In the past, most of the entity prediction methods based on embedding lacked the training of local core relationships, resulting in a deficiency in the end-to-end training. Aiming at this problem, we propose an end-to-end knowledge graph embedding representation method. It involves local graph convolution and global cross learning in this paper, which is called the TransC graph convolutional network (TransC-GCN). Firstly, multiple local semantic spaces are divided according to the largest neighbor. Secondly, a translation model is used to map the local entities and relationships into a cross vector, which serves as the input of GCN. Thirdly, through training and learning of local semantic relations, the best entities and strongest relations are found. The optimal entity relation combination ranking is obtained by evaluating the posterior loss function based on the mutual information entropy. Experiments show that this paper can obtain local entity feature information more accurately through the convolution operation of the lightweight convolutional neural network. Also, the maximum pooling operation helps to grasp the strong signal on the local feature, thereby avoiding the globally redundant feature. Compared with the mainstream triad prediction baseline model, the proposed algorithm can effectively reduce the computational complexity while achieving strong robustness. It also increases the inference accuracy of entities and relations by 8.1% and 4.4%, respectively. In short, this new method can not only effectively extract the local nodes and relationship features of the knowledge graph but also satisfy the requirements of multilayer penetration and relationship derivation of a knowledge graph. With the increasing construction of giant knowledge graphs, graph neural networks (GNNs), graph convolutional network (GCN) , and othA large number of knowledge graph cases show that a node often has a strong semantic relationship with a small number of adjacent nodes. It is not like GCN on “seeing flowers in the fog” and “finding needles in the sea” on the entire map, learning some valuable information from the giant knowledge map. Through the training and learning of the model, we should enable it to accurately classify the types of entities and predict and judge the attributes of the classified entities. An example is shown in The simple dot product of feature vectors and linear classification calculations can cause certain feature loss, which makes the entity classification and attribute prediction ineffective. As such, we propose a lightweight GCN for nonlinear cross learning of local knowledge graphs. Global iteration will certainly improve the coverage and accuracy, but this is often at the expense of the computational efficiency of the algorithm. At the same time, the knowledge graph structure or the baseline models of knowledge representations, such as TransE, TransR , and PTrGiven an example of such a set of triples as in To sum up, PTransE has a significant impact on the relational path embedding. It integrates multistep relational paths into knowledge representation learning, realizes information reasoning from the relational level, and improves the performance of knowledge graph completion. In terms of path selection, we proposed a resource allocation algorithm. Although this algorithm is feasible in quickly obtaining an effective relationship path, it is easy to cause resources to move closer to the entity that flows to the first step. If we select the first step of resource flow to the entity path, the first step of relationship path fitting will be generated. The main reason is that the co-occurrence relationship of global node features is ignored. Thus, a new local convolution global crossover named TransC-GCN is proposed in this study. It can not only effectively extract the local nodes and relationship features of the knowledge graph but also consider the needs of multilayer penetration and relationship derivation of the knowledge graph.We are committed to embedding giant graphs and high-dimensional entities into low-dimensional entity type relationships.   Through the graph convolution learning of local entity relationship, not only can the hidden entities and relationship features in the local be discovered but also the local knowledge representation effect can be improved.  The continuous improvement of local knowledge representation ability will improve the overall knowledge learning performance and strengthen the knowledge reasoning ability.  The small-scale local graph convolution application can avoid the occurrence of global overfitting while solving the long calculation time.Based on the research goals, we consider further adding local knowledge relationship path features on the basis of PTransE. At the same time, we combine multiple local crosses to realize the combination of local deep learning of relationship paths and global fusion representation.Partial Division Problem. If the part is too small, it will increase the amount of graph convolution calculation. On the contrary, the local features would be too rough. Therefore, partial division is the primary challenge.Cross Loss Function. The iterative application of the local GCN improves the learning effect of local features by defining the loss function and constraining the optimization during the local crossover process. This is a key to ensuring the quality of the model.In order to achieve the above goals, we need to address two challenges:Using graph convolution combined with the out degree and in degree of the knowledge graph to iteratively calculate the local range, which can prevent the local division from being too large, we limit the local calculation to a certain threshold range related to the global graph structure.The joint loss function is constructed through knowledge prior probability, posterior probability, and local cross entropy, which is calculated by normalization.Our contributions can be summarized as follows:Kipf et al.  introducGCN combining features of nearby nodes is dependent on the structure of the graph, which limits the generalization ability of the trained model on other graph structures. Ermis et al.  believe Graph Sample and Aggregate (GraphSAGE) is the most representative method in terms of uniform sampling of neighbor nodes and local node aggregation, as shown in GAT  uses theUnlike GCN, GAT allows implicitly assigning different importance to neighbors of the same node, while learning that attention is helpful for the interpretability of the model. The operation of GAT is point-by-point, and it is unnecessary to visit the global graph structure in advance. Therefore, it is suitable for inductive tasks. Important nodes in the graph and relations between nodes help to filter the noise between the neighbors of nodes and improve the interpretability of model results.Mr for the relationship r of each triplet <h, r, t> from the perspective of the relationship difference, and the head and tail entities are projected into the corresponding relational space. Then, TransE is used for translation. It is just that the head entity and the tail entity share Mr in the same triple, and there is no distinction between the head entity and the tail entity.A wide range of knowledge graph embedding techniques has been proposed. Based on the idea of TransE, the Trans  defines r space; then, Mrhh and Mrt are obtained. CrossE  is a hyperparameter that adjusts the ratio of balanced coding and partial crossover and θ°={θ1°, θ2°, θ3°} is the adjustment parameter.In the training process, to effectively supervise the feature loss caused by local convolution of the knowledge map and the partial filtering loss. When the divergence fusion crosses, the two tasks in the model are combined for training. This can improve the end-to-end training of the model. In summary, the joint loss function is written asTo further verify the effectiveness of TransC-GCN, we adopt the same experimental setting of Bordes et al.  in termshttps://github.com/daiquocnguyen/ConvKB) and ConnectE-E2T + TRT(https://github.com/Adam1679/ConnectE) programs were run.Furthermore, we compare our model with multiple baseline models under different parameter settings on the two tasks of entity type classification and entity attribute prediction. Moreover, we compare it with the baseline model , where CIn order to be more pertinent and comparative, we refer to the datasets extracted from the text relationship  as our rThe visualization of the dataset intuitively shows that the number of entities and relationships and the degree of association have a greater impact on the local knowledge graph. N is the triplet number for the training dataset; Ranki is the score averaged to the ith correct classification entity; and Hit rate is H_@K (K = 1/3/10), which means that in traversal training, the ability to obtain the correct triple entity prediction classification can be obtained once in K replacements.In order to verify TransC-GCN, we refer to two typical evaluation methods . FormallWe conducted experiments on the training sets and the validation sets, as shown in We conducted cross explorations of different combinations in the setting of various parameters. According to the validation set effect of the corresponding dataset, the average ranking score will be the best.Compared with tail entity and head entity prediction baseline models of the Bilinear, MLP and Trans series are shown in As shown in Figures As shown in We have shown that our TransC-GCN can handle large-scale knowledge graph and entity-relationship representation learning. In Because Savannah James like Zoe Saldana, she appreciated Avatar. Maybe she likes the bra of Athletic undergarment, which is of the brand Zoe Saldana. Of course, Savannah James must pay more attention to the player number of 23, so she may be want a signed 23 athletic undergarment bra of Zoe Saldana.When the gradient adopts AdaGrad to start training, the square of the accumulated gradient is found, which causes the effective learning rate of GCN to decrease prematurely and excessively. After inactivating neurons with small gradients, ReLU is used as the activation function, resulting in loss of diversity.Although experiments show that there is no significant difference between the maximum pooling and the average pooling in the results, there is still a loss of sparse entities in the test.TransC-GCN is not efficient due to repeated calculations of neighbor nodes across subgraphs.In this paper, we propose a TransC-GCN method based on local convolution and global crossover for knowledge graph completion. ①This is the first time that local GCN and TransC are combined for knowledge graph representation learning. ②TransC-GCN can not only divide the huge knowledge graph into several local knowledge graphs and use convolutional neural network coding for more intelligent and subtle local knowledge graph feature learning with strong semantic relations but also realize the volume of adjacent nodes and relationship features. ③Pooling and filtering data noise provide a new and efficient method for node relationship prediction and classification. ④TransC-GCN considers the information value of nearby local knowledge graphs. We propose a parallel method of cross fusion of local knowledge graphs based on divergence, which combines local knowledge graphs and global knowledge graphs more flexibly in representation learning. In a number of challenging baseline model test comparisons. TransC-GCN has excellent performance in entity reasoning accuracy and generalization ability and is lightweight. However, there are deficiencies in entity diversity learning:For future work, we will try to combine the pattern sequence ordering and the graph context to optimize TransC-GCN. Meanwhile, based on TransC-GCN, we intend to propose a new scene recommendation algorithm based on the combination of graph embedding and collaborative filtering.


