Current prognostic risk scores in cardiac surgery do not benefit yet from machine learning (ML). This research aims to create a machine learning model to predict one-year mortality of a patient after transcatheter aortic valve implantation (TAVI). We adopt a modern gradient boosting on decision trees classifier (GBDTs), specifically designed for categorical features. In combination with a recent technique for model interpretations, we developed a feature analysis and selection stage, enabling the identification of the most important features for the prediction. We base our prediction model on the most relevant features, after interpreting and discussing the feature analysis results with clinical experts. We validated our model on 270 consecutive TAVI cases, reaching a C-statistic of 0.83 with CI . The model has achieved a positive predictive value ranging from 57% to 64%, suggesting that the patient selection made by the heart team of professionals can be further improved by taking into consideration the clinical data we identified as important and by exploiting ML approaches in the development of clinical risk scores. Our approach has shown promising predictive potential also with respect to widespread prognostic risk scores, such as logistic European system for cardiac operative risk evaluation (EuroSCORE II) and the society of thoracic surgeons (STS) risk score, which are broadly adopted by cardiologists worldwide. Degenerative aortic valve stenosis (AS) is the most common valvular heart disease in the developed world. If left untreated the disease has a devastating course, rapidly causing death when symptoms develop. AS is caused by calcification of the aortic valve (AV). This could also lead to aortic valve regurgitation (AR) which also causes heart failure. The treatment for severe aortic valve disease consisted until recently of surgical aortic valve replacement (SAVR). However, in recent years transcatheter aortic valve implantation  and SAPIEN 3 (127 patients), Edwards LifeSciences ;CoreValve (10 patients) and CoreValve Evolut (124 patients), Medtronic .The anonymized dataset obtained from the Catharina Hospital consisted of 270 consecutive TAVI procedures that were performed between January 2015 and December 2016 using the following different brands and models of artificial aortic valves:For most of the patients, the procedures were performed through standard transfemoral access and only 7.4% of them required an alternative access site, namely the subclavian artery (five patients), the transapical (seven patients), and the direct transaortic (eight patients).The average age of the patients, when the TAVI procedure was performed, was 80.7 years, with a minimum age of 50.3 years and a maximum age of 94 years (standard deviation of 6.2 years). In our population, 48% of the patients were female.Survived within the first year (240 patients);Non-survived within the first year ).The retrospective data were divided into two categories and one classification label was assigned to each category to create two different groups of patients according to their survival to one year from the date of TAVI, as shown in The mortality information was collected in 2019 from the census of the national population of the Netherlands. The dataset consisted of numerous numerical and categorical information data, which could be divided, as shown in The retrospective study was approved by the local ethics committee and all enrolled patients signed informed consent. The reporting of this paper adheres to the “transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” (TRIPOD) guidelines . TRIPOD The overall processing steps of our data are depicted in We have reorganized some initially given features and some have been introduced, resulting from combining original features. For example, we mention the body mass index (BMI) computed from the height and the weight. An alternative feature processing has been applied for multiple answer questionnaires by using one-hot encoding. An additional approach has been reserved for the list of prescribed medicines. After analysis with the medical experts, we added and divided them into 28 pharmacological macro-categories , according to their class of medication therapy and to their mechanism of functioning. Concerning the dates included in the original dataset, that were describing when certain events occurred prior to TAVI, it was decided to define them relative to the TAVI procedure date. Finally, we computed the intermediate and final scores  for the RAND-36 questionnaire  accordinGradient boosting on decision trees (GBDTs) is a supervised machine learning technique, which currently represents one of the state-of-the-art techniques for models based on decision trees. On the other hand, well-established neural network techniques have emerged in several fields including the one for cardiovascular outcome predictions, often providing promising results, with respect to other more classical machine learning techniques, when large datasets are involved ,9,10. GeRecently, a new categorical feature-specific classifier called CatBoost has been designed that outperforms several gradient boosting on decision trees (GBDTs) classifiers ,13 such The CatBoost classifier was used, since in clinical practice and consequently in this dataset, categorical features are common. Therefore, we can more easily exploit all the information provided in the dataset, leaving this innovative approach for pre-processing of the categorical and numerical features to the preliminary stage of CatBoost see , at eachThe second stage of CatBoost involves an algorithm that builds an ensemble model with an iterative approach. At the 1st iteration, the algorithm learns from the dataset the first decision tree, to reduce the training error. At the 2nd iteration, the algorithm learns from the dataset one more decision tree, to reduce the error made by the decision tree obtained at the 1st iteration and the algorithm repeats this procedure for all succeeding iterations until the iteration count is exceeded. This count is chosen to maximize the training of the model without overfitting the data and, therefore, reducing the generalization capabilities of the model.The feature analysis stage is achieved by exploiting a new method that, with a local-level approach and its foundations in game theory, is able to provide interpretations and explanations of machine learning models, as shown in the first stage of m for a patient j on the total amount of n patients. We obtain then the estimate of the most important features in the decision making of the model. Consequently, we reorder them from the most relevant downwards by reordering the feature vector list.We exploited the SHapley Additive exPlanations unified approach ,17, usinThe most important features were then discussed with the medical experts to find possible patterns and clinical explanations related to patient mortality. The validated relevant features which were confirmed by the clinical experts and that were found more discriminative in the decision process were used to train the final model.At the feature analysis stage, we trained the classifier on a deep decision tree by including the entire dataset. We then analyzed the model to evaluate the importance of each feature. The temporary and the final model were trained only with the most informative features by imposing a threshold, to discard all non-relevant features. We conducted also a visual inspection of the SHapley Additive exPlanations summary plot, which proved to be useful when discussing the results with the medical experts.The training parameters of the final model were chosen after performing hyperparameter research, further details are shown in k-fold cross-validation multiple times with different randomizations per iteration. The temporary models used for validation utilize the same parameters as the final one.We then identified which were more suitable for maximizing the F1 score and AUC metric, by performing The intrinsic imbalanced nature of the medical datasets, as known in the literature , led us Validation of the model was been performed with five-times leave-one-out cross-validation (LOOCV), with a dedicated pipeline for each iteration. In fact, the previously discussed random over-sampling of the minority class is applied at each iteration, but only after each test sample is removed, to reduce any possible uncertainty in the results that could be caused by the randomization of the minority class samples. LOOCV was chosen because the minority class population was limited to only 30 patients and consequently a sufficient amount of information would not have been available to train the model if a more sophisticated validation approach would have been implemented . Current state-of-the-art prognostic risk scores in cardiac surgery use the area under the curve (AUC) of the receiver operating characteristic curve (ROC or C-statistic) as the benchmark metric. However, this metric is not always the best choice, especially in the case of validation performed on a dataset with imbalanced classes. Therefore, we adopted other metrics such as sensitivity, specificity, accuracy, precision , and F1 score. As suggested in the literature, calibrated risk models are of vital importance for valid decision support ,20. TherAccording to the results obtained with the SHapley Additive exPlanations and the related discussion of these results with the cardiologists, we identified the most relevant features for the prediction of one-year mortality for TAVI.The selected features are presented in alphabetical order and in order of importance, according to the SHapley Additive exPlanations, in Other relevant features that have been discarded to maximize the results at the risk of a reduced generalization capability on another population are risk scores related to bleeding with antiplatelet and nonsteroidal anti-inflammatory drugs (NSAIDs), New York heart association functional classification (NYHA class), QTC interval, gender, glomerular filtration rate (GFR), recent coronary artery bypass grafting (CABG) interventions, previous myocardial infarction and further classes of medicines e.g., angiotensin-converting-enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), and proton pump inhibitors (PPIs).We emphasize here that several factors are influencing the feature selection and the classifier training. Particularly, the order of the most important features can be highly influenced by the missing values. In fact, a certain feature can ascend or descend the list of the most important features proportionally to the amount of its missing values. It must be said that missing values contain information as well because they are a natural consequence of the clinical workflow, of the internal protocols adopted by each hospital, and of the varying urgencies that characterize each patient journey. However, by including all the features shown in In Table 6, the performance of the mortality predictor achieved in this work is compared to the ones achieved in other studies available in the literature. As previously mentioned, EuroSCORE II and STS, which are extensively accepted as risk scores by the cardiologist worldwide, reached in a TAVI study AUCs of 0.81 and 0.77, respectively. However, only 59 symptomatic patients with severe aortic stenosis were selected for this 30-day mortality study . Two pro1 score of 0.45. All the evaluation metrics and classification predictions acquired during the validation of our prediction model are shown in We computed the ROC curve shown in The calibration curves for each classifier are shown in As shown in As shown in To clarify and discuss the findings of SHapley Additive exPlanations, clinical experts were consulted to better understand why certain features were considered important for the prediction and for an improved understanding of the possible interaction between all the different variables. With the goal of finding an answer to why certain features were considered more important than others in the decision making of the model, we infer the following conclusions.Severe AV regurgitation is linked to heart failure and mortality, which is found also in our analysis. Paravalvular regurgitation after TAVI is a common complication. Paravalvular regurgitation