too long, cooperation will happen only sporadically, reducing its efficiency. On the contrary, in the saCeSS method proposed, the initial selection of the threshold to spread a cooperative solution, as well as the selection of the other configurable settings of the eSS method, will change adaptively during the execution progress.The results of the saCeSS (non-adaptive) show that the cooperation mechanisms and the asynchronous communication protocol proposed in the saCeSS method improve the results obtained by 10-eSS method. This is an important feature of the saCeSS, because it reduces the average execution time for each benchmark. For instance, even in the B2 problem, where the mean execution time is similar in the non-cooperative and the cooperative executions, the dispersion of the results is reduced in the cooperative case.When dealing with stochastic optimization solvers, it is important to evaluate the dispersion of the computational results. Figure np-eSS, CeSS and saCeSS) or to pure randomness. Table p-values of Dunn’s test for every pair comparison after the Kruskall-Wallis test application. Table Finally, to prove the significance of the results, a non-parametric statistical analysis has been applied to the final runtimes of the experiments over each test problem. Recent studies show that the most appropriate methods to compare the performance of different metaheuristics are the nonparametric procedures . In thisThe CeSS method presents an important issue related to its scalability, since the cooperation among islands is carried through a synchronous communication step. To assess the scalability of the coarse-grained parallelization proposed in saCeSS, experiments were carried out using 1 (that is a single eSS), 10, 20 and 40 processors. The convergence curves for B2 benchmark , to perform a fair comparison with saCeSS using 10, 20 and 40 processors respectively. The speedup was calculated accordingly. In most of the cases, the hybrid configurations obtain better performance than other configurations that only use MPI processes. In general, results show that, for the same number of processors, those hybrid configurations that achieve a good balance between intensification and diversification perform more effectively. For instance, the configuration of 5 MPI processes with 4 OpenMP threads each, achieves, in general, better speedup than the configuration with 10 MPI processes with 2 OpenMP threads each, while both use 20 processors. The exception is benchmark B4, whose performance is heavily affected by the number of different processes cooperating. That is, benchmark B4 greatly benefits from the diversity introduced with the scalability in the number of MPI processes versus the intensification of the OpenMP search. Thus, for benchmark B4, configurations using all the available processors to run MPI cooperative processes perform better.Table Figure Finally, Fig. In order to properly evaluate the novel parallel method presented here, we now compare it with a parallel version of another state of the art metaheuristic, Differential Evolution (DE ). PrevioThe convergence curves, considering problem B2 . A hybrid MPI+OpenMP implementation is proposed combining a coarse-grained parallelization, focused on stimulating the diversification in the search and the cooperation between different processes, with a fine-grained parallelization, aimed at accelerating the computation by performing separate evaluations in parallel. This novel approach results in a much more effective way of cooperation between different processes running different configurations of the scatter search algorithm.The new proposed approach has four main features: (i) a coarse-grained parallelization using a centralized master-slave approach, where the master is in charge of the control of the communications between slaves (islands) and serves as a scoreboard to dynamically tune the settings of the islands based on its individual progress; (ii) a cooperation between processes driven by the quality of the solution obtained during the execution progress, instead of by time elapsed; (iii) an asynchronous communication protocol that minimizes processes’ halts, thus improving the efficiency in a computational unbalanced scenario; and (iv) a fine-grained parallelization is included in each process to perform separate cost-function evaluations in parallel and, thus, accelerate the global search.The proposed saCeSS method was evaluated considering a suite of very challenging benchmark problems from the domain of computational systems biology. The computational results show that saCeSS attains a very significant reduction in the convergence time through cooperation of the parallel islands . A nonparametric statistical analysis shows that the saCeSS method significantly outperforms other parallel eSS approaches, such as an embarrassingly-parallel non-cooperative eSS algorithm, and a previous synchronous cooperative proposal.These results indicate that parameter estimation in large-scale dynamic models of biological systems can be feasible even when using small and low-cost parallel machines, thus opening new perspectives towards the development and calibration of whole-cell models .