Artificial bionic skin material is playing an increasingly important role in the field of medicine and bionic engineering and becoming a research hotspot in many disciplines in recent years. In this work, the digital moiré method was used to measure the mechanical field of the bionic skin material under different suturing conditions. Through the digital image process, the deformation characteristics and the stress distribution near the contact area between the bionic skin material and the suture were obtained and discussed. The different healing effects caused by suturing mode were further explored, which can provide mechanical guidance for wound suturing in clinical medicine. Artificial bionic skin materials are widely applied in the field of biology and clinical medicine. People can study the specific function of natural biological performance by simulating the natural biological structure using biomimetic skin material, which is essential in tissue engineering and regenerative medicine . In clinStress concentration usually occurs during the contact of the bionic skin material with the surgical suture. Hoy and Gingras  comparedDue to the characteristics of large deformation, Gao and Qian and Gao and Gao , 9 foundHuman skin tissue is nonuniform material, with nonlinearity, structure particularity, anisotropy, and specificity of physical and mechanical properties . MechaniThe deformation fields of the area around the pinhole using I-shape and V-shape suturing pattern were measured by the digital moiré experiment method. The specimen shown in Then, the black and white orthogonal gratings with a grid frequency of 3 dots/mm were prepared by spraying around the sutured area. Finally, the stitched specimens were fixed on the Instron 3343 electronic universal testing machine (load range 10 N~1000 N), applying a uniaxial tensile load of 2 mm/min. The experimental images were recorded by a BaslerA202K CCD camera (resolution 1003 pixel × 1004 pixel) and the associated image acquisition system. The second specimen was sutured using a V-shape pattern as shown in In this paper, the orthogonal grating images captured at the load of 28 N are analyzed. The horizontal and vertical grid lines were extracted after image preprocessing, and then, the images were processed using digital moiré image technology, mainly achieved through GUI programming of Matlab software. The brief processes are shown in The whole process can be divided into three steps. The first step is image preparation, in which the images of the deformed gratings were preprocessed and binarized, and the reference gratings were generated by the software. In this paper, the deformed grid lines were extracted into horizontal and vertical gratings, and then, a denoising was performed to enhance the gate line information. The collected images may be affected by the uneven illumination during the experiment. Therefore, the grating image was divided into several subregions, and the average gray value was selected as the threshold in each subregion. The second step is image processing. The binary transform grid diagram was superimposed on the four phase shift reference grid graphs, and the logical moiré pattern was obtained by logical operation. Wavelet decomposition was applied to the logical moiré image, and the high-frequency noise was filtered by selecting a proper threshold. And then, a clear, continuous digital moiré pattern was obtained after fringe reconstruction using low-frequency information. After the parcelled phase diagram was calculated, the Macy algorithm was used to get the unpacked phase diagram. The phase map without wrapping corresponds linearly to the fringe series distribution. Given the phase value of the fringe order zero, the phase value of each point can be determined, and then, the displacement map of the whole field was obtained. Finally, a data file was generated from the resulting deformation distribution information.After the digital image processing, the displacement field information in vicinity of the suture area was directly obtained. By coordinate transformation, the displacement fields are presented in radial and circumferential form for better illustrating, as shown in ur ≈ 0 as characteristic lines , the observation area can be divided into two different regions. In uθ ≈ 0 (gray dashed lines) are approximately located near the center of the four sectors. The characteristics of the displacement field show that after loading, the upper and lower sectors are the expansion zone, where the material approaches the concentrated force acting point in the radial direction, and become wide and occupy the majority of the sharp angle area, marked as EX in It can be seen from the displacement field information that the bionic skin material clearly exhibits the characteristics of the section configuration near the area in contact with the suture. If set It can be found that the partitioning features of the expansion zone and shrinking zone can be found near the pinhole both in I-shape and V-shape sutured specimens. The difference is that the displacement field of I-shape suturing is composed of four sectors, and the fan-shape area of the V-shape suturing is composed of three parts. The possible reason for the difference is that, under the same load, the specimens were subjected to equivalent concentrate forces in the vertical direction, the component force in the horizontal direction will cause the shrinkage zone of the second specimen under the action of the V-concentrated force, and the range of the shrinkage zone is related to the angle of the suture lines. Due to this reason, the expansion deformation on top of the suture point was weakened or offset.∂ur/∂r, ∂ur/∂θ, ∂uθ/∂r, and ∂uθ/∂θ are the partial derivatives of the displacement components in the polar coordinate system. The strain field at each point can be directly calculated from the displacement by interpolation. Since the strain is a secondary information, errors are inevitable in this process, the noise of the displacement field was filtered out by wavelet transform in this work, and then, the strain field was calculated based on the large deformation theory. The radial strain field εr, the circumferential strain field εθ, and the shear strain field εrθ of the pin tip region are shown in To understand the rule of sector division more intuitively, the experimental results were transformed into the strain field under the polar coordinate system, using the displacement-strain relation shown in Equation . (1)εr=∂The cool color in the figure represents a negative value, and the warm color represents a positive value. It can be seen that the radial strain is negative and the circumferential strain is positive in the upper region of the suture point, and the shear strain on the left and right sides of the surgical line is opposite. These features indicate that the material in this region produces radial compression and annular expansion under the extrusion of the surgical line. The material deforms towards the suture point in the radial direction and extends around the suture point in the circumferential direction. The radial strain is positive, and the circumferential strain is negative in the lower position of the concentrated force point. The shear strains on the left and right sides of the surgical line are also opposite, indicating radial stretching and circumferential shrinkage in this area, which is just opposite to the deformation in the upper area of the suture point. In conjunction with the displacement field results, it can be seen that the displacement and strain values are almost zero in the area surrounded by the two intersecting sutures, indicating that the deformation of the region is relatively small and remains relatively stable under external loads.It can be seen that the bionic skin exhibits a sector division configuration of expanding sector and shrinking sector under the tension of I-shape and V-shape sutures. However, differences can be seen in the two cases after comparison. There are four fan-shape zones under the action of I-shape suturing, and only three sectors can be found in the V-shape suturing. In the latter case, there is a triangular region within the range of the intersection of the surgical lines, where the strain is gentler and the circumferential strain is slightly contracted. The difference in the configuration of the two suture patterns will affect the healing of the wound to a certain extent.By inputting the experimentally measured mechanical properties of bionic skin materials into ABAQUS software, finite element analysis was performed to further explore the effect of suturing on wound healing. The constitutive model and its parameters were optimized by a variety of fitting methods. And then, numerical models were established on this basis. The geometrical and material parameters of the numerical models were the same as those of the experiment. The image with the external load of 28 N was analyzed. The distributions of the principal stress are shown in It can be seen from the figure that the differences of the distribution of the principal stress between the two cases are not very evident. The values are apparently different. In the relevant medical analysis, the “average stress index” (ASI), i.e., the ratio of the principal stress integral to the area in the calculated area, is commonly used to assess the stress level near the suture . In thisIn the above two experiments, the incision of bionic skin can remain fixed under the constraints of the surgical suture and showed a similar deformation law. Deformation differences can also be found according to the displacement and strain field, which will have some effect on the recovery of the wound. In the case of I-shape suturing, the expanding sector appears on both sides of the surgical line, and the material in this region is moving towards the contact point and extends towards both sides with the suture as the center. In the V-shape suturing case, little movement can be seen in the triangular region surrounded by the suture intersects due to the restriction of the suture.When held under tension, an expansion sector that deviates from the edge of the wound and caused by the vertical concentrate