is most common in patients with severe calcification of the native aortic valve leaflets. When a TAVI valve is deployed, it may not be able to fully operate properly, resulting in leakage. The severity of the regurgitation is correlated to a worse prognosis since patients will develop heart failure and require in-hospital treatment.A low AV peak gradient can be related to less severe aortic stenosis or to a dysfunctional left ventricle. High values indicate severe/critical aortic stenosis, that if left untreated, can lead to mortality for sudden cardiac death or heart failure. In severe aortic valve stenosis, the valve is narrowed resulting in a higher resistance over the aortic valve. The left ventricle needs to develop a higher pressure to open the valve. Severe symptomatic aortic valve stenosis is a devastating disease if left untreated and has a high mortality rate.Atrioventricular block is linked to higher syncope and mortality and needs to be treated with a pacemaker giving complications, which reduces survival. Atrioventricular block is a common complication after TAVI. This complication is related to valve size and calcifications of the native aortic valve. The atrioventricular node is positioned in the septum of the ventricle and when a TAVI valve is deployed, the stent frame or calcifications of the native valve can impose pressure on the node causing damage, which in turn results in several degrees of atrioventricular block. If left untreated, this can cause syncope or even heart failure. Monitoring the first days after TAVI for the development of atrioventricular blocks is required, as the function may sometimes return. If not, a pacemaker is implanted to bypass the node.Beta-blocker class of medication is used to manage heart rhythms  and in the case of heart failure. Both cases have an impact on survival. Atrial fibrillation is often seen in patients with aortic valve stenosis. To treat this rhythm problem, beta-blockers are often the first choice for rate control.Extreme values of body mass index (BMI) are unhealthy factors, even though there is clinical relevance that being slightly overweight gives a better prognosis after surgery.High blood creatinine concentrations suggest that there is a kidney deficiency. Kidney failure is linked to higher mortality. A high blood creatinine concentration is an indication that the renal function is declined.Very low values for the RAND-36  general A low hematocrit and hemoglobin value may suggest anemia, which is linked to mortality. Patients with anemia may require a higher cardiac output to deliver oxygen to the organs. Patients with aortic stenosis can develop heart failure and are thus unable to increase their cardiac output sufficiently. This may result in the deterioration of patients’ hemodynamics and eventually could increase mortality.The month on which each patient faces its post-procedure recovery has been shown to be statistically related to survival. Our assumption has been verified on the survival distribution of another center showing a similar survival trend over certain months, as shown in Previous devices such as pacemakers are implanted when rhythm disturbances are present and may lead to long-term complications. Implantable cardioverter-defibrillator (ICD) or cardiac resynchronization therapy with defibrillator (CRT-D) are implanted when the left ventricular function is very low, or when the patient has deadly arrhythmia. Both factors lead to a lower life expectancy.A high QRS duration is an index of a more diseased conduction system. This can lead to heart failure. The conduction system can be damaged by TAVI valves. As the valve is deployed, the stent frame or the calcification of the aortic valve may cause temporary or permanent damage to the conduction system. This can lead to a further widening of the QRS on the electrocardiogram. In some studies, this is linked to a higher mortality.Smoking leads to a higher risk of any cardiovascular disease, again proof of the fact that smoking leads to a lower chance of survival after an operation.This twofold approach, technical and clinical, provides a more solid background for this research, enabling the identification of important features for the prediction incorporating clinical expertise and the capability of analyzing a large amount of clinical data exploiting extensive and computationally intensive feature analysis.Similar conclusions of the most important features that have been identified cannot be guaranteed on a larger population or on another clinical center, especially when considering datasets larger than one or two orders of magnitude in size. The validation approach used in this research was chosen because of the clear limitations resulting from a small dataset size. Furthermore, extending the validation on a larger dataset would assess the prediction potential of this model on a larger population, possibly using other validation techniques that take advantage of a threefold split for training, validation, and test set. As this research is a single-center study, we firmly believe that external validations would give added value to the research field. Cross validating the models which are available in the literature could provide validation metrics completely exempt from bias that might be present on each center dataset and could, therefore, lead the model to non-ideally fit or overfit the data. This can represent a risk to be considered when validations are performed on single-center studies, especially when small populations with imbalanced classes are involved.1 score as an evaluation metric for this model, which resulted in a value of 0.45 with CI . The model has achieved a positive predictive value (precision) ranging from 57% to 64%, suggesting that the patient selection with respect to the current clinical workflow can be improved. It is important to extend the validation of the model on other patient data, possibly by performing a validation on a larger dataset, as well as in an inter-center validation process. Summarizing, we evaluated the predictive potential of a model developed for exploiting ML techniques on a set of features found to be important for one-year survival. The model has shown promising predictive potential for the TAVI procedure, offering attractive and powerful insights and results for the prediction of one-year mortality. The methodology presented in this study can be easily scaled up incorporating larger datasets and can be translated to other use-cases. This preliminary study forms a solid basis for further technical investigation and clinical studies to further consider, validate, and extend our approach.With this research, we aim to develop a predictive model for patient selection in cardiac surgery, specifically for the TAVI use-case, by exploiting a new state-of-the-art machine learning classifier designed for categorical features. We have successfully identified the most important features to predict the one-year mortality and have developed a model based on the most relevant features. We validated our model on 270 patients, obtaining promising results also with respect to widespread prognostic risk scores or predictive models for TAVI. The model is able to discriminate the two populations of survived and non-survived patients with an AUC on the ROC of 0.83 with CI  and with a specificity and sensitivity of 0.97 with CI  and 0.37 with CI , respectively. Since our dataset was intrinsically imbalanced with a ratio of 1/8, we measured also the F


The interplay of interface and bulk dislocation nucleation and glide in determining the motion of twin boundaries, slip-twin interaction, and the mechanical  behavior of fcc metals is investigated in the current work with the help of molecular dynamics simulations. To this end, simulation cells containing twin boundaries are subject to loading in different directions relative to the twin boundary orientation. In particular, shear loading of the twin boundary results in significantly different behavior than in the other loading cases, and in particular to jerky stress flow. For example, twin boundary shear loading along  Among deformation mechanisms in (higher symmetry) metals, perhaps the most prevalent are dislocation-based or -related ones. Besides dislocation glide, these include for example dislocation-mediated twinning, and dislocation-mediated phase transformations. A prominent example of the former is twinning induced plasticity (TWIP), and of the latter, transformation induced plasticity (TRIP). TWIP steels are particularity interesting for industrial applications due to their high ductility and strength ,2. DisloIn a number of previous works, MD simulations have been employed to investigate interaction between dislocations and twin boundaries. For example, Sedlmayr et al.  studied i et al.  employedi et al.  examinedLiebig et al.  performeo et al.  employedo et al.  studied One purpose of the current work is to gain further insight into the underlying atomic and deformation mechanisms behind such jerky flow related to twin boundary motion. A second purpose is the investigation of the interaction between twin boundary motion and bulk dislocation slip on the resulting mechanical behavior of twinned fcc metals. As in most of the studies discussed above, MD simulations are employed for this purpose here. After discussion of the corresponding simulation set-ups and cases studied in In this work, the software LAMMPS  is emploial from . As showial from  and Boyeial from , this po−1 (via the “box deform” command in LAMMPS) for 100,000 time steps of size , and twinned, fcc simulation cells. x and y directions are parallel to z is parallel to the twin boundary normal In particular, comparison with the untwinned case is carried out for the twin configuration in z) is studied with the help of the simulation cell shown in The effect of variable twin boundary orientation relative to the loading direction  the same, resulting in a velocity difference below 5%.As well-known , dislocAll stress results to follow represent the virial stress of the simulation cell. Since the temperature is relatively low, the kinetic contribution to stress is negligible. Strain results to follow represent the linear cell strain In this section, stress-strain results are obtained and discussed for the simulation set-up and loading cases described in As shown in the left column, the stress-strain behavior is similar in the three normal loading cases x direction In the case of xz plane , left isThis is in contrast to This is in contrast to the case of At about Closer inspection of the serrated or jerky stress-strain behavior, in As evident, the twin boundary moves via the nucleation and glide of interface partial dislocation loops along the twin boundary. The different behaviour of twin boundary motion in A layer (i) above the twin boundary in the positive x, or (ii) below the twin boundary in the negative x, direction  is higher than the corresponding screw barrier by more than a factor of two. Since both are subject to the same loading  effects. On the other hand, this is not the case for the velocity results for interface partial edge dislocations.z direction  effects. On the other hand, this is not the case for the velocity results for interface partial edge dislocations. Indeed, given that both are subject to the same loading, one would expect the higher energy barrier to glide for twin boundary partial edges  to resulApparently, additional mechanisms or atomistic effects are involved here beyond short-range energy barrier and/or long-range (continuum) Peach-Köhler considerations. More accurate determination of the energy barriers based for example on nudged elastic band and/or DFT information may shed further light on this. In any case, this represent on-going work and research in progress to be reported on in the future.For the case of variable twin boundary orientation in relation to the loading direction, a strong dependence of dominant deformation mechanism is observed as the angle Besides clarification of the velocity behavior of twin boundary partial edge dislocations discussed above, future work includes extension of the current study to variable temperature, other fcc materials, and to finite systems including for example interaction with grain boundaries and other defects.