We report the first case of a combined bony and soft tissue Chance fracture in the thoracic spine, with late presenting displacement following conservative management. Chance fractures are flexion-distraction injuries to the spine. They consist of disruption and longitudinal separation of the posterior elements of the vertebra, with the fracture extending through the pedicles and into the vertebral body. Both bony and soft tissue Chance fractures of the lumbar spine have been reported, as well as bony Chance fractures in the thoracic spine. This case suggests that this type of fracture is unstable and is an indication for operative management. It is also important to note that the displacement of the fracture occurred at more than eight weeks after injury, suggesting that instability may not present immediately. Chance fractures are flexion-distraction injuries to the spine, usually seen in individuals who have been restrained by a seatbelt during a road traffic accident (RTA) . First dSoft tissue Chance fractures have the same mechanism of injury, but affect the soft tissues rather than the bony structures. In a soft tissue Chance fracture there is rupture of the interspinous ligaments, facet joint capsules, and ligamentum flavum posteriorly and the posterior longitudinal ligament and intervertebral disc anteriorly . Both boWe report a case of combined bony and soft tissue Chance fracture in the thoracic spine, which, to the authors' knowledge, is the first such report in the literature.A 27-year-old man was involved in a road traffic accident (RTA), where he was a passenger restrained with a 3-point seat belt. Initial investigation at the local Emergency Department (ED) revealed posterior rib fractures and a haemothorax, which was treated by insertion of a chest drain. Further imaging of the thorax by computed tomography (CT) and magnetic resonance imaging (MRI) revealed a posterior element fracture at the level of T8.Four days later he was transferred to our centre for clinical review and further treatment with regard to his spinal injuries. Review of the imaging by the orthopaedic team at this time revealed a possible combined bony and soft tissue Chance fracture, with a rupture of the ligamentum flavum at T7/8 and a hyperintense signal in the intervertebral disc at T8/9 on MRI . The patA thoracic brace was fitted on day 7 after injury, and the patient was mobilised. Anteroposterior (AP) and lateral x-rays of the thoracic spine were taken to demonstrate the alignment of the vertebrae. The patient was discharged with paracetamol and dihydrocodeine PRN for analgesia, with follow-up planned one week later to monitor progression of the thoracic kyphosis. At the first follow-up appointment lateral X-ray of the thoracic spine showed no displacement of the vertebrae, and fortnightly follow-up was arranged thereafter.The patient developed pleuritic chest pain four days following this first appointment and was investigated by CT pulmonary angiogram (CTPA) to exclude pulmonary embolism (PE). CTPA was negative for PE and also demonstrated that there continued to be no displacement of the thoracic spine. Further x-rays at three and five weeks after discharge also demonstrated no change to thoracic alignment. However, at ten weeks following initial presentation, the patient complained of increased thoracic back pain, and lateral X-ray of the thoracic spine suggested displacement of the vertebra at the fracture site. MRI confirmed a traumatic spondylolisthesis of T8 on T9 . The patThe patient was still neurologically intact but was advised by the surgical team that the risks of continuing conservative management now greatly outweighed the risks of surgery. He underwent instrumented posterior stabilisation and fusion with allograft bone from T7 to T10 eight weeks later.Chance fractures are strongly associated with the use of lap-style seatbelts, with the seatbelt acting as the fulcrum about which the flexion-distraction injury occurs. As a result, the majority of Chance fractures reported in the literature occur in the lumbar or lower thoracic regions . Bony ChBony Chance fractures have also been described in the high thoracic region, in both the adult and paediatric populations , 4; thesBy the classification system proposed by Denis , Chance The lack of reports of thoracic combined bony and soft tissue Chance fractures in the literature made it difficult to assess the stability of the fracture in this case and to advise the patient as to the relative risks and benefits of conservative and operative management. The fracture was not a classical soft tissue Chance fracture, as it disrupted the posterior elements at T7/8, and the intervertebral disc at the level below . There wThe patient's decision to undergo conservative management in this case provides new information about the natural history of combined bony and soft tissue Chance fractures. This case suggests that this type of fracture is unstable and is an indication for operative management. It is also important to note that the displacement of the fracture occurred at more than eight weeks after injury, suggesting that instability may not present immediately.


