Fault detection and exclusion are essential to ensure the integrity and reliability of the tightly coupled global navigation satellite system (GNSS)/inertial navigation system (INS) integrated navigation system. A fault detection and system reconfiguration scheme based on generative adversarial networks (GAN-FDSR) for tightly coupled systems is proposed in this paper. The chaotic characteristics of pseudo-range data are analyzed, and the raw data are reconstructed in phase space to improve the learning ability of the models for non-linearity. The trained model is used to calculate generation and discrimination scores to construct fault detection functions and detection thresholds while retaining the generated data for subsequent system reconfiguration. The influence of satellites on positioning accuracy of the system under different environments is discussed, and the system reconfiguration scheme is dynamically selected by calculating the relative differential precision of positioning (RDPOP) of the faulty satellites. Simulation experiments are conducted using the field test data to assess fault detection performance and positioning accuracy. The results show that the proposed method greatly improves the detection sensitivity of the system for small-amplitude faults and gradual faults, and effectively reduces the positioning error during faults. The global navigation satellite system (GNSS)/inertial navigation system (INS) integrated system compensates well for the deficiencies of a single navigation system by fusing the information of GNSS and INS , so as tData fusion in the GNSS/INS integrated system is generally implemented using Kalman filtering algorithms , such asClassical fault detection methods include the residual chi-square tests and the state chi-square tests, both of which are based on the Kalman filter . They arWith the substantial progress in artificial intelligence algorithms in recent years, neural networks are quite valuable in the field of fault detection . With feIn recent years, generative adversarial networks (GAN) have achieved great success not only in image processing but also in time-domain sequence generation ,27,28,29This paper is organized as follows. In In the tightly coupled GNSS/INS integration model, the INS module solves the navigation parameters separately, and then performs integrated filtering with the GNSS measurements, and the obtained estimated error is used to correct the INS output. The specific flow chart is shown in Tightly coupled GNSS/INS integration contains two parts: the state model and the measurement model. The state model consists of the error state equations of INS and GNSS, which is usually expressed as:The state vector in the filter is given by:The measurement model can be written as:Assuming a discrete-time process, the state equation and measurement equation can be rewritten as follows:State update in extended Kalman filtering consists of state estimation and one-step prediction of the covariance matrix, which can be given as follows:The measurement update in the filter is given by:There are many factors that affect time series analysis, especially in dynamical systems where the dynamical equations of these factors are often nonlinear and more likely to be chaotic. If a sequence shows chaotic properties, reconstructing it in phase space is an important method to study the state of a dynamical system. The essence of this approach is to transform the extension of the time series into the interpolation of phase space. Based on the Takens’ embedding theorem , the optThe time delay and the embedding dimension are the keys to phase space reconstruc-tion. However, there are no uniform selection criteria . In thisHere, Next, we take the data of the 8th satellite as an example to analyze the chaotic characteristics of The mutual information method is a well-established method for determining the delay time which can describe the nonlinearity of the sequence and maximize the amount of information contained in the time series.We expand the one-dimensional time series Using the CAO method to find the embedding dimension enables the reconstructed time series to be free of information folding in the phase space, which is widely used in chaotic sequence analysis. The algorithm steps are as follows.Starting from a smaller embedding dimension The average of all ratios in We then define When The maximum Lyapunov exponent is an important index to judge whether the signal has chaotic characteristics. If the Lyapunov exponent is greater than 0, it means that no matter how small the initial distance between the two trajectories is in the phase space of the system, the difference will increase exponentially with time and eventually chaos will emerge. The steps for calculating the Lyapunov exponent are as follows:1.Perform a fast Fourier transform (FFT) on the time series to obtain the average period 2.Reconstruct 3.Find the closest point 4.Calculate the distance between each 5.Calculate the average of all The left part of In adversarial training, we consider the sequences of the training set to be normal, while the