Tiling robots with fixed morphology face major challenges in terms of covering the cleaning area and generating the optimal trajectory during navigation. Developing a self-reconfigurable autonomous robot is a probable solution to these issues, as it adapts various forms and accesses narrow spaces during navigation. The total navigation energy includes the energy expenditure during locomotion and the shape-shifting of the platform. Thus, during motion planning, the optimal navigation sequence of a self-reconfigurable robot must include the components of the navigation energy and the area coverage. This paper addresses the framework to generate an optimal navigation path for reconfigurable cleaning robots made of tetriamonds. During formulation, the cleaning environment is filled with various tiling patterns of the tetriamond-based robot, and each tiling pattern is addressed by a waypoint. The objective is to minimize the amount of shape-shifting needed to fill the workspace. The energy cost function is formulated based on the travel distance between waypoints, which considers the platform locomotion inside the workspace. The objective function is optimized based on evolutionary algorithms such as the genetic algorithm (GA) and ant colony optimization (ACO) of the traveling salesman problem (TSP) and estimates the shortest path that connects all waypoints. The proposed path planning technique can be extended to other polyamond-based reconfigurable robots. Residential robots that help in everyday, dull, dirty, and routine cleaning tasks have recently gained attention. A recent survey from the international federation robotics states that, in 2020, floor cleaning robots are expected to be sold twice as much as the previous year . These rA typical tiling robot consists of various mechanical and electronic components that help to perform autonomous operations . In receCCPP algorithms have mostly been constructed for workspace modeling methods. These widely used approaches include the exact cellular-based decomposition method , Morse-bN, it is a challenging task to generate optimal solutions with TSP. Simple techniques such as spiral, greedy, and zigzag path patterns were implemented in a conventional cleaning robot with a formulated TSP [However, the proposed coverage algorithms in previous literature were developed and tested extensively on robots with a fixed morphological design facing coverage issues when accessing constrained and narrow spaces. The waver design was introduced by Prabhakaran et al., where a cleaning robot called hTetro would change its morphology based on the perceived environment ,22. Sincated TSP . At thatated TSP  and ACO ated TSP . These eated TSP . By contIn this paper, we present the design of a novel reconfigurable robot called hTetrakis with three diamond-based modules that are able to change the morphology to overcome the constraints of environmental settings. Moreover, due to the reconfigurability of this hTetrakis robot, the energy cost function during navigation takes the activities of reconfiguration and locomotion, including translation, transformation, and orientation correction, into account to yield more precise results. The main contribution of this paper is twofold. First, we define a CCPP framework for reconfigurable tiling robots. Second, we construct the TSP cost function based on the energy profile of each action of the hTetrakis robot to derive the sub-optimal trajectory in the working environment before the robot conducts the complete coverage navigation.The outline of this paper is presented as follows. The design principle of the hTetrakis platform is based on the polyiamond hinge dissection principle. The building block of this platform is an equilateral triangular block, called a moniamond. There are four moniamonds in the platform, out of which the inner moniamonds are connected to form a trapezoidal block. All moniamond blocks are connected by a planar revolute joint, shown in w is denoted by the robot location i is defined by i is the block number among three robot blocks The representation of the hTetrakis as the waypoint inside the predefined workspace is set at the robot center of mass (COM). a×b.The tiling theory addresses the tileset generation in the CCPP framework for the tetriamond-inspired, reconfigurable hTetrakis robot. By reordering the sides of the triangles along the various edges, we can obtain various configurations, shown in Theorem 1.Combinatorial Rules for Tetriamonds.Any a×b can be tiled with all the three forms, i.e., the A, I, and U sets of tetriamonds, if (and only if) both a and b are multiples of 8.Proof. A set of I, U, and A forms the smallest parallelogram of size 8 × 8 shown in The process of the CCPP framework in W from the path planner and begin a waypoint clearing loop. Within the loop, the robot will be continuously updating its current configuration at waypoints based on the sensor readings. The algorithm prioritizes robot reconfigurations to robot linear motion, which implies that, if a discrepancy between the current robot morphology at the source waypoint Once the navigation process initializes, the system will load the waypoint series Tilesets by the tiling theory provide only the shape of the robot within the workspace. With one specific robot shape, the locations of blocks t is symmetric, such as A, and I, the block location of the tile t − 1 with the smallest orientation offset to the tile t is picked. As a sequence, the orientation is reduced because the orientation correction energy during robot navigation is minimized. Equation DtraFinding the trajectory Equation  is the oworks of ,27 explaThe experiments were conducted in a simulation environment to compare the costweights’ generated path and a real testbed environment to verify the energy consumption of CCPP.Several workspace sizes in Matlab Simulink with and without obstacles were selected to evaluate the efficiency by the costweight of the generated path for tested methods: zigzag, spiral, greedy search, and the GA and ACO methods. The workspaces were divided into triangle shapes equal to the hTetrakis block. A workspace with a regular size, workspaces with an irregular size, and the workspaces with obstacles are The numerical comparisons in terms of the costweights and the execution time of the zigzag, spiral, random search with 1000 iterations, greedy search, and GA and ACO methods for the workspace in The costweights generated for the simulation workspaces in The proposed CCPP framework for the tetriamond, reconfigurable tiling robot has shown efficiency in generating the best navigation sequence among the tested methods in both simulation and real testbed environments. Modeling the energy as the travel distance is an effective method of estimating the energy. Optimizing the order of traveling sequences by the TSP is a feasible solution for the proposed robot platform to conduct complete workspace coverage. As such, this paper should be of interest to a broad readership, including those interested in sensor-based localization, energy preservation, complete coverage path planning, and reconfigurable tiling robotic systems. The issues of dynamic obstacles in working environments and modeling energy with consideration of friction is an interesting research topic for future work.


Visual tracking is a fundamental vision task that tries to figure out instances of several object classes from videos and images. It has attracted much attention for providing the basic semantic information for numerous applications. Over the past 10 years, visual tracking has made a great progress, but huge challenges still exist in many real-world applications. The facade of a target can be transformed significantly by pose changing, occlusion, and sudden movement, which possibly leads to a sudden target loss. This paper builds a hybrid tracker combining the deep feature method and correlation filter to solve this challenge, and verifies its powerful characteristics. Specifically, an effective visual tracking method is proposed to address the problem of low tracking accuracy due to the limitations of traditional artificial feature models, then rich hiearchical features of Convolutional Neural Networks are used to make the multi-layer features fusion improve the tracker learning accuracy. Finally, a large number of experiments are conducted on benchmark data sets OBT-100 and OBT-50, and show that our proposed algorithm is effective. With the development of artificial intelligence and computer vision system, visual tracking has become more and more important in the field of computer vision applications. It has been widely used in surveillance, driver assistance system, remote sensing, defense system, or human–computer interaction. Convolution Neural Network (known as CNN) based feature extraction have also been successfully used to the multi-target tracking problem ,2,3,4,5,Normally, positive training samples and negative training samples are collected near the estimated target position by some existing deep-learning-based trackers ,11,12,13Based on previous researches, we find that using the last layer of CNN can extract effective semantic information but not fine-grained spatial information, for example, the object location. On the other hand, the front-end layer of CNN is accurately positioned but not used to extract object semantics. Therefore, we use the rich feature levels of CNN as the target representation of visual tracking, and at the same time using semantic and fine-grained details to deal with the huge changes in appearance to avoid the drift and loss of targetsUsing the search strategy from rough to fine and the hierarchical characteristics of CNN research and the multi-level reasoning mechanism of classical computer vision to obtain the optimal tracking results, at the same time combining the correlation filter on each CNN layer to conduct adaptive learning while the multi-stage correlation filter is used to implement co-positioning, and make the target position be inferred from rough to fine .A plenty of experiments on large data sets which called OBT-100  are testWe can consider visual tracking ,11,16 f=F−l by searching the max position of the correlation response graph with size We can estimate the target location of layer In CNN, when the convolution reaches a higher level, the semantic information is relatively rich, so it is often used to represent the appearance characteristics and classification of the object. Therefore, its fusion weight needs to be set to a higher value, and the convolutional neural network at low levels make the target boundary obvious. The target can be accurately positioned, but it is sensitive to occlusion deformation and should be given a lower fusion weight. According to the above principle, the weighted sum of the response graph of each layer is used to obtain the final convolution feature response graph HOG feature is a traditional feature. Compared with convolution feature, the target representation of HOG in complex scenes is not rich enough. In order to make full use of traditional features and convolution feature, our algorithm makes adaptive weighted fusion of HOG traditional feature response graph f respectively.In order to calculate the discrimination ability of traditional features and convolution features in the tracking process, the algorithm uses the difference value of feature response graph Peak Side Lobe Ratio (PSLR) of adjacent image frames to calculate the weight of feature fusion . The smal can be updated by the minimum output error of all trace results. However, the method has to solve a set of As described in , the optEquation  to obtaiThe main steps and implementation details of the tracking algorithm are given in Algorithm 1. This algorithm uses VGG-Net-19  trained r of the constraint condition of neighborhood search. This is due to the use of the method of estimating the position of the target by summing up the multi-layer weighted response graph.Keep the parameters of each layer of training related filter unchanged. We set the regularization parameter to Equation  and makee window . 