This short paper describes the design, construction and preliminary experimental results obtained with a potential new detector for the gas chromatographic analysis of hydrocarbon species. The functional principle of the detector is the measurement of the temperature change of a catalyst as catalytic cracking occurs on its surface. The catalyst is a silicon dioxide-aluminum oxide-zeolite mixture similar to the materials used commercially in industrial riser crackers. The temperature drop which occurs at the onset of cracking is measured using two opposed thermocouple junctions. The first prototype, described in this paper, consists of a single pair of junctions. After appropriate signal conditioning , the thermocouple output is logged using an electronic integrator. Work on multi-junction cells, which is currently in progress, is also described briefly. The detection of the separated components from a gas chromatographic column is usually based upon the measurement of some property of the analyte species which is easily and clearly distinguishable from that of the carrier gas ,2.1 Incl3 to C6 branched hydrocarbons. Cracking catalysts have virtually no effect on low molecular weight hydrocarbons such as propane or n-butane. The ease of cracking usually increases with the hydrocarbon molecular weight. Among aliphatic hydrocarbons, cracking is accelerated by tertiary groupings, but is retarded by quarternary groupings . Thus, a molecule may possess functionalities that have competing effects toward the cracking process [Catalytic cracking has been of immense industrial importance since its introduction in 1927 . This is process .Catalysts for cracking are usually formulated from a silica-alumina mixture which contains 10 to 20 percent aluminum oxide. Recently, the addition of up to 15 percent synthetic sodium alumino-silicate (type X zeolite molecular sieve) has provided greater catalytic activity. Commercial catalysts often have trace quantities of rare earth metals or platinum, but this is mainly done to assist in the process of hydrocracking (cracking followed by hydrogenation).The two modifications of the prototype catalytic cracker detector which have been tested to demonstrate the potential of the approach are depicted in μV/deg in the temperature range of interest [As mentioned earlier, the functioning of the prototype catalytic cracker detector is based upon the measurement of the decrease in temperature of the coated junction (upon contact with a crackable hydrocarbon) with respect to the uncoated  or remotinterest . The outThe filter-amplifier was used with a gain setting of 1, and only served to decrease short term noise. It is, in fact, possible to eliminate this device altogether and feed the detector signal directly to the integrator. Chromatograms which are quite acceptable may be obtained in this fashion.μ1 of a mixture of n-hexane and n-octane (60/40 approximate mole percent) is shown in μV. Thus, the peaks obtained correspond to a catalyst temperature drop of between 0.12 °C and 0.16 °C. The response of the detector is selective for crackable hydrocarbons. Thus, samples of n-butane and propane were unresponsive, as was a mixture of freons. The detector responds also to alkyl substituted aromatic hydrocarbons, with the response increasing with the size of alkyl substituent. This observation is expected in view of the work by Haensel [A sample chromatogram showing the detector response to 5 Haensel . Benzene Haensel ,19.After several weeks of operation, a deposit of coke was found to have formed upon the surface of the coated junctions. This is expected, since coke formation always occurs in commercial riser crackers. The coke layer did not cause a noticeable decrease in the activity of the detector, probably because of the relatively small quantity of hydrocarbon undergoing reaction in the detector relative to that commercial situations. The coke layer is easily burned off in the presence of air.The preliminary work on the catalytic cracker detector shows that the device has a good deal of potential as the basis of a detector for the selective analysis of hydrocarbons. It does not require a continuous stream of carrier gas, as does a thermal conductivity detector (TCD), nor does it require the fuel and oxidant of a flame ionization detector (FID). The circuitry required for the detector is extremely simple, consisting of a low-cost filter amplifier instead of the bridge circuit (for the TCD) or the electrometer (for the FID). These features make the catalytic cracker detector attractive for continuous line process analysis in an industrial environment, where safety, durability and simplicity is of paramount concern.In its present form, the prototype detector has some major drawbacks. The first and most important is the low sensitivity (approximately three orders of magnitude lower than the TCD). We are addressing this problem by constructing multiple- junction thermopile cells in order to boost the signal level. Results with a six-junction cell have been very encouraging, with a nearly five-fold increase in sensitivity being observed. The six-junction prototype is similar in concept to that shown in