pseudo-sequences produced by the generator are abnormal. Before the training, the dataset needs to be partitioned into multiple sub-sequences to achieve better training results. We partition Feed random sequences generated from random space into the generator to generate pseudo-sequences.Pseudo-sequences and original sequences are inputted to the discriminator for discriminating.Optimize the parameters of the discriminator.Optimize the parameters of the generator.Record the parameters of the discriminator and generator in the current iteration after completing the iterative training.After sufficient iterations of training, the pseudo-sequence is extremely similar to the original sequence, and the discriminator is sufficiently sensitive to anomalous sequences, although it is difficult to distinguish the pseudo-sequence from the original sequence. Therefore, the fault detection function consists of two parts: the generation score and the discrimination score.Supposing that the system obtains the pseudo-range at the moment The discriminator score can be obtained from After sufficient iterations, the The fault detection function for 1.Calculate the generation error using the pseudo-sequences and the original sequences: 2.3.The dispersion degree of the generation error can be given as:The classification accuracy If the navigation system is fault-free, then there is a null hypothesis When the observation redundancy is high, isolating fault measurements introduces small positioning errors because the system has high integrated filtering accuracy. However, when the satellite configuration is poor or the number of visible satellites is low, isolating fault observations reduces the available information, which leads to a rapid decrease in filtering accuracy with increasing fault duration, and eventually seriously affects the accuracy and reliability of the whole system.In practical navigation applications such as UAV and vehicle navigation, the system needs to be able to adjust the reconfiguration scheme dynamically when the satellite observation environment becomes unstable due to factors such as building block and electromagnetic interference. The influence on the integrated filtering is investigated by calculating the RDPOP of the faulty satellite. The formula is as follows:RDPOP reflects the decrease in positioning accuracy after isolating a satellite. Therefore, a system reconfiguration scheme can be constructed based on RDPOP as follows:The specific process of the GAN-based fault detection and system reconfiguration method is as follows.①Preprocess raw pseudo-range data.②The pre-processed data is fed into a trained GAN model to calculate the detection score. The system is considered faulty and requires system reconfiguration if the score is greater than the detection threshold ③Calculate the RDPOP value of the faulty satellite. If RDPOP is greater than ④Obtain the navigation solution of the tightly coupled system by correcting the INS output with the error estimation from the integrated filtering.The architecture of GAN-FDSR is shown in The actual data is collected by a vehicular integrated navigation system which consists of a vehicle, two GNSS antennas, and a POS320 inertial navigation device. The inertial sensor specifications of the POS320 are listed in In order to analyze the RDPOP of satellites under different environments and the influence on positioning accuracy, four groups of satellite observation environments provided in The RDPOP of the faulty satellite in each environment is shown in In In order to verify the advantages of the method proposed in this paper, a fault is added to the measurement of G7 during 300–360 s. The configuration of the satellites and the RDPOP of G7 are shown in The types of faults in the integrated navigation can be roughly divided into large-amplitude faults, small-amplitude faults and gradual faults. Large-amplitude faults are simple to detect due to rapid and large changes, whereas small-amplitude faults and gradual faults are a problem in fault detection due to their small initial amplitude. To test the GAN-FDSR fault detection performance, five fault types are set which contain two step faults and three gradual faults. The specific fault parameters are shown in In addition to fault detection performance, positioning accuracy is another critical metric in navigation. In Considering that there will be a certain amount of error even if the system is fault-free, In this paper, a GAN-based fault detection and system reconfiguration method for a tightly coupled GNSS/INS integrated system is proposed. This method greatly improves the fault detection performance and positioning accuracy, and helps to improve the integrity and reliability of the system. A novel fault detection method is designed based on the generator and discriminator of GAN, which departs from the traditional method that using residuals for fault detection. We investigated the feasibility of chaos theory for the processing of pseudo-range data to improve the learning efficiency of the model for nonlinear characteristics through phase space reconstruction. We