3-4, 4-Algorithm 1: Tracking algorithm with CNN and correlation filtersWe evaluated the proposed approach on a large benchmark data set OTB-100  and compWe used the following latest evaluation criteria of object tracking system to evaluate the proposed methods.The overlap rate between the target position The degree of object offset has a great relationship with the distance between the center points (ground-truth) before and after its movement (Bounding Box). If the actual distance is within the range of the set threshold, the experimental results are not bad. Different thresholds may result in different DP rates, so we can draw a curve of experimental data that contains obvious changes. The disadvantage of this method is that when the target is zoomed or the size changes, it is not very comprehensive to use the center point as the index.This indicator is complementary to the previous one. The average Euclidean distance has its own advantages on this issue.All of our average accuracy and success rate are based on the first frame, and the initialization of the first frame is achieved by ground-truth. There are two disadvantages to this approach. First of all, the tracking algorithm may be sensitive to the initial position given in frame 1, which will has a great impact on the accuracy of the initial position. Secondly, most algorithms do not have the mechanism to reinitialize after the tracking failure, which will seriously affect the tracking effect.In an image or video sequence, the tracking algorithm starts tracking from different frames as the starting frame , and the bounding box used for initialization is the ground-truth labeled on the corresponding frame. We took the average of these results to get the TRE result.The tracking algorithm may be affected due to the possible error of manually labeled ground-truth. Therefore, in order to reduce this loss, the bounding box was produced by slight displacement of ground-truth and scaling. The displacement is Deep learning tracker (DLT) ;Correlation filter trackers, including THCF , CSK 3030, STC  and KCF Representative tracking algorithms using single or multiple online classifiers, including MIL , Struck We compared and evaluated the proposed algorithm with 12 latest trackers. These trackers can be broadly divided into the following three categories:In sequence  and all sequence . As we csequence  in termssequence  tracker I, our proposed tracker had similar performance compared to the THCF [As we can see from the THCF  tracker.the THCF  tracker We further analyzed the tracking performance of the complex scene video  in the data set OTB-100 . Table 2The following results can be observed from In this experiment, we split the features, and two algorithms Ours_Deep and Ours_HOG were obtained. Among them, Ours_Deep used the convolution feature for target tracking, and Ours_HOG algorithm only used the HOG feature. In order to prove the effectiveness of multi-feature fusion target tracking proposed by the algorithm in this paper, Ours_Deep, Ours_HOG and other different features integrating tracking algorithms were selected in this experiment for comparative analysis on the OTB-100 test set. In order to prove the effectiveness of the proposed algorithm in the training of convolutional neural networks and the selection of convolutional layers, we split the convolutional layers on the OTB-100 dataset and tested their different performances respectively. We first tested each convolutional layer involved in the experiment, and then searched and measured the combination of layers 5 and 4. Obviously, we also connected all three layers, 3, 4 and 5 together, as hypercolumns that world be used in the experiment . HoweverThe KCF tracker learned the nucleated correlation filter with Gaussian kernel on the HOG feature. It performed well in partial deformation and fast motion sequences, but drifted when the target object was heavily obscured and rotated. DLT approach did not take full advantage of the semantic and fine-grained information and therefore could not track targets on the selected challenging sequence. Struck method was not effective in deformation sequence, background clutter, rotation, and severe occlusion, because Struck, although using structured output to effectively alleviate the sampling ambiguity problem, was not able to effectively deal with large appearance changes due to its manual characteristics.There are two main reasons for the good performance of our algorithm. First, the algorithm combined the HOG feature and the hierarchical convolution feature, which was more efficient than the traditional manual feature method. Our depth features came from multiple layers of CNN, including the semantics and fine-grained details at the category level, which handled the appearance deformations caused by deformation, rotation, and background clutter. The experimental results show that for the basketball sequence in complex scenes, the 12 latest methods could not track the target well, while our method could achieve a distance precision of 91.8%. Second, the strategic update of memory filter could also deal with the appearance change of tracking target so as to achieve the purpose of automatic recovery of tracking failure.Since the hand-designed feature extraction has a great influence on the performance of target tracking, this paper studies how to effectively combine the neural network layered features and HOG features to improve the performance of the object tracking algorithm. In a typical deep neural network, the front-end network layer has more image texture information and has higher resolution, which can accurately locate the target; while the back-end network layer retains more image semantic information, suitable for the target for large-scale positioning. This algorithm proposes the use of deep convolutional neural network hierarchical features and related filtering algorithms, using high-level abstract information to roughly locate the target in the first place, and then using shallow texture details for fine positioning, and finally weighting fusion with HOG features to obtain the target location. This paper proposes that this adaptive weighted feature fusion tracking algorithm combines the advantages of deep learning layered features, HOG features, and related filters, which has achieved good results on a large-scale object tracking test set. The speed is also ahead of the current other tracking algorithms based on deep learning.


This study reports the technical results of a field trial of the system in Mbarara, Uganda. During this trial, oxygen supplied from the LPOS system was distributed to four beds in the paediatric ward of Mbarara Regional Referral Hospital. Over a three-month period, medical-grade oxygen was made available to patients 100% of the time. This period was sufficient to quantify the ability of the LPOS system to deal with blackouts, maintenance, and an unscheduled repair to the LPOS store.Increased access to reliable medical oxygen would reduce the global burden of pneumonia. Oxygen concentrators have been shown to be an effective solution, however they have significant drawbacks when used in low-resource environments where pneumonia burden is the heaviest. Low quality grid power can damage oxygen concentrators and blackouts can prevent at-risk patients from receiving continual oxygen therapy. Gaps in prescribed oxygen flow can result in acquired brain injuries, extended hypoxemia and death. The FREO Oxygen is essential in the treatment of hypoxaemic illness in paediatric patients, reducing mortality and sequelae , 2. HoweThe LPOS system comprises a power conditioner, oxygen storage utilising low-pressure reservoirs, pneumatic switch, and low-cost oxygen distribution to individual patients. In combination with a standard concentrator and a backup cylinder, these devices are intended to improve reliability of oxygen supply whilst reducing the cost of oxygen for the health facility. By buffering short power outages using the local low-pressure storage and switching to more expensive high-pressure storage (cylinders) during extended outages, the LPOS system augments existing concentrator technology to provide reliable oxygen access to patients. This article presents key findings from the first trial of the LPOS system in clinical use in the paediatric ward of a health facility in Africa.Mbarara Regional Referral Hospital is the major public referral hospital for Western Region, Uganda. The paediatric ward has 70 inpatient beds [Due to the technical nature of the work, patients or the public were not involved in the design, conduct, reporting, or dissemination plans of this research. As the system moved towards large scale production, we are including the public (ward staff and maintenance personnel) in the continuing user-centric design process.As shown in Elite and DeVilbiss 525KS [2 developed a power conditioning system, PROTECT.The electrical requirements of oxygen concentrators recommended for low-resource settings, such as the AirSep ss 525KS , is consss 525KS . Howeverss 525KS . ConsequDuring the research and development phase of PROTECT, a wide range of commercially available off-the-shelf voltage stabilisers were assessed for compatibility with AirSep Elite concentrators. Findings revealed that the large current required by the air compressors during start-up caused the off-the-shelf voltage stabilisers to fail. PROTECT has been designed to address this gap by conditioning the power to meet the specific requirements of oxygen concentrators. Functions include voltage stabilisation for inputs between 180 VAC to 260 VAC, automatic shut-down outside that range, and controlled restarts to avoid strain on the compressor created by rapid power cycling.The concentrator used was an off-the-shelf AirSep® NewLife® Intensity designed to produce up to 10 litres per minute of 87% - 95.5% oxygen on 230 VAC electricity.The LPOS Store has been previously described in detail . Fig 2 sDuring operation, the oxygen concentrator is set to maximum output and oxygen that exceeds patient demand automatically flows to LPOS. As oxygen enters