force (I-shape suturing) appeared near the contact area. This is not conducive to the recovery of the wound and may lead to scars after cure. The deformation of the wound is relatively much smaller in the triangular area surrounded by surgical sutures under the action of crossconcentrated force (V-shape suturing), indicating that the V-shape suturing can play a more stable role in the wound healing under the same external force. Moreover, the concentrated stress can be dispersed by V-shape sutures, resulting in a wider area of expanding sector with smaller strain gradient, which is a positive factor for wound recovery. Selecting an appropriate suture density can further reduce the strain gradient, hence promoting wound recovery.In addition, the value of ASI is greater in V-shape suturing than I-shape suturing. Sutures can provide appropriate mechanical support during the wound healing period, but the relevant local stress caused by the sutures also can change the wound repair environment to a certain extent. Wound healing is a complex process where moderate stress can stimulate growth factors conducive to wound healing. However, excessive stress can cause wound inflammation, cracking, ischemia, and even gangrene phenomenon, because transitional restrictions on the deformation of the wound, especially in the triangle area surrounded by crossed sutures, will lead to local poor blood circulation and subcutaneous nervous system obstruction, leaving the drug and nutrition cannot be normally delivered to the wound, affecting tissue regeneration and repair. In addition, material instability phenomenon may happen when the stress level reaches or exceeds a certain threshold, resulting in surface wrinkles affecting the appearance.Based on the above analysis, it can be seen that the suturing pattern can affect the level and mode of constraint near the wound area even under the same external force. Therefore, the appropriate suturing pattern should be chosen according to the following situations: V-shape suture can effectively promote wound healing in common cases; but for joints with more frequent movement or patients with skin microcirculation disorders, I-shape suturing is more suitable. In addition, skin wrinkles may easily caused by large stress concentration, which will affect the appearance of the human face skin. However, it can also promote nutrient absorption in the esophagus, intestine, and other parts of the wall mucosa, playing an important physiological role. Hence, this factor also needs to be considered in the choice of suture pattern. V-shape suturing should be recommended for the skin, and the I-shape suturing is recommended for inner lumen structures.It is worth mentioning that this article mainly focuses on the effects of stress and deformation on wound healing, but the wound healing of real skin is a complex process. In addition to mechanical stimulation, the motion state, nutrition intake, drug delivery, surgical technique, radiation, cytokines, and other complex physical and chemical factors can also have great influence. The authors are currently preparing an animal skin suture experiment to conduct a comprehensive consideration.


K and α) need to be selected in advance, which mainly contains two steps: the maximum kurtosis index is employed to preliminarily determine a series of local optimal decomposition parameters (K and α), then from the local parameters, the global optimum parameters are selected based on the minimum energy loss coefficient (ELC). After decomposition by IVMD, the raw signal is divided into K intrinsic mode functions (IMFs), the optimal IMF(s) with abundant fault information is (are) chosen based on the minimum envelopment entropy criterion. Secondly, the time-shift technique is introduced to information entropy, the time-shift multi-scale sample entropy algorithm is applied for the analysis of the complexity of the chosen optimal IMF and extract fault feature vectors. Finally, the sparrow search algorithm, which takes the classification error rate of SVM as the fitness function, is used to adaptively optimize the SVM parameters. Next, the extracted TSMSEs are input into the SSA-SVM model as the feature vector to identify the gear signal types under different conditions. The simulation and experimental results confirm that the proposed method is feasible and superior in gearbox fault diagnosis when compared with other methods.The working environment of wind turbine gearboxes is complex, complicating the effective monitoring of their running state. In this paper, a new gearbox fault diagnosis method based on improved variational mode decomposition (IVMD), combined with time-shift multi-scale sample entropy (TSMSE) and a sparrow search algorithm-based support vector machine (SSA-SVM), is proposed. Firstly, a novel algorithm, IVMD, is presented for solving the problem where VMD parameters ( In recent decades, the installed scale and grid-connected capacity of wind turbines have increased significantly. As of the end of 2019, the installed capacity of wind turbines in the world exceeded 690 million kW, and more than 100,000 wind turbines had been built  used fauThe gearbox is a critical component in the drive system of a wind turbine; due to the influence of its working environment, local faults such as cracks or spalling frequently occur. According to research, gearbox faults account for one-quarter of the total wind turbine faults, and the operation and maintenance costs account for about 25%–35% of the total cost of wind turbines. The downtime caused by gearbox faults is longer than that caused by other faults ,7. ThereK and the mode frequency bandwidth control parameter α of the VMD algorithm. When α is small, and the bandwidth of the Wiener filter is large, which can better detect the impact components in the signal; however, simultaneously, the decomposed modes are more likely to contain noise components , and N indicates the population size. bestx denotes the global best position at present; β is a random number, which follows a mean of 0 and a variance of 1 in the normal distribution; K represents a random number within ; i, fg,f and wf indicate the fitness value of the current individual, the fitness value of the global optimal solution and the fitness value of the worst solution, respectively. In addition, an arbitrary small constant ε is introduced to avoid zero division error  and α ∈ , respectively, with a search step Δα = 500. Selecting the best VMD parameters according to the IVMD algorithm process described above. The parameter optimization process of the IVMD algorithm for the simulation signal is shown in The search range and step of K, the ELC value decreases at the beginning and then increases, and then decreases continually. According to the trend in K continues to increase, the ELC will also decrease. Therefore, after the mode decomposition number K was 5 (including 5), the simulation signal showed over-decomposition and mode mixing. Based on the result , which is marked in the red box and selected as the optimal VMD decomposition parameter of the simulation signal, the signal was decomposed by VMD with that parameter. The decomposition results are presented in K, α) of VMD. From In accordance with the above simulation signal analysis results, we used the IVMD algorithm to decompose gear signals under four conditions. Taking the tooth crack fault as an example, the optimization process of IVMD decomposition parameters is shown in To further verify the above findings, IMF3 was selected as the optimal IMF decomposed by IVMD and EMD according to the minimum envelope entropy criterion to perform envelope analysis, and the results are shown in In a gearbox system, a local fault in the gear causes periodic vibration of the signal. The more obvious the periodicity of the fault signal, the smaller the envelope entropy value. Therefore, the optimal mode components in each work stage were selected according to the minimum envelope entropy value criterion for subsequent feature vector extraction, and time-domain waveform of the optimal IMFs is depicted in th, 11th, and 16th scale; on the other scales, the two signals can be identified. Considering the whole scale, the four features’ entropy curves seriously cross, which means the four signals’ conditions cannot be clearly distinguished. It also can be seen that MSE is unable to measure the complexity of the signal on higher scales due to the influence of coarse graining processing. The feature entropy obtained by the TSMSE algorithm shows a good degree of differentiation for each signal  of the SVM. The parameters of the algorithm are shown in Based on the above experimental signal analysis results, the SSA was applied to perform adaptive optimization of the parameters  is superior to the original algorithm  by comparative analysis. Furthermore, to prove that the final combination algorithm (IVMD-TSMSE-SSA-SVM) provides advantages in fault diagnosis of wind turbine gearbox, the proposed optimized combination algorithm model was compared with different combination algorithm models, and the results are shown in (1) The average testing accuracy of the classification model using the IVMD algorithm (96.15%) is higher than that using the default VMD parameter (93.28%). Consequently, the above result proves that the proposed IVMD algorithm performs better than the default parameter VMD algorithm in signal decomposition.(2) The average testing accuracy of 98.45% can be achieved by the classification model combined with the TSMSE feature vector, which outperforms the model with the feature vector selected by MSE (90.95%), as the TSMSE reflects the complexity and chaos of the signal on different scales and it is influenced by the length of the time series that is weakly compared with the MSE algorithm due to the time-shift technology. The above discussion verifies that the TSMSE algorithm can extract information with more abundant fault features and is superior in fault feature extraction.