Liquid-crystal polymers (LCPs) are well known materials for functional sensor and actuators, because of their high-responsiveness to an electric field. Owing to their complex physical nature, however, the prediction of the functions of LCPs is a challenge. To attack this problem from a molecular point of view, a simulation study is a promising approach. In this work, for future applications of molecular dynamics simulations to problems involving an electric field, we develop an LCP model which consists of coarse-grained mesogenic molecules and smeared charges. For the smearing function of the electrostatic force, the Gauss error function is introduced. This smearing is optimized to attain a reasonable accuracy for phase transition phenomena of liquid crystal while numerical instabilities arising from the singularity of the Coulomb potential are circumvented. For swelling systems, our LCP model exhibits the characteristics of both liquid crystals and unentangled polymer chains; orientational order of the mesogenic units and Rouse-like relaxation dynamics. Our coarse-grained LCP model successfully incorporates electric charges and dipoles and is therefore applicable to problems concerning an electric field. Liquid-crystal polymers (LCPs) consist of open chain compounds containing mesogenic units. It is well known that LCPs exhibiting liquid crystal phases show high-responsiveness to external stimuli such as an electric and magnetic fields, and irradiated light ,2,3,4. CSkačej et al., developed an off-lattice coarse-grained LCP model using the soft-core Gay-Berne (SCGB) ellipsoidal potential, and carried out Monte-Carlo simulations under simplified body-force-like electric field conditions . They obIn this work, toward future molecular simulations of LCPs, we develop a coarse-grained LCP model. To enable the direct calculation of piezoelectric tensor, the dipole moment on a mesogenic unit is expressed using a pair of point charges. The Coulomb force for point charges is smeared using the Gauss error function. With using this smeared charge, the coarse-grained molecular simulations are stabilized while maintaining reasonable accuracy to investigate the phase transition phenomena of LCPs qualitatively. We perform MD simulations using this model for LCP swelling systems without the effect of an external field. The results show that our model exhibits the characteristics of liquid-crystalline orientational order and Rouse-like relaxation dynamics of unentangled polymer chains. We conclude that our coarse-grained LCP model has the possibility of hierarchically linking molecular and macroscale simulations.Q and q is modified by introducing the Gauss error function in the following manner: k is Coulomb constant that will be set to unity in our simulations, r. (ii) The singularity of Coulomb force at Our coarse-grained LCP model can be thought of as a modified version of the model of Skačej et al. ,21. The ulations ,20. In tThe implementation for mesogenic ellipsoid follows that of the course-grained MD program COGNAC ,23. As si and j, i. The length parameter for the ellipsoid pair For the intermolecular interaction between ellipsoids, SCGB potential  is used.Here, Here, In the SCGB potential, the strong core repulsion in the original GB potential is replaced by a weaker linear repulsion. The SC potential energy m stands for the potential slope and Here, In this study, the van der Waals diameter k and For the bonding potential between adjacent segments k is the spring constant, r is the bond length and Here, V including 121 LCP molecules each made up of 30 GB particles, and 3630 GB monomer particles. Therefore Our MD simulation system is a cubic cell of volume lgorithm  with a ty COGNAC .S defined asThe smearing strength of the electrostatic potential is adjustable by the parameter Equation . Figure There are two possible reasons for the smoothed phase transition behavior by introducing the electrostatic potentials. One is the influence of finite system size. The phase transition behaviors are confirmed to be little affected when the linear dimension of the system is doubled, and therefore the finite size effect is not likely to be the major cause of the smoothed phase transition behavior in the presence of electrostatic interactions. The other is the alignment of ellipsoids induced by the electrostatic potential. The ellipsoids with large spontaneous polarizations are stabilized strongly due to the head-to-tail dipolar interactions that affect the phase transition temperature ,27. Morep is the index of the normal mode, i-th ellipsoid. p dependence of the relaxation time The understanding of the relaxation dynamics is crucial for the elucidation of the mechanical characteristics of LCPs. For this purpose, we analyze the autocorrelation of normal modes itten as ,(13)Cp(l to p−2 . This rel to p−2 . TherefoWe developed an LCP model which uses coarse-grained molecules and smeared electrostatic charge toward the prediction of electrostrictive dynamics. For the smearing function of the electrostatic force, we introduced the Gauss error function. The smearing strength was optimized so as to attain a reasonable accuracy for phase transition