the gas section of the lower reservoir, it forces the water in the fluid section into the upper reservoir. As the water and oxygen are contained in separate airtight bags, the water does not contact the oxygen or evaporate. In the event of a power failure, the weight of the water previously displaced into the upper reservoir provides the force to drive the stored oxygen to the patient, without the need of a pump or battery. This approach is concentrator agnostic and does not require any modification of the concentrator.The LPOS store installed for this trial holds approximately 240 L of oxygen which can provide for four hours of oxygen for a child prescribed 1 LPM of oxygen. The store scales well, with a 1000L prototype currently being investigated.Prioritizer is a pneumatic switch that automatically routes the lowest cost oxygen to patients. If the power is on, oxygen flows from the concentrator. If the power is off, oxygen flows from LPOS. If the power is off and LPOS is empty, then flow from the back-up cylinder is automatically activated. No user intervention is required to change between oxygen sources.Standard oxygen cylinders were used to maintain oxygen flow to patients during extended power outages. The hospital engineering staff regularly checked the cylinder pressure to minimise the risk of running out of cylinder oxygen.The status of the system is displayed to nursing staff via a traffic light-style lamp. It has three states: Green indicates that the concentrator is on, Orange indicates that the LPOS is in use and Red signifies that the backup cylinder has been enabled.Distributing the oxygen to patients is relatively straightforward but can be prohibitively expensive. For example, a study in the Gambia indicated a cost of USD$11, 000 for a 20-bed 6-cylinder bank system . Further2 LPOS system can provide reliable oxygen without occupying valuable ward space. This approach also enables health care workers to focus on the needs of the patient instead of specific concentrators or cylinders.As described in 2C serial bus. The sensors were polled at 1.25 Hz by a specialized data acquisition system. The data were routinely logged to solid state drives and uploaded to a remote server to enable real-time remote monitoring. A backup oxygen cylinder was connected to the Prioritizer subsystem, and formal tests made of the performance of the system under simulated power failure conditions at different oxygen flow rates.In preparation for the clinical trial, a two month on-site technical phase was undertaken. During this technical phase, the pressure in the oxygen reservoir was monitored using an NPX USA MPX4250 pressure sensor, and the oxygen flow rates from the concentrator, into and out of the LPOS store, and to the simulated patient were monitored using Sensirion SFM3000 flow meters. Oxygen concentration was monitored with a Longfian Scitech JAY-120 oxygen analyzer. Each of these sensors was calibrated against laboratory standards and linked via an IPrior to supplying oxygen to patients, the technical phase data was analysed to confirm that the system was performing according to specification. Volumetric Flow Meters (VFMs) were installed to four designated beds and oxygen made available to the ward staff for use. No changes were made in the process of diagnosis of pneumonia or hypoxaemia, the criteria for the use of oxygen, nor any other aspect of treatment. The flow to each child could be individually adjusted between zero and two litres per minute to meet the needs of the patient.2 Foundation Australia.Ethics approval was granted  by the Human Research Ethics Committee of Mbarara University of Science and Technology and the Uganda National Council of Science and Technology (HS 2361). The nature of the trial was explained to the parents of all prospective patients and written informed consent was obtained prior to treatment. Although no caregivers refused LPOS oxygen, if consent was not given the child was admitted to a different bed and received standard care using a combination of piped cylinder oxygen and standard oxygen concentrators. All components of the system were the same as already routinely in use in the ward, or formally approved as medical or food grade by the United States Food and Drug Administration (FDA). The trial was funded by FREOThe clinical field trial was undertaken for a period of 3 months starting from 17/07/2018 through to 17/10/2018 inclusive. Data acquired during this trial period is publicly available at . During Of the remaining 109 events, the LPOS Store provided all required oxygen for 90 outages greater than 1.5 minutes. As shown in In the table the sum of the proportions of time during which flow came from each component is not equal to the total proportion of time that patients received oxygen. This is due to brief periods in the change-over from one to another during which two sources were supplying oxygen simultaneously.During the clinical trial, 56 children were treated with oxygen from the LPOS system. This represents an average of 8,293 litres per child, and an average of approximately 39.5 hours of oxygen treatment per child.Four deaths were recorded among the children receiving LPOS oxygen: one was assessed by the attending doctors as due to complications of severe pneumonia, one as tuberculosis plus malnutrition, one as septicaemia and gastroenteritis, and one as pyloric stenosis with hyponatraemia and severe hypokalaemia. Detailed analysis of the data confirmed that there were no power interruptions of more than two hours, and no break in oxygen availability during any of these children’s admissions. They all received primarily concentrator oxygen via the LPOS system, with supplemental oxygen via the LPOS Store. Only one received backup cylinder oxygen, in three separate periods, with a total of two and a half hours over a 20 day admission.The LPOS system provided an uninterrupted supply of up to 8 litres per minute (LPM) of oxygen to four paediatric beds during the three-month trial of continuous monitoring. During that time there were many interruptions to concentrator function, mostly due to unscheduled cuts in grid electricity. Although the majority were less than 15 minutes, some lasted more than six hours.The hospital engineering department provided routine maintenance for the concentrator and rectified minor mechanical failures occurring during the trial. As anticipated, most of the oxygen was provided by the standard AC-powered oxygen concentrator, with about 3.3% automatically provided from the LPOS Store and 2.8% from the backup cylinder. No intervention was required by the ward clinical staff at any point. No other system offering 100% reliable oxygen without clinical staff intervention is available to the hospital.The cost of this prototype LPOS system was USD$2,300—including the cost of concentrator, LPOS store, low-pressure piping to the ward, volumetric flow meters and installation. Based on the local price of electricity of USD 30 c/kW.h, and assuming an average concentrator power consumption of 590 W the cost of electricity required during the trial was USD$369. During the trial, two cylinders of oxygen at a cost of USD$20, excluding transport, were required to cover periods when the LPOS store was empty. The cost of regularly cleaning filters and simple maintenance of the system is estimated to be USD$120 per year. Therefore, the overall running cost is estimated to be USD$439 per quarter to supply up to 8 LPM of reliable oxygen spread across four paediatric beds. If the costs measured during the trial are approximately constant during the year this would lead to an annual cost of USD$1756.As tabled above, the LPOS system delivered 464,391 litres of oxygen to the patients, offsetting the purchase of 75 cylinders at a cost of USD$1500, excluding transport, per quarter. Therefore, over the trial period the LPOS system delivered a net savings of USD$1061, which demonstrates a potential payback period of less than 1 year. Cost-savings will be significantly larger for remote clinics, where the transport cost of cylinders can exceed the cost of the oxygen itself .Storing the oxygen at low pressure requires a larger amount space than storing it at high pressure in a cylinder. The installation site at Mbarara was a disused alcove external to the paediatric ward which we modified with a locking gate. As the system has been designed to be not require attention from nursing staff, it does not need to be located within the ward and can be installed in unused storage areas, external alcoves or even in purpose-built sheds. Find space is an issue for low-pressure oxygen storage but we found that available space is common in the environment in which LPOS is designed to operate.2 is also in the prototype stage of testing a novel solar powered oxygen concentrator. A combination of mains powered, and solar powered systems will be necessary to increase access to medical oxygen to all low-resource environments. An LPOS store attached to a solar-powered oxygen concentrator can also increase the efficiency of the solar concentrator by turning off the concentrator once the oxygen storage is full, effectively duty cycling the concentrator. This combination of technologies could reduce the overall cost of a solar powered oxygen concentrator system.LPOS is designed to operate in a “grey-power” environment where mains power is available but not reliable. In areas where mains power is not available or is of such poor quality that it prevents the concentrator from filling the oxygen store, solar-powered concentrators are another solution. There are currently trials underway in Uganda investigating the effectiveness of solar powered concentrators  and FREOIn order for an innovation such as LPOS to be effectively taken up in low-resource environments, a clear economic advantage must be demonstrated. A full economic analysis was outside the scope of this trial but remains a high priority for future work. We have continued to measure important economic parameters such as electricity and maintenance costs in preparation for a deeper analysis.The LPOS system has now continuously operated for one year and demonstrates robustness and reliability in day-to-day clinical use in the paediatric ward of a busy African hospital. It is now in routine use in the same ward and is ready for trials in a wider range of health facilities, including district hospitals and sub-district health centres.This study has shown that the addition of the LPOS system allows for long term uninterrupted oxygen delivery from a concentrator, even through extended power outages. The system supplied up to 8 LPM of oxygen to four beds in the Mbarara paediatric ward over the clinical trial period with 100% oxygen availability. Relative to oxygen provision solely from cylinders, a net saving of USD$1061 and a payback period of less than 1 year was demonstrated. By adding innovations which condition poor power supply and store excess oxygen at low pressures, the LPOS system increases the effectiveness of a common off-the-shelf oxygen concentrator, increasing access to life-saving oxygen therapy.