also analyzed the relationship between RDPOP and positioning accuracy under different observation environments to develop a dynamic system reconfiguration scheme. Finally, several experiments were conducted to assess fault detection performance and positioning accuracy using measured data. The results show that: (a) The method shows excellent detection performance and significantly reduces detection delays and missing alarm rates for difficult small-amplitude and gradual faults. (b) The positioning error of the system during faults is reduced effectively by dynamically selecting an appropriate system reconfiguration strategy according to different environments.However, the study presented in this paper is based on the assumption that the INS always works properly, and the possibility of inertial sensor failures needs to be taken into account to improve the method in the future. In addition, the incipient fault diagnosis of the integrated navigation system also deserves further study .


It was accurate in yielding the correct legal state for the voluntary, assisted, involuntary and decline categories in 94%, 92%, 88% and 86% of the clinical case narratives, respectively. For internal reliability, a correspondence model accounted for 99.8% of the variance by which the decision paths clustered together fittingly with each of the legal states. Inter-rater reliability testing showed a moderate degree of agreement among participants on the suitable legal state . These results suggest the algorithm is valid and reliable, which warrant a subsequent randomised controlled study to investigate whether it is more effective in clinical practice than standard assessments.The challenges in assessing whether psychiatric treatment should be provided on voluntary, assisted or involuntary legal bases prompted the development of an assessment algorithm that may aid clinicians. It comprises a part that assesses the incapacity to provide informed consent to treatment, care or rehabilitation. It also captures the patient’s willingness to receive these treatments, the risk posed to the patient’s health or safety, financial interests or reputation and risks of serious harm to self or others. By following various decision paths, the algorithm yields one of four legal states: a voluntary, assisted, or involuntary state or that the proposed intervention should be declined. This study examined the predictive validity and the reliability of this algorithm. It was applied 4052 times to 135 clinical case narratives by 294 research participants. The legal states yielded by the algorithm had high statistical significance when matched with the gold standard (Chi-squared = 6963; df = 12;  Clinicians are ordinarily required to make a clinical assessment of patients with mental illness in terms of mental health legislation, especially for purposes of involuntary treatment and hospitalisation. This is required by The Principles for the Protection of Persons with Mental Illness and the Improvement of Mental Health Care, as adopted by the United Nations General Assembly in 1991 and the mental health legislation of most countries . This clBoth the clinical aspects and legal prescriptions of this assessment are rather difficult ,4. ThereTo aid clinicians in this rather difficult clinical assessment, an algorithm may improve accuracy in decisions and reduce the risk of harm . Whilst The Incapacity and Legal State Assessment Algorithm (ILSAA) comprises accordingly a part that assesses incapacity to give consent to the proposed TCR. It also captures the patient’s willingness to receive TCR, the risk posed to his or her health or safety, the risks of serious harm to self or others or the financial interests or reputation of the patient. Through various decision paths, the ILSAA yields one of four possible legal states as being suitable: voluntary, assisted, involuntary or that TCR is declined. The ILSAA is available as The ILSAA was applied 4052 times to 135 clinical case narratives by 317 research participants. Its predictive validity was tested by comparing the legal states as yielded by the ILSAA assessments, with the gold standard for each clinical case narrative. This included the potential influence of clinical features on the accuracy of the ILSAA. For internal reliability testing, the four legal states yielded by the ILSAA were tested for an association with the ILSAA’s decision paths. Moreover, the ILSAA was examined for internal consistency among its decision paths. For inter-rater reliability, consistency between participants was examined for the legal states yielded by the ILSAA and its decision paths.From the population who are meant to use the algorithm, two groups were conveniently sampled: psychiatrist-in-training who were already registered health care practitioners as designated by the MHCA and general physicians-in-training who would be qualified as health care practitioners in the subsequent year or two. Unlike some countries, all psychiatrists-in-training, called registrars in psychiatry, first had to complete training as general physicians and be professionally registered