(3) The SSA-SVM model has higher fault identification accuracy compared with the original SVM model; the testing accuracies of the two models are 97.05% and 92.35%, respectively, which indicate that the SSA can effectively determine the best SVM parameters. That is, the SSA-SVM model can effectively identify gear vibration signals under different conditions. The above analysis shows that the performance of the proposed model in wind turbine gearbox fault diagnosis is more accurate than that of other methods. Therefore, this model shows great application potential in fault diagnosis.This paper proposed a new wind turbine gearbox fault diagnosis model to accurately extract fault features and diagnose fault states. The effectiveness of this model in fault diagnosis was verified through experimentation; however, the proposed model has some limitations, which are listed as follows:(1) At present, the rotating machinery equipment is developing toward being large-scale and intelligent, so the structure of the equipment is becoming increasingly complex, and the collected signals contain increasingly abundant information, which poses difficulties in effectively extracting the fault features of a signal. Although the IVMD algorithm effectively determines the parameters of the VMD adaptively, the time cost increases when it deals with complex signals. Therefore, improving the IVMD algorithm to reduce the time cost is a direction for future research.(2) In the proposed method, SSA is used to optimize the parameters of the SVM model. Although SSA has some advantages compared with other algorithms, the parameters (percentage of producers and safety threshold) in the SSA are set artificially, which relies on the users’ prior experience. This may lead to poor optimization results due to improper parameter selection. Therefore, future research should determine how to avoid the influence of human factors on the optimization effect of SSA.


Vaccination against SARS-CoV-2 will likely be the most promising way to combat the pandemic. Even if mass vaccination is urgent, it should still always be supported by appropriate patient safety management. The aim of this study, based on failure mode, effects and criticality analysis (FMECA), was to identify possible failures and highlight measures that can be adopted to prevent their occurrence. A team of resident doctors in public health from the University of Padua and specialists in risk analysis in public health examined the mass vaccination process. A diagram was drafted to illustrate the various phases of mass vaccination, analyze the process, and identify all failure modes. Criticalities were ascertained by rating the severity, frequency and likelihood of failure detection on a scale of 1 to 10. We identified a total of 71 possible faults distributed over the various phases of the process, and 34 of them were classified as carrying a high risk. For the potentially high-risk failure modes, we identified 63 recommended actions to contain the cause of their occurrence or improve their detection. For the purpose of detecting potential failures, FMECA can be successfully applied to mass vaccination, which should be considered a high-risk process. Deadly pandemics and large-scale epidemics have challenged human existence throughout history. While these crises were once separated by centuries, or at least many decades, they are now becoming much more common. Since 2003, we have experienced severe acute respiratory syndrome (SARS) (a near pandemic), an influenza pandemic (H1N1pdm in 2009), a chikungunya pandemic (2014), a Zika pandemic (2015), and a widespread pandemic-like extension of Ebola over five African countries, with cases exported globally (2014 to 2015) [SARS-CoV-2 is a new type of coronavirus that causes a serious, contagious disease (COVID-19) ,4. The rAlthough hundreds of clinical trials have been initiated since the outbreak of COVID-19, an antiviral drug that is effective in all patient groups has yet to be developed and assessed. Hence the urgent need to vaccinate the whole population against the SARS-CoV-2 virus. Vaccination will likely be the most effective way to counter the COVID-19 pandemic . The proWhile the development of a safe and effective COVID-19 vaccine has not been easy, its production and distribution, and its administration especially, also pose extraordinary challenges . Mass vaTwo methods are used to manage the risks associated with critical processes. One is reactive: measures are taken after an adverse event has occurred to prevent it from happening again. The other is proactive: processes are analyzed a priori to prevent adverse events from occurring in the first place. One of the most popular proactive methods is failure mode, effect and criticality analysis (FMECA). According to the Joint Commission, FMECA is a systematic, analytical technique used prospectively by a team to prevent the appearance of problems associated with a process before they occur . This isThese step-by-step assessment methods have increasingly been used to maximize the safety and quality of clinical care in many healthcare settings and are now widely used to proactively evaluate complex clinical processes.The purpose of this study was to conduct a prospective and systematic analysis of the various stages of the mass vaccination process, applying FMECA to identify possible errors and enable preemptive measures to be taken.The FMECA was conducted in accordance with the process described in The analysis was conducted in April 2021, about 4 months after the start of the COVID-19 vaccination campaign in Italy when about 7,401,431 people  had received a single dose of vaccine while 3,333,644  had completed the vaccination course .After an introductory session held with a team of experts to explain the features of FMECA, mass vaccination against SARS-CoV-2 was identified as the high-risk process to investigate. The team consisted of resident doctors in public health from the University of Padua who were actively involved in the mass vaccination program underway in Veneto  in different local health units, together with in public health specialists with expertise in risk analysis. A process diagram was drawn up, illustrating the various phases of the mass vaccination process .Analyzing the process enabled all failure modes to be identified, and criticalities were pinpointed by rating these failure modes in terms of their: occurrence (probability of the event occurring); detectability ; and severity (effect of the error on the patient). Each item was classified on a scale of 1 to 10. The numerical score quantifying the three items was used to calculate a risk priority number (RPN), which is the product of the severity, occurrence and detectability scores (RPN = occurrence × detectability × severity). The median value of the failures’ RPNs was used to assess the final score, and we also reported the ranges of the risk priority numbers (RPN).Thus, as part of the FMECA, the RPN is a numerical estimate of a risk attributed to a process, or a step in a process; it identifies the elements most likely to contribute to medically serious failures.The maximum RPN is 1000 and any RPN > 100 was used to identify a high-risk failure . This isFor each failure mode, the team analyzed the criticality index and decided whether the risk was acceptable or improvements were needed. The highest scoring failures were considered high-risk and identified as priority areas in which improvements, through safety strategies, should be made.The assessment process detected a total of 71 possible failures distributed over the various phases of the process , and 34 The RPNs obtained  ranged fFor the potential high-risk failure modes, at least one recommended action was identified with a view to reducing their occurrence or improving their detection. This resulted in the 63 recommendations listed in FMECA is increasingly used as a method for assessing processes and improving their safety. Given the numerous potential failure modes in every phase of a mass vaccination process (most of them defined as high-risk), our study shows that this activity should be considered a high-risk process, just like other healthcare activities conducted in ambulatory settings.Many failures are related to the spatial layout of the MVC. The unavailability of health facilities with the features needed to conduct mass vaccination programs, and the unfeasibility of quickly building new ones made it objectively difficult to reconcile the need to ensure user safety with the adaptation of spaces normally used for other activities.Taking into account the operational document for organizing MVCs published in the Veneto Regional Authority’s official bulletin (Bur) in March 2021  and the In the phase where the vaccines are reconstituted, the RPNs were ≥200 for every failure mode identified . This finding could be due to the complexity of the procedures and the high workflow typical of mass vaccination resulting in failures that are hard to detect but have potentially severe effects on public health (by reducing the efficacy of vaccination) and users’ health (by causing anaphylactic reactions). For many years, the emphasis has been on the adverse effects of vaccines after their administration, while little is known about the delicate phase of vaccine dose preparation. Paparella’s work  highlighJudging from the RPNs, the pre-vaccination screening and post-vaccination observation phases should be considered the phases at highest risk: “Failure to investigate clinical history ” or “Users leave MVC before completing the required observation period (based on their risk factors)” could have the most severe effects on users . We recommend several actions to prevent these most risky failures, such as giving users written notification of their exit time, checking users at the exit, or giving users precise indications on potential symptoms of an adverse reaction. The most important recommendation, however  makes the definition of RPN-based scores context-specific . In further research on the topic of FMECA, we suggest interviewing personnel employed in other countries in order to draw up a more generalized model.FMECA can be usefully performed on a mass vaccination process to help identify potential failures. Safety strategies were recommended for each failure mode identified by our analysis and these recommended actions could be considered for practice and for further studies in the field.