phenomena of liquid crystals. The nematic-isotropic phase transition was smoothed and shifted to higher temperature due to the electrostatic interaction. This is because the strong polarizations on the aligned ellipsoids generate a global polarization, which stabilize the nematic phase. In addition, the relaxation analysis for the autocorrelation of normal modes revealed that our model exhibited unentangled polymer characteristics. In other words, we confirmed that our LCP model with smeared charges exhibited both characteristics of liquid crystals and polymers. Thus, we succeeded in the development of an LCP model that can react to the electric field, and our model will be useful for predicting the mechanical properties of LCPs induced by the alignment of the mesogenic units. In further studies, the piezoelectric tensor will be calculated by this model, which will enable the hierarchical linkage between microscopic modeling and macroscopic electrostrictive simulations. We believe that this linkage for the prediction of the macroscopic functions of LCPs leads to successful molecular designing for the development of LCP sensors and actuators.


Blood flow-metabolism mismatch from dynamic positron emission tomography (PET) studies with  Blood flow-metabolism mismatch from dynamic PET studies, e.g., with ,,Two main approaches have been proposed as alternatives to catheterized arterial sampling for determination of the AIF in a dynamic PET study. The fully image-based approach focuses on arterial signals associated with blood pools largely using manually placed ROIs over corresponding blood pool structures in the imaging field of view, with possible corrections to account for the contaminating effects of spillover of tracer uptake into these areas from surrounding tissue.22.1,A physiologically based pharmacokinetic Markov chain modelIt is also required that 2.2a-priori past experience with the tracer is both used in a combined Bayesian-like estimation strategy. It is important to appreciate that while the circulation model references the whole body, the extraction procedure only requires data from the field of view of the scan—not the whole body. The imaging data are reduced by segmentation/clustering to obtain a statistically representative collection of time courses. The exact number of time courses is selected adaptively based on the characteristics of the image data. Details of the segmentation techniques are given in Refs. a-priori characterization of the population behavior of the parameter vector Based on the above, the estimation of the AIF is replaced by a problem of estimating a-priori experience. Specifically, the value of a-priori mean , as opposed to direct measurement by arterial or venous blood sampling, is usually a necessity. While several methods have been proposed for this,The work presented explores the use of a statistical AIF extraction methodology based on a whole-body circulation model. The innovative element is that this model accounts for arterial, venous, and nonarterially driven signals—not just the arterially driven signal alone. Since nonarterial signals are particularly relevant in the context of breast cancer imaging, where the heart is the dominant blood pool in the field of view, it makes sense to evaluate the whole-body approach in this setting. Our group’s previous work has reported satisfactory performance for the extraction method in the context of cerebral imaging studies with The methodology used for blood extraction with ,The absolute scaling of the AIF is not resolved by the methodology. Importantly, however, the technique enables the AIF scaling to be achieved using either arterial or venous blood information. This flexibility is an advantage in settings where the complexities of direct arterial sampling would make venous measurement more appealing. In this work, a direct late-time LV-ROI value is used for scaling. No adjustment for myocardial spillover was used,Our results demonstrate that the extraction method satisfactorily recovers detailed kinetics and the blood flow-metabolism mismatch information from PET studies with 6SAIF is a reliable and reproducible AIF extraction method for diagnostic assessment of blood flow-metabolism mismatch from dynamic


Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Residual neuromuscular blockade occurs when the patient is still partially paralyzed when awakened after surgery. The condition is associated with subjective discomfort and an increased risk of respiratory complications. Use of an objective neuromuscular monitoring device may prevent residual block. Despite this, many anesthetists refrain from using the device. Efforts to increase the use of objective monitoring are time consuming and require the presence of expert personnel. A neuromuscular monitoring e-learning module might support consistent use of neuromuscular monitoring devices.The aim of the study is to assess the effect of a neuromuscular monitoring e-learning module on anesthesia staff’s use of objective neuromuscular monitoring and the incidence of residual neuromuscular blockade in surgical patients at 6 Danish teaching hospitals.In this interrupted time series