with the Health Professions Council of South Africa as medical practitioners. They were all enrolled in the postgraduate degree programme in psychiatry at the University of Pretoria, South Africa, and appointed for executing clinical duties in a specialist clinical internship post at a large psychiatric hospital. The general physicians-in-training were enrolled at the same university and were all within 10 to 20 months of completing a six-year medical degree .The set of clinical case narratives on which the ILSAA was applied captures a variety of potential clinical presentations, various symptom permutations, subjective intensity in emotional experience and suicide risk indicators . The setThe set of clinical case narrative presents various symptom permutations that include features of mood disorders, cognitive symptoms, psychotic symptoms, the extent and duration of symptoms, the intensity and qualities of afflicted emotions and what the experiences were about. Some narratives relate cases of incongruence between the patient’s account of severity and that of others  and different points of view on the suicide risk.The clinical case narratives contain features related to suicidality (54% of cases), cognitive impairment (35% of cases), psychotic symptoms (27% of cases), incongruence between the severity of symptoms as evaluated by the patient and others (18% of cases) and incongruence in the evaluation of suicide risk (24% of cases). The features related to suicidality include a family history of completed suicide, past or recent suicide attempts, past or current suicidal thoughts, suicide planning and current non-suicidal self-injurious behaviour.Each clinical case narrative provides information that is required for assessing incapacity owing to mental illness, whether the person is willing or unwilling to receive the proposed CTR, the health or safety of the person and/or that of other people, potential or actual serious harm to himself or herself and/or other people and, when pertinent to the circumstances, the person’s financial interests, dignity or reputation.The clinical case narratives were purposively developed for the training of physicians-in-training and mental health practitioners in applying the MHCA. An example is available in The variables examined in the study were the four legal states yielded by the ILSAA and the gold standard legal state for each clinical case narrative. The legal states were whether the MHCU should receive voluntary, assisted or involuntary TCR. The fourth category was whether mental health TCR should be declined when it was not clinically indicated or not a mental health service priority.Further variables were the 56 decision paths of the ILSAA that could be followed through 36 potential decision points, resulting in one of the four legal states. There were 12 decision paths for the voluntary, 9 for the assisted, 20 for the involuntary and 15 for the declined legal state categories.The clinical features that were examined as variables were psychotic symptoms, cognitive impairment, suicidality, incongruence between the accounts of the patient and that of others regarding the severity of the patient’s condition and incongruence between the accounts of the patient and others on the suicide risk.Three hundred general physicians-in-training and 17 of a potential 20 psychiatrists-in-training (85%) participated in training sessions during February and March 2020 on the MHCA’s requirements and the use of the algorithm. The sessions entailed an introductory lecture on the MHCA and demonstration of the algorithm by applying it interactively to four example case narratives (that were not used in the study). Thereafter, each trainee was requested to apply the algorithm to a set of 15 randomly selected clinical case narratives that was randomly assigned to each trainee. The trainees marked the suitable decision path and legal state for each of the clinical cases assigned to them. Some trainees completed fewer than 15 cases owing to the time constraints of these training sessions.The trainees who participated in the training sessions were invited to participate in this ethically approved study. Only the data of trainees who provided written informed consent to participation in the study were then collated for analyses. Twenty-three of the general physicians-in-training (7.7%) in the training sessions and three of 20 psychiatrists-in-training (15%) declined the invitation to participate in the study.The predictive validity of the algorithm was examined by calculating the goodness-of-fit between the legal states yielded by the ILSAA and the gold standard legal states, using the chi-squared test and standardised residuals. Moreover, the predictive accuracy, sensitivity, specificity, precision rate or positive predictive value (PPV), the negative predictive value (NPV), the miss rate or false negative (FN) rate and the fall-out or false positive (FP) rate were calculated. Since multiple participants  rather than a singular test contributed to each case narrative’s evaluation as true or false positive and true or false negative, all