The results replicated a pronounced facilitatory effect of action depiction (relative to no action depiction). By contrast, the facilitatory effect of a preceding speaker's emotional face was less pronounced. How the facial emotion was rendered mattered in that the emotional face effect was present with natural faces (Experiment 2) but not with smileys (Experiment 1). Experiment 3 suggests that contrast, i.e., strongly opposing emotional valence information vs. non-opposing valence information, might matter for the directionality of this effect. These results are the first step toward a more principled account of how distinct visual  cues modulate language processing, whereby the visual cues that are referenced by language (the depicted action), copresent (the depicted action), and more natural  tend to exert more pronounced effects.Research findings on language comprehension suggest that many kinds of non-linguistic cues can rapidly affect language processing. Extant processing accounts of situated language comprehension model these rapid effects and are only beginning to accommodate the role of non-linguistic emotional, cues. To begin with a detailed characterization of distinct cues and their relative effects, three visual-world eye-tracking experiments assessed the relative importance of two cue types  as well as the effects of the degree of naturalness of social  cues . We predicted to replicate previously reported rapid effects of referentially mediated actions. In addition, we assessed distinct world-language relations. If how a cue is conveyed matters for its effect, then a verb referencing an action depiction should elicit a stronger immediate effect on visual attention and language comprehension than a speaker's emotional facial expression. The latter is mediated non-referentially  Monitoring people's gaze behavior in a visual context provides a unique opportunity for examining the incremental integration of visual and linguistic information , and not at the empty towel (as a destination) to which the apple could be moved  the utterance. For instance, washes) or the fencer (if they had heard paints). From the anticipation of the action's patient (the pirate in SVO sentences) or agent (the fencer in OVS sentences), the authors deduced that listeners had assigned a thematic role to the initially role ambiguous noun phrase the princess. Thus, comprehenders can rapidly exploit referential cues  for language processing and the assignment of thematic roles.In addition to noun-object relations, adults can use other referential cues, such as verb-mediated depicted action events, to facilitate role assignments, and thus the processing of canonical subject-verb-object (SVO) and noncanonical object-verb-subject (OVS) German sentences . The log ratio is symmetrical around zero. This means, a positive value indicates a preference to look at the target agent over the competitor. A negative log ratio indicates a preference to look at the competitor over the target agent. A value of zero indicates no preference for either of the two characters. Since the log of zero is undefined, we added a constant of 0.1 to account for missing data points regarding fixations to both the agent and the competitor. Hence, this log probability ratio expresses the strength of the visual bias toward the target agent relative to the competitor character. Additionally, it has the advantage that it does not violate the assumptions of independence and homogeneity of variance  and as a function of prime  using the mean log gaze probability ratios calculated on successive 20-ms time slots. For the inferential analyses, the log ratios were subjected to linear mixed-effects models [using lmer of the lme4 package of R  + (1+action*prime | item)]. The fixed effect structure of the model was not reduced. We calculated the values of p using the lmerTest package . In that study, the woman's happy and sad facial (static) expressions were one of the three most recognizable among 15 faces . We recorded that woman for the videos of the present studyThe emotional prime in Experiment 2 consisted of face videos. In the positive video, a woman changed her facial expression from neutral into a broad smile . The negative video was constructed in the same way but the woman's face turned from a neutral into a sad expression see . We chosThe design was identical to Experiment 1  with the exception that for the prime face, only the emotional expression varied in valence . For theThe analyses for the eye-movement data were the same as in Experiment 1. Accuracy scores for the face recall task were not analyzed inferentially since they only yielded four data points per participant. Accuracy scores for the questions about how the characters are feeling were also not analyzed as these questions were only asked on filler trials. Analyses of the comprehension question scores were performed similar to Experiment 1 using prime and action as fixed factors. However, since all experimental comprehension questions were in the passive voice, voice was not included in the models.When contrasting the incongruent (dotted lines) and congruent face prime conditions (solid lines), we note that they deviate. When no action is depicted, this happens from the end of the verb and into the adverb region (the solid is above the dotted blue line). When an action is present (red lines), the solid is above the dotted line from the middle of the verb onward until the middle of the adverb region. The presence of the emotionally congruent (vs. incongruent) prime thus draws more looks toward the target agent during the verb and the adverb region . During the NP2 region, the red and the blue lines converge again as the agent is named and can thus be discriminated.df : 577.300, t: −5.867, p < 0.01, see df : 522.3, t: −2.810, p < 0.01, see df : 572.7, t: −2.100, p < 0.05). Participants fixated the target agent significantly more than the competitor when the speaker's prime face was positive (vs. negative) upon hearing the verb-adverb and across the long region. The interaction between action and emotional prime was not significant  depicted, except for the NP1 regionParticipants answered 96% of the comprehension question and 99.4% of the face recall question correctly. The analysis of the answers for the “who-does-what” comprehension questionsThe eye-tracking results reinforce the insight from Experiment 1—viz. that people use the depicted action toward discriminating the agent of the OVS sentence starting from the verb. In contrast to Experiment 1, we also observed a significant effect of the emotional prime in the verb-adverb and long region. As before, however, the emotional cue seems to be used to a lesser degree for sentence interpretation than the action depiction as the effects emerged only in the verb-adverb and long region and were not as pervasive as the action effect. Participants' accuracy in answering both the comprehension and face recall questions was high (no significant effects of the independent factors on accuracies were observed).Experiments 1 and 2 replicated the effects of depicted actions on the assignment of thematic roles in non-canonical German OVS sentences. Participants reliably used depicted actions as contextual cues to anticipate the target agent, facilitating sentence processing in real time. Yet, whereas the schematic smiley did not affect real-time sentence processing, the natural emotional speaker's face led to a significant effect in the verb-adverb and the long region, i.e., across the whole sentence. Nevertheless, the emotional prime face still had a less pervasive effect than the depicted action. Our final study addressed this issue to examine the emotional prime effect in more detail. We will briefly address and motivate each change for Experiment 3 with regard to the results of Experiments 1 and 2. Note that Experiment 3 was conducted to maximize finding an effect of the emotional facial expression, resulting in more changes than for an incremental replication experiment.Accordingly, we changed the design, materials, presentation, and task in Experiment 3 such that the focus was on the speaker's facial expression. We omitted the action factor and scenes depicted no actions. Additionally, we removed the middle character; target scenes only contained the happy-looking target agent and the grumpy-looking competitor character. Further, the characters' facial expressions were rendered more salient see . In lineWe hypothesized that the less pervasive effect of the emotional prime effect might be due to the different ways of cue presentation. While the depicted actions were present during real-time sentence processing, the emotional prime face was presented prior to encountering the target scene and sentence. In Experiment 3, we presented the speaker's facial expression as a prime because presenting it simultaneously together with the target scene while participants listen to the OVS sentence would have drawn attention away from the characters [unpublished pilot data from another study (2011) supports this view]. However, we decreased the scene preview time from 2,000 to 500 ms. This shortens the time for which the emotional prime must be retained in working memory, perhaps facilitating its effects on the processing of the target sentence.each trial. Participants were instructed to verify via button press as quickly and accurately as possible whether the screenshot of the facial expression matched the speaker's expression in the prime video. We further assessed participants' reaction time for the assignment of thematic roles. On each trial, following the face verification, the target sentence was repeated in SVO structure. Participants were asked to verify as quickly and accurately as possible