study, we are collecting data repeatedly, in consecutive 3-week periods, before and after the intervention, and we will analyze the effect using segmented regression analysis. Anesthesia departments in the Zealand Region of Denmark are included, and data from all patients receiving a muscle relaxant are collected from the anesthesia information management system MetaVision. We will assess the effect of the module on all levels of potential effect: staff’s knowledge and skills, patient care practice, and patient outcomes. The primary outcome is use of neuromuscular monitoring in patients according to the type of muscle relaxant received. Secondary outcomes include last recorded train-of-four value, administration of reversal agents, and time to discharge from the postanesthesia care unit as well as a multiple-choice test to assess knowledge. The e-learning module was developed based on a needs assessment process, including focus group interviews, surveys, and expert opinions.The e-learning module was implemented in 6 anesthesia departments on 21 November 2016. Currently, we are collecting postintervention data. The final dataset will include data from more than 10,000 anesthesia procedures. We expect to publish the results in late 2017 or early 2018.With a dataset consisting of thousands of general anesthesia procedures, the INVERT study will assess whether an e-learning module can increase anesthetists’ use of neuromuscular monitoring.Clinicaltrials.gov NCT02925143; https://clinicaltrials.gov/ct2/show/NCT02925143 (Archived by WebCite® at http://www.webcitation.org/6s50iTV2x) Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Postoperative residual neuromuscular blockade, or residual blockade for short, occurs if the effects of the relaxant have not subsided or have not been sufficiently reversed before the patient is awakened . VolunteThe depth of the neuromuscular blockade can be monitored intraoperatively with a neuromuscular monitoring device that measures the muscle response to peripheral nerve stimulation. Typically, the response of the adductor pollicis muscle, adducting the thumb, is measured using an acceleromyographic neuromuscular monitor following stimulation of the ulnar nerve at the level of the wrist . In clinRepeated local educational efforts in anesthesia departments may increase the use of neuromuscular monitoring and reduce the incidence of residual blockade ,22. As tThe aim of the INVERT study is to assess the impact of an e-learning module on neuromuscular monitoring on the application frequency of objective neuromuscular monitoring and the incidence of residual neuromuscular blockade in patients monitored with a nerve stimulator.We hypothesize that the e-learning module will increase the use of objective neuromuscular monitoring significantly in both patients receiving succinylcholine and patients receiving a nondepolarizing muscle relaxant.®, Düsseldorf, Germany). Furthermore, we have chosen the interrupted time series design, in which data are collected repeatedly, at fixed intervals, before and after the intervention , in which data are collected from the same hospitals in the year leading up to the intervention. The e-learning module was implemented over a period of 2 weeks, and we area again collecting data from all departments at fixed 3-week intervals.The effect of the intervention is analyzed statistically using segmented regression analysis, testing for changes in both the level and the trend of the outcome. The design is proposed to be the strongest quasi-experimental approach for assessing the longitudinal effect of interventions and also allows description of the timing of the effect of the intervention . This deWe are including the 6 anesthesia departments at the teaching hospitals in the Zealand Region of Denmark following agreement of the head of each department to participate.We are including the following anesthesia personnel: nurse anesthetists in training, certified registered nurse anesthetists, first- though fourth-year residents in anesthesiology, and certified anesthesiologists. We are excluding personnel without clinical functions, such as administrative personnel.We are including and collecting data from all patients undergoing general anesthesia with neuromuscular blockade in each data collection period. Patients undergoing general anesthesia on more than one occasion will be included in the analyses as one case for every general anesthetic received.The investigator group has developed the e-learning module in collaboration with the Regional Unit for Development and Evaluation of Learning Technologies in the Capital Region of Denmark. Learning objectives for the module are based on a needs assessment, including focus group interviews with nurse anesthetists and anesthesiologists from 5 different Danish hospitals and clinical observations of neuromuscular monitoring use in practice (NCT02239965) as well as a previous Danish survey  and expeWe recruited a local investigator at each study site. This person is responsible for motivating the anesthesia personnel to complete the e-learning module and introduce all new employees to it. On the first day of implementation, the local