the ILSAA applications on the same case narrative were calculated as a fraction of one. The number of true positives (TP) were calculated as the sum of the fractions for all case narratives. For example, 38 of 41 applications of the algorithm on the case narrative labelled FeCo correctly identified the legal state as involuntary. This 38/41 fraction (or 0.927) was added to the fractions calculated in the same way for all the other case narratives in the involuntary legal state category, thus deriving a composite number of TPs for the involuntary legal state category. The same was performed for all the legal states in calculating true negative (TN), FP and FN values. The composite fractions were rounded to obtain integers as is standard practice for expressing TP, TN, FP and FN values.Whilst predictive accuracy concerns all instances of TPs and TNs using the legal states as points of reference, the case-specific accuracy calculations took each case narrative as a point of reference. The case-specific accuracy is the proportion of ILSAA applications that was accurate for a specific case narrative. For example, when 30 of 40 applications of the ILSAA were the same as the gold standard for a particular case, the case-specific accuracy was 75%. The mean and median for case-specific accuracies were calculated. The mean of the case-specific accuracies is an alternative method of expressing the ratio between TPs and the total number of case narratives. Pearson’s correlations were calculated between the case-specific accuracies and the clinical variables.For internal reliability testing, Pearson’s chi-squared test was used to examine the association between the legal states and the decision paths. In addition, a correspondence analysis was performed, which was modelled using the symmetric normalisation of the legal states and the decision paths along two dimensions.For inter-rater reliability, the extent of agreement between the participants in applying the ILSAA was calculated using Krippendorff’s alpha coefficient, which provides for a categorical metric across variable numbers of applications of the ILSAA on each clinical case narrative and that each participant could apply the ILSAA only to some of the case narratives. Potential Krippendorff’s alpha values range from −1 to 1, that is, from perfect systematic disagreement to perfect systematic agreement, with 0 indicating the absence of both agreement and systematic disagreement. Bootstrapped sampling with 95% confidence intervals was performed on the Krippendorff’s alpha calculations, with the advantage of adjusting for data not following a normal distribution.The probability threshold for a type I error was set at 5%. SPSS version 27 was used for the analyses.The 294 participants comprised 277 general physicians-in-training and 17 psychiatrists-in-training. These groups, respectively, represent 92.2% and 85% of the trainees who had been requested to participate in the study. The participants applied the ILSAA 4,052 times. Six of these applications had no legal state outcome recorded, and for fifty-five (1.4%), the decision path was marked ambiguously. For example, a participant made corrections without clearly indicating some of the decision points.p < 0.001), and this was the case similarly for the general physicians-in-training  and the psychiatrist-in-training . The covariance of the legal states yielded by the ILSAA and the gold standards for each case narrative was indicated by the large, positive standardised residuals for each of the four legal states, shown in Supporting the predictive validity of the algorithm, the Pearson’s chi-squared test value for the association between the algorithm-derived assessments and the gold standard legal states was highly statistically significant  when compared to each of the other legal state outcomes. The value closest to zero  is nonetheless of a magnitude that indicates independent variance .The True Positive, False Positive, True Negative and False Negative values are shown in The median of the case-specific accuracies was 85.7%. The mean of the case-specific accuracies for all the case narratives was 79.9%. The 95% confidence interval for the case-specific accuracies ranged from 60.8% to 99%. As shown in p < 0.001). The correspondence analysis yielded a Cronbach’s alpha value of 0.998, which accounted for 99.801% of the variance and an Eigenvalue of 1.996. The correspondence model was highly significant statistically . In this model, using symmetric normalisation, each legal state and the decision paths were scored on two dimensions. The scores are shown in For internal reliability testing, the association between the legal states yielded by the ILSAA and its decision paths was highly significant statistically  by constructing the normal distribution that pertains to the data by resampling the data 1000 times.The inter-rater reliability of the algorithm is reflected in the Krippendorff’s alpha values shown in The results indicate that the Incapacity and Legal State Assessment Algorithm is valid in that it performed as it was supposed to. In 294 