whether the OVS target sentence and the SVO sentence described the same event or not. A correct answer indicated participants had understood the thematic role relations in the OVS sentence. Finally, as we had 16 experimental items and relatively low power, we increased our sample from 40 to 64 participants.A further change concerned participants' task. In Experiments 1 and 2, participants answered comprehension questions in the active or passive voice for who-is-doing-what-to-whom and/or questions about the emotional expression of the prime face and the feelings of the depicted characters. No time limit had been imposed and accuracy had been at ceiling. To assess whether participants kept the prime face in memory during the trials, in Experiment 3 we presented them with a screenshot of either the positive or the negative speaker face after With the implemented changes, the resulting simplified design and a stronger focus on the interactive and situated setting in the instructions, we expected to find a more pervasive effect of a speaker's emotional facial expression on the real-time processing and thematic role assignment of non-canonical OVS sentences, if, as Experiment 2 suggested, emotional facial expressions can indeed facilitate the assignment of thematic roles.A further 64 students of Humboldt-Universität zu Berlin, all native speakers of German with normal or corrected-to-normal vision, between 18 and 30 years  took part in the experiment. Participants were tested in the eye-tracking laboratory of Humboldt-Universität zu Berlin. One participant had to be excluded due to a technical problem. Participants received 8.50 Euro for their participation. All gave written informed consent. Ethics approval was given by the ethics board of the German association for linguistics .We are only reporting the changes compared to Experiment 2 here. We removed the depicted actions, and retained the factor emotional prime with two levels: congruent prime vs. incongruent prime. We additionally changed the face recall questions to prime face verification: participants are now asked to decide as quickly and accurately as possible if the speaker's prime face matches the posttrial picture of the speaker's face. Additionally, we changed the who-does-what question: participants heard a sentence either matching or mismatching the target OVS sentence in content, sentence structure, or in both. They decided as quickly and accurately as possible whether the content in the two sentences was identical or not. Participants answered with their left and right index fingers using yes/no buttons on a button box. The position of the yes/no buttons was counterbalanced across participants. One experimental session took about 50 min.We removed the middle character (the patient) from the scenes, such that participants' attention is only divided between the target agent and the competitor character. Moreover, the target and competitor character's emotional facial expressions were improved such that the competitor character's face was very negative and the target agent's face very positive see .For the prime face verification questions, a screenshot of the final frame of the speaker's emotional prime face video was taken and used in each condition: For all critical items in a list, the picture of the test face was positive in half of the trials and negative in the other half. Moreover, the test face matched the prime face in the video in half of the trials and mismatched in the other half of the trials. The filler trials were also followed by either a (mis) matching positive or (mis) matching negative emotional prime face picture. Across all trials, the valence and emotional match of the pictures used for prime face verification were counterbalanced within and across lists and participants.N = 4), in content (N = 22), or matched in structure (N = 24) or in content (N = 6) with the to-be-verified sentence. Across all 44 critical item and filler trials, 24 of the verification sentences matched in structure and 20 mismatched. Also, half of the 44 verification sentences matched in content with the to-be-verified sentences and the other half mismatched in content. This resulted in half of the trials requiring a yes and half of them requiring a no answer for each participant. The same speaker (PK) that recorded the critical and filler sentences also recorded the sentences for the sentence verification question.We further created 16 SVO versions of the critical OVS item sentences for the sentence verification questions. All critical to-be-verified sentences matched in content, i.e., also in role relations and only mismatched in sentence structure, thus requiring a yes answer. Additionally, we created a verification sentence for each of the 24 filler sentences: The filler sentences either mismatched in sentence structure (If we find more looks to the target agent (vs. the competitor) during the verb-adverb region in the positive congruent prime condition (vs. the negative incongruent prime condition), we could conclude that participants have (a) correctly assigned thematic roles even in the absence of depicted action cues and (b) have done so in a facilitative fashion with the help of the positive prime face. The reaction-time data should corroborate that participants are faster in verifying OVS/SVO event identity when the prime is congruent (vs. incongruent). Conclusions regarding the assignment of thematic roles are less clear if, however, we only find effects of the positive prime face in the eye tracking but not the reaction-time data. People would still have established an on-the-fly link between the positive face, the target agent's happy facial expression and the positive verb-adverb. But—in the absence of an emotional prime effect on the response times—we could not be sure that the emotional prime improved the post-trial comprehension of the role relations. By contrast, if we find an effect of the positive prime face in the response times but not in the eye-movement record, then we could conclude that the prime face helps participants to correctly assign thematic roles but that this effect takes time and participants cannot use it “on the fly” to ease the assignment of thematic roles.Each trial started with a fixation dot  but the eye-tracking data analysis was performed on correctly answered trials only. The fixed factor for the eye-tracking analyses was emotional prime (congruent vs. incongruent). The fixed factors for the prime face verification accuracy and RT analysis were emotional prime (congruent vs. negative) and match (prime face—test face match vs. prime face—test face mismatch). The fixed factor for the sentence verification accuracy analyses was emotional prime (congruent vs. incongruent). The response-times for the prime face verification and the sentence verification questions  were analyzed by mixed-effects models using log transformed reaction times as a dependent variable and prime and match  as fixed factors. Reaction times +/- 2.5 SDt: 2.307, p < 0.05) and in the long regiondf : 17.88568, t: 2.700 p < 0.05, see the Accuracy in the prime face and sentence verification questions was lower  than for the who-does-what questions (96% correct answers in both Experiments 1 and 2). Given the lower accuracies, we excluded incorrectly answered prime face verification and sentence verification trials from the analysis. The analyses revealed a significant main effect of emotional prime in the verb-adverbz: −1.902, p = 0.0571) main effect of prime face for the face verification questionsAcross conditions, participants answered 92% of the prime face verification questions and 77% of the sentence verification questions correctly. The analysis revealed a marginal , a significant main effect of match , and a significant emotional prime x match interaction : participants responded faster when the prime face was congruent  speaker facial expression. The emotional prime face did affect the looks to the characters in the scene, and this effect emerged in the same regions as in Experiment 2 (the verb-adverb and the long region). However, the directionality of the effect goes into the opposite-than-expected direction. Participants preferred to look at the grumpy-looking competitor character more after being primed with a sentence-congruent (positive) prime face and preferred to look at the happy target agent more after being primed with a sentence-incongruent (negative) prime face , 11. TheIn three visual-world eye-tracking experiments, we assessed whether participants' incremental comprehension of non-canonical OVS sentences is modulated to the same extent by referential cues (depicted actions) and non-referential cues, i.e., visual  cues .In Experiments 1 and 2, participants made extensive use of the depicted action (vs. no action) for online sentence processing. They were more likely to anticipate the correct target agent (vs. a competitor) during OVS sentence processing in real time when the agent depicted in the scene was performing (vs. was not performing) the action mentioned in the sentence. We hence replicated existing findings demonstrating that a supportive visual context, which is referenced by the linguistic input, can rapidly facilitate OVS sentence processing and the assignment of thematic roles , but not when it was a smiley (Experiment 1). Moreover, the effects of the emotional facial expression were less pervasive compared to the effects of the referenced depicted action.The latter finding could be caused by the way the listeners link aspects of the scene to language. While the depicted action is mediated by its referring linguistic expression (the verb), matching the emotional valence of a preceding prime face to the target character's facial expression and to the