investigators introduced the e-learning module. The primary investigator also visited the departments in the intervention period and introduced the study, but without revealing the primary outcome to the participants. The participating departments ensured that the personnel could complete the module during their normal work hours, such as by having colleagues cover for them while they complete the module. Course progress was logged for each anesthetist, and email reminders were sent to ensure the highest possible completion rate. The local investigator and the head of department were also informed about the completion rate throughout the implementation period. To increase awareness about the study and the e-learning module, the local investigators distributed candies and pens with the INVERT study logo at intervals. New employees joining the departments after the intervention period were also included in the study. The module is available for ongoing access, meaning that learners can still access the module, such as for use as a clinical troubleshooting tool. All anesthetic practices and medication use are at the discretion of the individual anesthetist according to local guidelines.Given the nature of the intervention, it was not possible to blind the anesthesia personnel. However, they are not informed of the specific outcomes, only that the study “aims to assess the effect of the e-learning module on use of neuromuscular monitoring”. The investigators in charge of data analysis will not have access to the data until after the final data collection period.We will assess the effect of the e-learning module on knowledge, behavior, and patient outcomes. A meta-analysis of studies on the effect of Web-based learning indicates that an e-learning module will have greatest effect on knowledge, a smaller effect on skills, and a yet smaller effect on behavior and patient-related outcomes . We haveApplication of neuromuscular monitoring in cases involving succinylcholine onlyApplication of neuromuscular monitoring in cases involving a nondepolarizing muscle relaxant (with or without succinylcholine)The primary outcome is divided because the two types of relaxants are used in different clinical situations: succinylcholine for “rapid sequence induction and intubation” and nondepolarizing relaxants for nonemergent tracheal intubation.Last recorded train-of-four (TOF) ratio  before tracheal extubation in patients receiving a nondepolarizing relaxantAdministration of the reversal agent sugammadex or neostigmine and repeated administration of the reversal agentTiming and dosage of reversal with sugammadex or neostigmine in relation to the neuromuscular monitoring valuesTime from administration of the reversal agent (sugammadex or neostigmine) to extubationTime from tracheal extubation or removal of the supraglottic airway device to discharge from the postanesthesia care unit in cases involving a nondepolarizing relaxant with or without neuromuscular monitoringPre- and postcourse test scores as a measure of course participants’ knowledgeSecondary analyses that may be performed if the data allow it include the incidence of respiratory complications, arterial oxygen desaturation, and the effect of the e-learning module at the individual level.Data are recorded in the MetaVision anesthesia information management system either automatically or manually, by the anesthetist. TOF data are recorded automatically when the neuromuscular monitoring module is activated. The anesthesia information management system saves TOF data every minute, even if the neuromuscular monitoring module measures a TOF value every 12 seconds. To ensure that the reported TOF values at the time of tracheal extubation are not erroneously measured due to lack of fixation of the patient’s hand, movements caused by the surgical personnel, or other factors, we will collect the last five TOF values before tracheal extubation and use the highest value, given that the values increase incrementally. We will develop an algorithm for choosing the last correctly measured TOF value and will perform manual validation on part of the dataset. Data manually entered into the anesthesia information management system include the type and dose of intravenous drugs and the time of tracheal extubation. The anesthetist enters these data by pressing a button in the software and can alter the time and the details, such as the dose of medicine administered, afterward if needed. Where possible, we will seek to validate these manually entered data, such as by comparing them to changes in ventilatory data from the anesthesia machine. In case of doubt about the correctness of data for a particular case, we will access the full dataset for that case in order to investigate further.A simulation-based sample size calculation revealed that the sample size necessary to detect an increase in neuromuscular monitoring from 40%-60% (with an 80% power) would require 3 consecutive data collection periods, each comprising approximately 100 patients per site, both before and after the implementation of the intervention. We expected to achieve this sample size by letting each period be 3 weeks long. The