Coronaviruses cause respiratory and gastrointestinal diseases in various vertebrates, including minor respiratory diseases in humans. Because of that fact, focused research on these viruses was limited to a few dedicated, but talented, research groups. However, that changed in 2003, when a new coronavirus emerged, designated as severe acute respiratory syndrome corona-like virus (SARS-CoV), which caused a life-threatening respiratory disease characterized as an acute respiratory distress syndrome with a fatality rate of almost 10%. Suddenly, the world’s researchers devoted countless hours to attempting to identify, characterize and develop treatments for this new virus. Knowledge of coronavirus virology multiplied exponentially and, more importantly, quickly. Within 1 year of discovery, the genome of the virus had been sequenced and a great deal was known about its replication cycle. Unfortunately, discovery of efficacious treatments has not developed as quickly. In addition, and probably as a result of the emphasis on SARS-CoV research, new coronaviruses causing less severe, yet significant, disease in humans have also been discovered.Coronaviridae, often using information gained from studying group 2 coronaviruses. The second part of the book consists of chapters that review the pathogenesis of coronavirus diseases, such as those caused by SARS-CoV, feline infectious peritonitis virus (FIPV), mouse hepatitis virus (MHV) and human NL63 coronavirus (HCoV-HL-63). Also included are chapters on immune responses to coronaviruses, vaccine development and the current status of anti-coronavirus therapies.Some 4 years after the outbreak of SARS, this book edited by Volker Thiel tries to summarize the most recent advances in coronavirus molecular biology, vaccine development and coronavirus therapeutics, with great emphasis on SARS-CoV. The authors of most of the chapters are some of the most respected experts in the field of coronavirus research. The book consists of 16 chapters divided into two parts. The first section contains chapters that discuss the evolution and molecular biology of the The book represents a valiant effort to summarize the recent advances in coronavirus research – an extremely fast moving area of study – by some of the world’s leading experts in coronavirus virology. The knowledge contained in the book demonstrates how quickly and relatively efficiently the worldwide research community can meld together into a giant collaborative effort and concentrate its resources to rapidly begin to understand and solve problems, in this case a health problem.This chapter, authored by David Wentworth and Kathryn Holmes, is a review of the initial stages of coronavirus infection, binding and entry. The authors present several models of binding and attachment to cells by coronaviruses. Much of the information presented comes from studies of SARS-CoV. This chapter is an excellent generalized review of the coronavirus proteins necessary for attachment and the receptors to which coronaviruses attach.Coronaviridae. Also included are studies of other members of the Nodovirales that support the various proposed mechanisms of coronavirus RNA replication.John Ziebuhr and Eric Snijder are the authors of this chapter. This chapter is a review of the information known regarding expression of the replicase gene complex of coronaviruses and how the proteins of this complex function. Included in the review are discussions of the functions of RdRp polymerase, exo- and endoribonucleases, and the proteases associated with the replication complex. The authors do an excellent job in presenting what is known about coronavirus RNA replication, relying heavily on data gathered from experimentation with MHV, one of the most intensely studies viruses of the cis-acting elements associated with coronavirus RNAs. The author makes a good effort to summarize the potential mechanisms whereby cis-acting RNA elements act to promote coronavirus gene replication. He makes excellent use of data, mostly from the study of MHV replication, to support some of the proposed mechanisms of action for these cis-acting elements.This chapter by Paul Masters reviews studies of the 3´ and 5´ and internal genomic Nodovirales evolution based on transcription strategies. Although this chapter very thoroughly reviews the topic of transcription, there are a few noticeable typos and one or two awkwardly written sentences.Luis Enjuanes, Isabel Sola, Sonia Zuñiga and José L Morena author this chapter on the mechanism of RNA transcription in coronaviruses. The authors present the most widely accepted model of coronavirus transcription, summarized by them diagrammatically as a ‘three-step working model’. The authors also present three alternative models, one of which relies on information gathered from studying arteriviruses. The authors discuss in copious detail the many cellular and viral factors involved in coronavirus transcription and end the chapter with a brief discussion on Volker Thiel covers a very important topic on the development of reverse genetics SARS-CoV, which has fostered astoundingly rapid advances in the understanding of SARS-CoV replication. The author selects seven applications for which reverse genetics has been used to study recombinant viruses and various gene products, with emphasis on SARS-CoV. He also discusses the development of coronavirus-based vectored RNAs and the generation of coronavirus vaccines using virus-like particles. A very well-explained figure portraying an HCoV-229E-based replicon accompanies this chapter.trans-acting factors involved in coronavirus packaging, primarily using data from MHV experimentation. This chapter also includes a brief, yet informative, summary of the various packaging signals that are discussed.The authors, Krishna Narayanan and Shinj Makino, review the current understanding of the initial stages in coronavirus particle assembly. The authors describe the various virion MHV packaging signal systems about which most is known, as well as those packaging systems associated with infectious bronchitis virus (IBV), transmissible gastroenteritis virus (TGEV) and SARS-CoV. The last section discusses This chapter contains a very good summary of the data discussed by the authors, Leen Vijgen, Els Keyaerts and Marc Van Ranst. In this chapter, the authors review data demonstrating the molecular evolution of the MHV group 2 coronaviruses  and the bovine coronavirus (BCoV)-related strains, BCoV, human coronavirus OC43 (HCoV-OC43), porcine hemagglutinating myelo-encephalitis virus (PHEV), canine respiratory coronavirus (CRCoV) and equine coronavirus (ECoV). The authors provide the reader with a standard phylogenetic tree with a rather lengthy figure legend, perhaps too long. The information provided in the chapter is an informative review of the mechanisms that drive virus evolution in general, along with an explanation of the evolutionary history of the group 2 viruses.In ovo vaccination is also discussed as a future method of immunizing poultry.Paul Britton and Dave Cavanagh discuss developments and future strategies in the development of IBV vaccines. IBV is extremely important because it causes major losses in the poultry industry. The authors first outline the natural course of coronavirus disease in poultry and then discuss the devastating potential for these viruses to infect other domestic and wild avian species. The authors also provide reasons for the lack of efficacy of current vaccines: multitudinous serotype variation without cross-protection and no induction of long-term immunity. The authors report that small differences (<5%) in amino acid sequences in the major immunologically recognized epitopes can lead to lack of cross-protection between serotypes. The authors also review the nature of the protective immune response that a vaccine should elicit and compare the efficacy of attenuated and killed vaccines in eliciting such responses. They review the process of virus attenuation and report on two, yet to be licensed, experimental vaccine approaches for coronaviruses: subviral vaccines and adenovirus-vectored vaccines. The authors of this chapter are Bert Jan Haijema, Peter Rottier and Raoul de Groot. These authors discuss the pathogenesis and natural infection history of feline coronavirus (FCoV) infections in domestic cats, including enterovirus infections caused by enteric FCoV (eFCoV) and infectious peritonitis caused by FIPV and sometimes by eFCoV. Also included in the chapter are sections on the molecular biology of these viruses, and the potential for vaccine development. The authors compare and contrast the relatively benign eFCoV with the highly pathogenic form of FIPV. The remainder of the chapter describes in great detail the molecular biology of the highly pathogenic FIPV WSU strains.In this chapter, written by Cornelia Bergman and Stephen Stohlman, the authors review the mechanisms involved in the establishment of two types of brain infections caused by neurotropic MHV. They also discuss immune system factors that contribute to acute and persistent infections caused by MHV. The authors then explain the mechanism of sustained antibody secretion within the CNS that is necessary for prevention of virus recrudescence from persistently infected cells: the maintenance of virus-specific antibody in the CNS.John Nichols and Malik Peiras describe the pathogenesis of SARS-CoV infections in humans and suggest that the pathogenesis is mainly due to damage to type I pneumocytes resulting in diffuse alveolar damage and loss of function, leading to respiratory distress. They also describe the clinical picture and outcome of the disease known as SARS and discuss the possible deleterious effects of the hyperimmune response to the virus, which is covered in slightly greater detail in the next chapter. They present a very good review of what is known about the pathogenesis of SARS infections as of early 2007.Perhaps a more appropriate title for this chapter would be ‘Interferon Responses to SARS Infection’, because the authors, Martin Spiegel and Friedermann Weber, spend most of the chapter reviewing interferon (IFN) responses as a consequence of SARS-CoV infection. They begin with a general, detailed review of the classical IFN-induction pathways. They then discuss how SARS-CoV initiates infection despite the activation of IFN-induction pathways, using some of their data to show that SARS-CoV counteracts IRF-3 by sending it back to the cytoplasm from the nucleus, where it acts to inactivate the IFN-β promoter. The authors also discuss the role of IL-8 in reducing IFN responses, which is produced in significant amounts during a SARS infection. The authors also speculate on how SARS-CoV infection induces the so-called ‘cytokine storm’ associated with SARS infections. It would have been appropriate if the authors had included in their review a discussion of the deregulation of the cytokine response in the lungs, where much of the SARS infection occurs and its relationship to the systemic cytokine response as detected in serum.Barry Rockx and Ralph Baric begin this chapter by introducing the reader to the human coronaviruses that cause disease. They then describe the genetics of SARS-CoV and the functions of some of the gene products. They also provide an interesting discussion of the evolution of SARS-CoV, the pathogenesis of the infection caused by SARS-CoV, the immune response to the virus and the components of the immune system that are protective against the infection caused by SARS-CoV. To enable the reader to quickly review all of the vaccines and vaccine trials published to date, the authors insert a comprehensive table of SARS-CoV vaccines tested as of early 2007 and the results of any challenge studies done with the vaccines listed. They also discuss the future development of live-attenuated vaccines and replicon particle vaccines. They summarize the challenges of developing a successful, protective coronavirus vaccine, especially for SARS-CoV. They suggest that such a vaccine must elicit broad-spectrum