valence of the adverb is arguably more complex. In our view, the greater complexity arises because, first of all, the listener must infer the valence of the emotional prime face, since no emotion labels are provided. Keeping the inferred emotion in memory, s/he then inspects the target scene and starts to interpret it in relation to the unfolding OVS sentence. Only when the valence of the emotional sentence becomes clear (during the verb and adverb regions), could the listener reactivate the previously seen emotional face and link the valence of the face to the emotional adverb and the happy smile of the target agent. In Experiment 2, this prime face-language connection enabled anticipatory looks to the target agent. We propose that effects of the non-referential cue arguably involve more processing steps than the effects of the referential cue on real-time assignment of thematic roles (the verb mediates the action and the associated agent that can fill a thematic role slot).Alternatively, the effects of the emotional primes were less pervasive than of the actions because of differences in presentation. While the depicted action was present during sentence presentation, the emotional facial expression was shown and then removed before the onset of the target scene and sentence. Thus, whereas the listener had access to the depicted action throughout comprehension, the emotional prime face had to be held in working memory from the end of the prime presentation until the end of the trial. The effects of the emotional prime might be less pervasive because relating visual and linguistic input is arguably easier when both are presented together than when they are presented separately. This assumption is indirectly supported by Glenberg and Robertson's  indexicaAnother reason for why the effects of the non-referential cue were less pervasive could be the different sentence structures investigated. Recall that Carminati and Knoeferle  and MünsHowever, while being less pervasive than the effects of the depicted action in Experiment 2, the emotional prime effects provide some support for the view that the valence of a prime face can also facilitate the real-time assignment of thematic roles in non-canonical German OVS sentences.natural (but not the smiley) emotional facial expressions. One possible reason for that could lie in the changes in emotional prime presentation between Experiments 1 and 2. While the happy utterance-congruent smiley (Experiment 1) contrasted with a  static red star, the valence congruence manipulation in Experiment 2 was achieved by contrasting a woman's happy (utterance-congruent) and sad (incongruent) facial expressions. Hence, we contrasted an emotional with a non-emotional prime in Experiment 1 but one woman's facial expression of contrasting valences in Experiment 2. In order to strengthen our claim that only the naturalness of the emotional prime face elicited an effect in Experiment 2 but not 1, the happy smiley prime in Experiment 1 would have to be contrasted directly with a sad smiley prime instead of a red star in a follow-up study. Additionally, using valence-contrasting faces in Experiment 2 may have increased the overall awareness of emotions in the study and boosted prime effects compared to Experiment 1. This might additionally be the case because in Experiment 2, the focus on emotions was further increased by occasionally asking participants to comment on the characters' feelings and to recall the valence of the prime face.The analyses also revealed significant effects of the dynamic However, it could also be argued that the longer exposure duration of the natural facial prime  caused its better integration into sentence processing. A longer exposure to the emotional expression might have led to more in-depth processing of the emotional content although the studies that have varied stimulus duration (from as short as 50 ms to 10 s) of emotional facial expressions found no effect of the duration manipulation on emotion perception and recognition for happy faces  prime face into the real-time processing of the OVS sentence. The target sentence was spoken by a female voice, and the gender match with the face prime might have encouraged participants to more readily perceive the happy-looking woman as the speaker than a smiley. That this is likely the case is also supported by “Theory of Mind” assumptions  during the verb-adverb and long region when having been primed with a positive (vs. negative) speaker face. We did not predict this reversal but identified possible reasons To recap, in Experiment 2, the visual scene that participants saw while listening to the positively valenced sentence contained the happy-looking target agent alongside a neutral-looking patient and a slightly grumpy-looking competitor character. In Experiment 3, we omitted the neutral-looking patient and increased the valence of both the target agent's and the competitor character's emotional facial expressions. This means that the slightly grumpy-looking competitor character was given a really grumpy face  while the happy-looking target agent's face was made even happier looking . That is, in Experiment 3, the emotional valence of the target scene was foregrounded and the valence highlighted.We assume that in both experiments, the congruent happy speaker prime face raised expectations toward an upcoming happy event. In Experiment 2, following this congruent prime face, and with the expectations toward a positive event in mind, participants faced a scene in which the emotionally most salient character is the happy-looking target agent. The slightly grumpy-looking character might not have been as emotionally salient and might hence not have violated the primed positive expectations. Hearing the verb and adverb describing the happy event in the scene, participants quickly used their expectations and the congruent positively valenced linguistic input to direct their fixations toward the also happy-looking target agent. When that agent was named, their expectation that this is indeed the character carrying out the positive action is confirmed.In contrast, in Experiment 3, following the congruent prime face, participants encounter a scene featuring a very grumpy-looking and a very happy-looking character. Both characters' facial expressions might be salient, but it could be that the really grumpy-looking character drew more attention than the really happy-looking character. This idea is supported by evidence suggesting that negative emotional facial expressions and events draw more attention and are better memorized than positive faces and events [at least for younger adults . Rothermund et al. , for exavia pairs of playing cards, which either moved closer together or farther apart. The nouns referring to the agent and patient in the following German target sentence were printed each on one of the two cards. The card movements primed the written target sentence either expressing a friendly  or an unfriendly  relationship between the agent and patient, such as Sandra met her aunt cheerfully/grumpily at the health center (translation). In Experiment 1, in these sentences, the adverb expressing the social relation between the protagonists  appeared after the second noun . The results revealed shorter reading times in the adverb region when the cards moved close together and the sentence expressed a friendly relationship between protagonists compared to when prime card movement and target sentence did not match in social meaning. Hence, participants experienced a facilitation effect in sentence reading. However, in Experiment 2, Guerra and Knoeferle (Sandra met cheerfully/grumpily her aunt). The results revealed longer reading times for matching vs. mismatching social meaning. Thus, participants experienced an interference effect. The authors argue that the shift from facilitation to interference is due to an increased competition between two strongly activated representations of the same conceptual representation: When the previously seen playing cards prime the activation of the concept of un/friendliness and the adverb is encountered late after the agent–patient relationship has been established, sentence processing is facilitated. However, when the adverb is encountered before the second noun phrase, the concept of un/friendliness is activated earlier and competes in activation with the same concept activated by the matching playing cards. In the latter case, sentence processing took longer.A similar interference effect has recently been reported for real-time language processing , they again found facilitation effects. Hence, the activation time between two similar conceptual representations seems to be crucial for the directionality of the effects regarding real-time language comprehension.This reversal might be similar to the reversed priming effect in the present Experiments 2 and 3: whereas we see increased fixations to the happy-looking target agent in the adverb region in Experiment 2, we see increased fixations to the grumpy-looking competitor agent in the adverb region in Experiment 3. In Experiment 3, in contrast to Experiment 2, we not only increased the salience of the target agent and the competitor agent's opposing emotionally valenced facial expressions, but also we decreased the preview time of the target scene from 2,000 to 500 ms. Just like in Guerra and Knoeferle , two conTaken together, the reversal of the result pattern that we see in Experiment 3 could (a) be due to the competitor character's highlighted negative facial expression, which violated the primed positive expectations and the positively valenced sentence. This explanation is also in line with studies showing that semantically inconsistent objects in scenes attract