baseline value of 40% was based on a 1-month data sample from quality assurance at the participating hospitals, while the increase to 60% reflects the minimal effect size that we believe would make it worthwhile to disseminate the course to other departments. It is possible that the effect of the module could “wear off” after the 9 weeks of postintervention data collection if either a loss of knowledge occurs or the motivation to use neuromuscular monitoring decreases after the study period. To assess this, we extended the postintervention data collection period beyond what the sample size calculation indicated. This extension is ethically justifiable because prolonging the data collection does not affect patient treatment and because the data are already automatically collected in the anesthesia information management system.P value of less than 0.05 to be statistically significant.When analyzing the data, we will use segmented regression analysis . All resIn the analysis of the secondary outcomes, we will exclude cases with missing data on the outcome studied, that is, we will perform only per-protocol analyses. However, in reporting of the median TOF ratio at tracheal extubation, we will include both an analysis where a TOF count between 0 and 3 (and hence no TOF ratio reported) is included as a TOF ratio of 0 and a per-protocol analysis where only cases with a TOF ratio are included. Furthermore, we will report the proportion of patients transferred from the operating room while still tracheally intubated and, if possible, report the cause for this, such as severe residual neuromuscular blockade.The study solely uses data routinely registered in the anesthesia information management system. The Committees on Health Research Ethics for the Capital Region of Denmark have confirmed that the study does not need approval from the committee system and that there is no need for individual patient consent (protocol no. 16028220). The study is registered at clinicaltrials.gov (NCT02925143) and with The Danish Data Protection Agency (HGH-2015-063/04364).All 6 anesthesia departments agreed to participate in the study. The e-learning module was implemented simultaneously in all departments on 21 November 2016. Currently, postintervention data are being collected. We expect to publish the results in late 2017 or early 2018.We have designed a study that aims to assess the value of an e-learning module on neuromuscular monitoring at all levels of potential effect: knowledge and skills, patient care practice, and patient outcomes. We expect that the multicenter design and the large number of participants completing the e-learning module will increase the internal and external validity of results. The primary outcomes are automatically recorded in the anesthesia information management system, increasing the validity of the collected data.While randomized controlled trials are the gold standard of design in clinical research, this design is sometimes unfeasible in medical education research. Participants, in our case anesthesia personnel, completing the e-learning module cannot be randomized individually to use or not use the knowledge that they gained from the module. Similarly, while it is practically possible to randomize patients at a particular hospital to receive treatment from either an anesthetist who had completed the module or one who had not, there would be a nesting effect that could affect the results, such as due to local traditions regarding neuromuscular monitoring. The effect of the intervention could also spill over from anesthetists in the intervention group to the control group, such as through teamwork or meetings. One way of overcoming this challenge would be to conduct a cluster randomized trial , but, asThere will be some limitations to the study. The anesthetist manually enters certain data in the anesthesia information management system, which should be taken into account when interpreting the results. Studies reporting on the incidence of residual neuromuscular blockade typically measure the TOF ratio upon arrival to the postanesthesia care unit. As this approach would require the presence of investigators in all departments at all times throughout the study period, it was not possible in our study. Instead, we chose to use the data that were readily available from the anesthesia information system, namely, the last recorded TOF ratio in the operating room. For this reason, we will not obtain data on this secondary outcome for patients without monitoring with a nerve stimulator. Finally, we did not design the study to assess the effect of the e-learning module at the individual participant level, but rather at the levels of each department, as a whole. However, if possible with the data obtained, the former will described in a secondary analysis.One of the advantages of Web-based learning, such as an e-learning module, is that participant numbers can be increased with only small expenses . If the In conclusion, with a dataset consisting of thousands of general anesthesia procedures, the INVERT study will thoroughly assess whether an e-learning module can increase anesthetists’ use of neuromuscular monitoring.