cross-reactivity to all the potential quasi-species that will probably arise and that coronavirus vaccines must not trigger an immune enhancement of the challenge virus. This section is well written and very thorough.Coronaviridae. He also devotes several pages to the clinical and molecular diagnostic tests available for detection of SARS-CoV. There are also sections in which the novel group 3 coronaviruses of birds and dogs and newly recognized human pathogens, HCoV-NL63 and HCoV-HuK1, are briefly discussed. HCoV-NL63 and the infection that it causes are described in more detail in the next chapter.In this chapter, Leo Poon discusses the emergence of human coronaviruses, with special emphasis on the emergence of SARS-CoV and its origins. The author briefly reviews the epidemiological history of the SARS epidemics and discusses the basis of the classification of SARS-CoV within the This chapter, authored by Krzysztof Pyrc and Lia van der Hoek, reviews what is known about the novel group I coronavirus HCoV-NL63 (NL63). The authors review the discovery and identification of HCoV-NL63, the molecular biology of the virus, including genomic organization, the transcription and translation strategies leading to virus replication, post-translational modifications of virus proteins and the known functions of the virus proteins. There is also an entire section on virus attachment and entry into the host cell. The epidemiology of HCoV-NL63 is reviewed, and the authors discuss the concept of HCoV-NL63 as a coinfecting agent in many respiratory diseases. They postulate the significance of coinfection with HCoV-NL63, especially in relation to the finding that coinfection with HCoV-NL63 often results in more hospitalization of patients than do respiratory infections caused by a single agent. A paragraph is devoted to the putative association of HCoV-NL63 with Kawasaki disease or lack thereof. In the final section, the authors describe potential antiviral targets in the viral replication cycle and review the few chemotherapy studies that have been carried out on treatment of HCoV-NL63 infections.in vitro. This leads to the discussion of some of the pitfalls of this chapter. In many cases compounds found in the table have been demonstrated to have in vitro efficacy by some laboratories and not to have in vitro efficacy in other laboratories. The authors should have discussed the problem of laboratory-to-laboratory variability in determining efficacy of compounds against SARS-CoV. The authors, when reporting on compound efficacy against SARS-CoV, many times forget to report on the selectivity of the compound. Even though some of the compounds described are potent inhibitors of SARS-CoV, they are toxic enough not to be selective inhibitors. Selectivity should have been emphasized in a more critical review of the compounds listed in their table, because compounds with selectivity indices of less than 20 often do not show activity in animal models. A number of the compounds mentioned in the table fall into this category. The reader is also not told whether or not the activity is virucidal; however, that is often the fault of the group publishing the data. Virucides are much less likely to be efficacious in treating lung infections owing to the toxicity often associated with them, lack of oral bioavailability, and the lack of efficacy against cell-to-cell transmission of virus. The authors fail to mention the few studies that have been published on the activity of several of these compounds in a mouse lung replication model. A number of the active and inactive compounds mentioned in the table do not prevent virus replication in the lungs of mice. For example, ribavirin has been found not only to have poor selectivity in vitro, but actually to prolong and enhance viral replication in a mouse lung replication model; a finding that has since been verified in a newly established mouse adapted SARS-CoV lethal murine model. Overall, the authors should be more critical in their review of the antiviral agents that have purported activity against SARS-CoV in vitro.The authors, Els Keyaerts, Leen Vijgen and Marc Van Ranst, briefly review the potential antiviral targets on the SARS virion and in the virus replication cycle. They provide the reader with a simple yet effective cartoon of the virus replication cycle to illustrate sections of the virus replication cycle that could be targeted by antiviral chemotherapies. Also included in this chapter is a comprehensive list of compounds and other materials that have been reported to show efficacy against SARS-CoV ‘Coronaviruses: Molecular and Cellular Biology’ presents a comprehensive review of the field of coronavirus virology. The contributors to the book are many of the experts in coronavirus virology. The contents of the book are particularly useful for those wishing to conduct research on coronaviruses because most of the authors include in their summary or conclusion paragraphs a number of key questions or problems for which research needs to be carried out to further the understanding of coronaviruses and how to treat the infections they cause. Most of the figures are very useful in helping the reader understand the narratives provided by the authors. The few tables provided are excellent in summarizing information that could be useful to readers wanting to know, for example, what antiviral agents have been found active against SARS-CoV in vitro or what vaccines have been tested against SARS-CoV.The book entitled There are some deficiencies to be found in the book, as there are in any comprehensive review. One minor problem, of course, is that the information is dated, but this book is more current than most review books. Perhaps the most problematic part of the book is the last chapter. The authors of the last chapter should be more critical on reporting of the compounds with published activity against SARS-CoV. Many of the compounds have been found active only in one laboratory but not in another and many have very poor selectivity, but this is not emphasized. Another small problem that the editor could have resolved is the standardization of the acronym for severe acute respiratory syndrome corona-like virus. Several acronyms for this virus were used throughout the text. Most experts in the field, including taxonomists, prefer the term SARS-CoV. A book such as this could establish that this acronym be used.When reading the book, the reader should be aware that contents are current as of early 2007 and that since then some further advances have been made in the molecular biology of SARS-CoV. However, this text is recommended for those who want to quickly be brought up to date on coronavirus research or who want to know what research questions remain to be answered in the field of coronavirus virology.


Most recycling methods remove the essential sizing from reinforcing fibres, and many studies indicate the importance of applying sizing on recycled fibres, a process we will denote here as resizing. Recycled fibres are not continuous, which dissociates their sizing and composite lay-up processes from virgin fibres. In this study, commercial polypropylene and polyurethane-based sizing formulations with an aminosilane coupling agent were used to resize recycled glass and carbon fibres. The impact of sizing concentration and batch process variables on the tensile properties of fibre-reinforced polypropylene and polyamide composites were investigated. Resized fibres were characterized with thermal analysis, infrared spectroscopy and electron microscopy, and the tensile properties of the composites were analysed to confirm the achievable level of performance. For glass fibres, an optimal mass fraction of sizing on the fibres was found, as an excess amount of film former has a plasticising effect. For recycled carbon fibres, the sizing had little effect on the mechanical properties but led to significant improvement of handling and post-processing properties. A comparison between experimental results and theoretical prediction using the Halpin-Tsai model showed up to 81% reinforcing efficiency for glass fibres and up to 74% for carbon fibres. The manufacturing and use of glass and carbon fibre-reinforced composite materials based on thermoset polymers have increased during the last decades in all engineering applications. Naturally, the amount of end-of-life (EoL) composites has been increasing as well. A common approach to deal with EoL fibre-reinforced composites has been landfilling, although it is the least preferred option for waste management, as stated in the European Waste Framework Directive . TherefoMuch work remains to make the recycling of composites viable in industrial scale. Several methods, such as thermal ,3, steamMost of the recycling processes remove the sizing layer from the fibre surface . Sizing The application of sizing on recycled fibres, denoted here as “resizing”, could help to bridge the gap between virgin and recycled fibres by mitigating the issue of uneven fibre properties and by guaranteeing a proper fibre-matrix adhesion. This is also acknowledged in the current literature ,19, althThermally recycled glass fibres (rGF) from EoL wind turbine blades and carbon fibres (rCF) from EoL aerospace components were used. The fibres were recycled by TECNALIA  with conventional pyrolysis process. The exact origin  of the recycled fibres was not known. Single fibre tensile test with the Fibrobotics device  Fibrobo. It is h® PP2-01, Michelman Inc., Cincinnati, OH, USA) was used with the PP matrix as the film former. It improves the interfacial properties by bonding with the fibre surface and/or the coupling agent (in the case of rGF) and mixing well with the PP matrix. The film former is designed for both chopped strands and continuous fibres to provide enhanced impact resistance, slip and lubricity. According to the supplier, the concentration of the non-volatile part of the solution is 38.5–41.0%. A non-ionic polyurethane dispersion  was used as film former with the PA6 matrix. The dispersion is designed for chopped strands, and it provides good impact resistance, thermal stability and adhesion with the matrix. According to the supplier, the concentration of the non-volatile part in the solution is 58–60%. Both film formers are informed to be compatible with glass and carbon fibres. For the sizing of rGF, 3-aminopropyltriethoxysilane  was chosen as the coupling agent for both matrices. Acetic acid  was used to hydrolyse the coupling agent functional groups and to control the pH of the sizing solutions. The chemicals were mixed with deionised water in the sizing solutions. In general, the selection of a film former and a coupling agent depends on the type of matrix to be used. In this study, the resized glass and carbon fibres were compounded with heterophasic polypropylene copolymer  and polyamide 6 . Due to the confidential rules of the related project, more detailed information about the matrices could not be provided, but the analysis was based on a comparison between neat resin and composites. A non-ionic malleated polypropylene dispersion . A screw rotation rate of 80 mintype 1BA ) with a The target fibre fraction in the compounds was 20 w-%. This was verified by determining the fibre weight fraction of the tensile test specimens with the burning-off method . For thThe morphology of the fibres and fracture surfaces of the tensile test specimens were analysed by scanning electron microscopy . The samples were coated with a thin carbon coating to enhance their conductivity.Thermogravimetric analysis  measurements were performed for resized fibres to evaluate the amount of sizing on the fibres. Temperature range was from 30 to 700 °C and the heating rate 10 K/min in a nitrogen atmosphere.