more attention  than consistent objects based on the viewer's expectations and world knowledge about what a particular scene usually contains [e.g., a cocktail glass vs. a microscope in a kitchen scene , no effects of the prime face on sentence verification accuracy emerged. Experiment 3's null effect in the sentence verification accuracy plus the reversed result pattern in the eye-tracking data calls our interpretation that the positive prime face facilitates real-time assignment of thematic roles (Experiment 2) into question.What the eye-tracking data does tell us though is that the linguistic input together with the emotional facial expression modulates attention to the characters in the scene, since the first effects emerged after the NP1 region, triggered by the verb and the adverb. Whether these effects are, however, specific to the assignment of thematic roles is less clear. The reversal of the result pattern in Experiment 3 could simply be due to the enhanced negative facial expression of the competitor character in the scene (see Section The Reversed Priming Effect). It could mean that the assignment of thematic roles can be facilitated by using the expectations based on the face in real time, if the visual context does not portray strongly opposing valence information  and/or if similar conceptual representations do not compete for activation in temporal proximity. The expectations to what should come next might be violated by seeing a valence-incongruent character on the screen next to a valence-congruent character. That contrast might have drawn listeners' attention to the valence mismatching (vs. matching) character when the positive verb-adverb region confirmed the expectations derived from the positive prime face  cues, i.e., emotional facial expressions and depicted actions, against each other. Interestingly, Experiment 3 showed that the exact nature of the situation in which emotional facial cues are embedded seems to influence the directionality of the effects. Clearly, more research is needed, which explores the effects of referential and non-referential  cues and their relation to each other in real-time language processing. Our studies represent a first step in going beyond the integration of referential cues in language comprehension and suggest that subtler and crucially also social cues, such as the emotional facial expression of a speaker, can affect real-time language comprehension. The reported findings pave the way for extant real-time language processing accounts to include the effects of non-referential  visual cues, their modulation by the naturalness of facial expressions, and their relative effect differences compared with referential (action) cues.Our results provide some support for the view that a natural facial expression of emotions elicited a priming effect on the interpretation of emotionally valenced OVS sentences (in contrast to a schematic smiley). Crucially, our studies show that different kinds of information in a visual context and distinct language-world relations yield distinct visual context effects on language processing. As one reviewer pointed out, it is, of course, also possible to establish different degrees of referentiality by using different linguistic cues, i.e., the emotion verb The raw data supporting the conclusions of this article can be made available upon request to the first author.The studies involving human participants were reviewed and approved by University of Bielefeld ethics board (Vote 2013-007) and ethics board of the German association for linguistics . The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.PK and KM designed the experiments and wrote the manuscript. KM conducted the studies and analyzed the data. The data are available upon request. Analyses of the data from Experiments 1 and 2 have previously been published in Münster  and in pThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Adolescence is a developmental period crucial for the maturation of higher-order cognitive functions. Indeed, adolescence deficits in executive functions are strong predictors of increased vulnerability to several mental disabilities later in life. Here, we tested adolescent mice in a fully-automated attentional set-shifting task equivalent to the humans’ Wisconsin Card Sorting Test (WCST) and the Cambridge Neuropsychological Test Automated Battery Intra-/Extra-Dimensional set-shift task (ID/ED). Compared to an adult, adolescent mice required more time to complete the task (≈16 days), and a higher percentage failed to finish the entire task. Nevertheless, adolescent mice completing this demanding task showed an increased effort in solving the extradimensional shift stage (EDS) compared to previous stages. Moreover, we found that this paradigm can be used to detect early cognitive dysfunctions in adolescent genetically modified mice. Thus, this automatic paradigm provides a further tool to assess attentional control in adolescent mice, and the development of dysfunctional executive functions from adolescence to adulthood. Executive functions include the ability to monitor and flexibly change behavior when facing novel situations. These abilities develop from early childhood and mature during early adolescence and young adulthood  and strictly adhere to the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. Dysbindin-1 null mutant (DYS −/−), their heterozygous (DYS +/−) and wildtype (DYS +/+ DYS +/+) littermates on a C57BL/6J genetic background were used . On the second day, mice were placed for 40 min in the Operon chambers with only neutral stimuli for all different dimensions and were trained to move from one chamber to the other at the end of each trial (Habituation phase 2). A session was started by placing the mouse in one chamber with neutral stimuli cues. A free pellet was delivered and a trial began when the subject entered the food magazine. This dropped the door to give the mouse access to the other chamber. Infrared photobeams flanking the door between the two chambers detected the movements of the animal so that the door was closed when the mouse moved from one chamber to the other. A nose poke into any of the nose-poke holes resulted in a pellet delivery into the food magazine. Infrared photobeams inside the food magazine detected the mouse while it retrieved the food reward and dropped the door to give the mouse access to the other chamber for the next trial. On the 3rd day (Habituation phase 3), the mice were trained to perform two simple discriminations  to a criterion of eight correct responses out of 10 consecutive trials so that they were familiar with the stimulus dimensions. These exemplar pairs were not used again during the test. A session started by placing the mouse in one chamber with neutral stimuli, while in the other chamber the stimuli cues were turned on or placed in position. Then, the door was dropped to give the mouse access to the other chamber with the stimuli cues on and the mouse had to choose the nose-poke hole in which it was presented the correct stimulus . Nose poking into the correct hole resulted in a pellet delivery and, when the mouse entered the food magazine, the door was dropped to give the mouse access to the other chamber for the next trial. Nose poking in the incorrect hole was not rewarded and the house light was turned on for 5 s. Following these 5 s with the house light on, the door was dropped to give access to the other chamber for the next trial. The first 10 trials of each stage were exploratory trials: if the mouse selected the incorrect hole, an error was recorded but the trial was not terminated until the mouse poked also in the correct hole. In subsequent trials, if the mouse poked in the incorrect hole, an error was recorded, the trial was terminated, and all dimensional stimuli were turned off. The apparatus was wiped down with 70% alcohol at the end of each mouse session.We employed a ‘two-dimensional’ ID/ED paradigm as in previous studies in humans, non-human primates, and rodents  throughout the manuscript. One-way analyses of variance (ANOVAs) with the different stages  as a within-subject factor was used to examine the performance in the tasl . In the experiment using genetically modified mice, two-way ANOVAs with genotype  as a between-subjects factor and the different stages  as a within- subject factor was used to examine the number of trials necessary to reach the criteria, timing needed to complete each stage and the latency to respond. Mice were weaned at PND28, single-housed, and food-restricted to start the test from PND31 . We testAdult mice were food-restricted throughout the experiment in order to maintain about 90% of their baseline free-feeding body weight. In adolescent mice we kept a less strict food restriction regimen of about 95% or less of their initial baseline , to alloOut of the 13 adolescent wild-type mice tested, eight were able to complete the entire task , with anF8,63 = 3.90; p = 0.0009), as they needed more trials to complete the EDS stage compared to SD, CD, and IDR  and adolescent  mice a decreasing duration, consistent with a better performance throughout the task , stage , or their interaction , was evident for the days needed to reach the criterion . During the task, we found a significant stage x genotype interaction for the trials . In particular, mice improved their speed to respond at the IDS2 stage compared with IDS in a genotype-independent way  and strictly adhere to the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health.MC and FP designed the study. MC and DS performed the behavioral tests and the statistical analyses. All authors contributed to discussions about the results and critically revised the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.