−1. For coupled TGA-FTIR measurements, the ATR sample holder was replaced with an internal TGA-FTIR coupling accessory , and the same TGA device was used as above. The measured wavenumber range was 600–4500 cm−1.The functional groups on the fibres were identified using Fourier-transform infrared spectroscopy (FTIR) with Bruker Tensor 27 spectrometer  using a PIKE Technologies  GladiATR Attenuated Total Reflectance (ATR) sample holder. The ATR material was a diamond crystal. The wavenumber range of analysis was 600–4000 cmThe tensile properties of the composite specimens were tested with Instron 5067 universal testing device  with a 30 kN load cell. The tension tests were carried out at a strain rate of 10 mm/min; ten specimens were tested for each sample.Matrix residues on the fibre surface after recycling can significantly hinder the functionality of the new sizing, decreasing adhesion between the matrix and the fibres. SEM analysis prior to the sizing a revealeGlass is assumed to be stable at the temperature range of the thermal analysis (TGA) and the observed mass changes originate from the degradation of organic materials of the sizing on the fibre . ThermalThe TGA curves of resized fibres represented two mass loss steps for the PP-based sizing and three steps for the PU-based sizing . The firFurther understanding of the nature of the mass loss steps was achieved by a coupled TGA/FTIR measurement from the film former solution. A 3D plot of the results is presented in As expected, rinsed rGF samples showed significantly lower mass losses compared to samples without rinsing , but the−1 is the main noticeable detail of the spectra. This predominant area is associated to the different vibrational modes of Si–O and Al–O bonds and combination vibrations in the glass structure [−1 is related to the stretching vibrations of BO3 groups that are present in the E-glass structure [−1 region were stronger compared to the fibres before sizing. Although it is not possible to differentiate between Si bonds coming from rGF or coupling agent, this increase can be attributed to the presence of sizing in the fibre surface, because the bulk fibre remains unchanged during the resizing process. Another difference between the fibres with PP sizing and without sizing are the areas of 2800–3000 and 1300–1500 cm−1. The first one is assigned to the stretching vibration of C–H bond in CH2 and CH3. The sharp shoulder in the 5 w-% sample at 1374 cm−1 corresponds well to the CH3 “umbrella” vibration. Although the peak intensities are weak, these absorption bands can be attributed to the presence of film former, due to its PP backbone [−1 can be assigned to the bending vibrational mode of C-H of the PP backbone in malleated PP [−1. The first area and the peak at 1180 cm−1 are assigned to the stretching vibration of C–O bond of carboxylic group of PU film former. The second area related to C=O stretching vibration of the film former [Examples of FTIR spectra of rGF are presented in tructure . The medtructure . For thebackbone , and of backbone . The chaeated PP  and of Neated PP . For them former .The effects of the acetone and acidic pre-treatments can be seen in Examples of the resized rCF are shown in In nitrogen atmosphere, carbon fibres are considered stable at the temperature range of the TGA experiment and mass loss to be related to the degradation and evaporation of the sizing on the fibre . The masThe tensile test results for the rGF-PP and rGF-PA composites are reported in The amount of sizing on the fibre surface correlated with the composite tensile properties in the case of PP showing initially an increasing trend in strength and modulus with increasing amount of sizing but at higher concentrations again a drop in the performance. This is assumed to be due to the plasticizing effect of the excess film former at the fibre-matrix interface. The fracture surface of the rGF-PP compounds a,b withoFor PA6 composites with PU-based sizing, there was no correlation between the amount of the sizing and the tensile properties . As the The rCF composite tensile test results  indicateThe fracture surfaces of the rCF compounds  reveal tE1) of short, aligned glass and carbon fibre-reinforced composites is Halpin-Tsai equation [η and ψ are given as:To evaluate the reinforcing efficiency of the resized fibres, the tensile properties of the thermoplastic compounds were compared with a theoretical ideal value. The rule of mixtures (RoM) is commonly used to approximate the tensile modulus and strength of fibre-reinforced polymer composites. RoM is based on the properties of the components as well as their relative volume fractions. The reinforcing efficiency of fibres is related to the load transfer at the fibre matrix interface. Many models exist for prediction of composite properties. One of the models to predict the tensile modulus (equation :(1)E1=EMFE and ME are the tensile modulus of fibres and matrix, fV fibre volume fraction, ξ is a shape fitting parameter to fit the Halpin-Tsai equation to the experimental data, ψ depends upon the particle packing fraction and φmax is the maximum packing fraction and has a value 0.82 for random packing of fibres. If fibres with a circular cross-section are oriented in the flow direction during compounding, ξ can be given for longitudinal modulus by the Equation (3):L refers to the length of a fibre in the flow direction and D is the diameter of the fibre.In the Equations (1)–(3), The Halpin-Tsai model uses the following assumptions: the fibres are axisymmetric, identical in shape and size. The orientation of the fibres is assumed to be longitudinal and the distribution random. Additionally, the fibres should strongly bond to the matrix interface, and no interfacial slip during deformation is considered . The recThe aim of this study was the optimization of the batch-type sizing processes for recycled fibres. The effect of different sizing variables, such as pre-treatments of fibres, the concentration of the sizing solution, and rinsing the resized fibres after sizing, were tested for recycled glass and carbon-reinforced thermoplastics. Fibre surface pre-treatments were found to be neither needed nor successful to improve the final composite properties. Increasing the concentration of the sizing solution increased the amount of the sizing on the fibre surface whereas rinsing the fibres after the batch-type sizing decreased the amount of the sizing—both following intuitive behaviour. For glass fibres, an initial increase followed by a decrease in composite properties was found as a function of the amount of sizing. This trend was more distinct for the polypropylene-based sizing for polypropylene matrix than for the polyurethane-based sizing for polyamide matrix. The reason was analysed to be the plasticising effect of excess film former at the fibre–matrix interphase, highlighting the importance of the rinsing step in the process. For recycled carbon fibres, the sizing had little effect on the tensile properties of the thermoplastic composites, but the sizing was essential to gain better handling and post-processing properties. A comparison between experimental results and theoretical prediction using Halpin–Tsai model showed up to 81% reinforcing efficiency for glass fibres and up to 74% for carbon fibres.


This paper reports the finding of unstable limit cycles and singular attractors in a two-dimensional dynamical system consisting of an inductor and a bistable bi-local active memristor. Inspired by the idea of nested intervals theorem, a new programmable scheme for finding unstable limit cycles is proposed, and its feasibility is verified by numerical simulations. The unstable limit cycles and their evolution laws in the memristor-based dynamic system are found from two subcritical Hopf bifurcation domains, which are subdomains of twin local activity domains of the memristor. Coexisting singular attractors are discovered in the twin local activity domains, apart from the two corresponding subcritical Hopf bifurcation domains. Of particular interest is the coexistence of a singular attractor and a period-2 or period-3 attractor, observed in numerical simulations. Memristors postulated by Chua in 1971 ,3. The fA generic memristor, possessing coexisting pinched hysteresis loops and twin local-activity domains, is designed and named a bistable bi-local active memristor (BBAM) in . Here, bL. Its mathematical model is shown inside the rectangle box of The corresponding dynamic system is described by the following two-dimensional system:The twin subcritical Hopf bifurcation domains of this system having unstable limit cycles are shown in The paper aims is to present an easy operational scheme for finding unstable limit cycles and to explore the complex dynamical behaviors of system (1). More precisely, in this paper, unstable limit cycles will be found by the designed algorithm and their evolution law will be revealed by numerical analysis, and moreover coexisting singular attractors will be identified in the local activity domains of the memristor.The rest of the paper is organized as follows. A programmable scheme for finding unstable limit cycles is designed and verified by numerical simulations in In order to find unstable limit cycles of a dynamic system, some feasible schemes were suggested . HoweveThe proposed programmable scheme searching for unstable limit cycles is shown in Remark 1.The disturbance terms Algorithm 1 is verified as follows. Letting the parameters Algorithm 1: An algorithm for finding unstable limit cycles.Step 1. Determine the equilibrium points Step 2. Disturb the coordinate component Step 3. Trigger a larger perturbation Step 4. Select the initial condition as the midpoint Step 5. Mark Similarly, when the voltages V decreases in one subcritical Hopf bifurcation region, V crosses the critical value V increases in another region of Evolution law can be drawn from Coexistence of attractors is often observed in higher-dimensional nonlinear autonomous dynamical systems ,27,28 orLetting the voltage V are selected as a pair of opposite values, When V from the twin local active domains of the memristor, coexisting attractors of the associated dynamical system can indeed be found by numerical simulations. t = 0–300 s and t = 8700–9000 s, respectively. The initial condition and time length for each attractor are marked in t increases, one of the two singular attractors (the red attractor) shown in t = 0–300 s and t = 3700–4000 s. The initial conditions and time duration for each attractor are listed in t = 3700–4000 s, one of the coexisting attractors (the red attractor) in Next, the question if coexisting attractors can emerge from system (1) is discussed. By selecting an appropriate voltage V variations. It is interesting to find that when the parameter value of V is changed to the opposite value, the corresponding attractor will appear and is also symmetrical with respect to one in the original system. This is the external response of the intrinsic properties of the memristive twin local active domains in the associated dynamical system.In summary, the coexistence of singular attractors indicates that, starting from different initial conditions, the system state will move to different regions and form different attractors under parameter This paper presents a programmable scheme for finding unstable limit cycles and explores the complex dynamics of the associated dynamical system in the twin local-activity domains of the memristor. Unstable limit circles are found by the proposed algorithm, which appear in pairs and are symmetrical about the origin in the two subcritical Hopf bifurcation regions, determined by the intrinsic properties of the system. In the twin local activity domains of the memristor, coexisting singular attractors emerge from the associated dynamical system. This coexistence indicates that the system is very sensitive to initial conditions. Easily missed but not unimportant, the coexisting attractors also appear in pairs and are symmetrical about the origin, which is the external response of the symmetry of the bistable bi-local active memristor. The twin local active domains of the memristor present the complexity of its associated dynamical system, indicating that many other types of dynamical systems constituting of the memristor deserve further exploration.