participants applying the algorithm 4052 times on a set of 135 clinical case narratives, it yielded legal states that matched excellently with the gold standard legal states. The algorithm was accurate in yielding the correct legal state for the voluntary, assisted, involuntary and decline categories in, respectively, 94%, 92%, 88% and 86% of the clinical case narratives. Its specificity ranged from 89% to 96%, and its sensitivity ranged between 82% to 89% except for a 59% sensitivity in predicting the decline category.Results of the reliability testing indicate that the algorithm performed consistently for its decision paths and among those who applied of the algorithm. Internal consistency was found in a significant association between the legal states and the decision paths. Moreover, a correspondence analysis that accounted for 99.8% of the variance showed that the decision paths clustered clearly together for each of the legal states along two dimensions. Inter-rater reliability testing of the algorithm showed a moderate to strong degree of agreement among the participants for the legal states and modest agreement for the decision paths.Considering the challenging, difficult and non-exact nature of the decisions captured by the algorithm ,5,7,8, tThe challenging, difficult and non-exact nature of the decisions captured by the algorithm also limited the reliability results. Whilst the internal consistency was excellent by common standards, the inter-rater reliability results reflected the difficult nature of the decisions. The modest agreement for the decision paths was mitigated by a moderate to strong degree of agreement for the legal states. This makes sense considering that several algorithm paths lead to the same legal state. This limited result should be expected in that differences in emphasis are likely, for example, regarding which aspect is most striking when incapacity to give informed consent cuts across various actions  . WhetherBeing the first validation study of an algorithm that assesses whether psychiatric treatment should be provided on voluntary, assisted or involuntary legal basis, results may at best be compared with the performance of dissimilar diagnostic assessment instruments. For example, the accuracy, specificity and sensitivity of the ILSAA compare favourably with the Structured Clinical Interview for DSM-5-Clinician Version (SCID-5-CV) , algoritThere are other limitations pertaining to the results, which may be addressed in further research. That the algorithm is valid and reliable does not mean that it is necessarily more effective than not using it at all. A subsequent study on the algorithm’s effectivity may build on the validity and reliability results, and compare it with standard assessments. To this end, a randomised controlled design will control for common factors that may influence the algorithm’s performance.Using clinical case narratives in this study was advantageous in various respects but the use of these only partially reflects the properties of the algorithm as these would be when using the algorithm among patients. The clinical case narratives captured a large variety of permutations in which clinical features may present and it captured ways in which patients may be incapable of consenting to interventions. For validity and reliability testing, it was important that the algorithm would be tested for having sufficient reach across this variety of presentations, whereas a study among patients would need many more participants and have taken many years so as to include most of the permutations in clinical presentations. Another advantage was that the clinical case narrative presented all the information required in the assessment. This meant that the availability of information was not an issue in addition to the challenges and difficulties in applying the algorithm, as it would likely be when applying the algorithm among patients. Although the credibility and authenticity of clinical case narratives have been carefully nurtured, subsequent studies that test the algorithm among patients are nonetheless recommended.Further limitations to the results are that the physician-in-training participants lacked in clinical experience and used the algorithm as individuals. Although the results for psychiatrists-in-training and the general physicians-in-training appeared to be similar, the small number of psychiatrist-in-training who were more experienced participants did not allow for statistical comparisons. One may hypothesise, nonetheless, that the algorithm would yield stronger results in subsequent studies when used by more experienced clinicians. Furthermore, the trainees applied the algorithm as individuals. In contrast, the MHCA requires that at least two clinicians make the assessment for the involuntary and assisted legal states. A subsequent study may examine whether the conjoint application of the algorithm would yield stronger results.The algorithm is meant to assist and enable clinicians in making challenging, difficult and non-exact assessments of the most suitable legal state for providing psychiatric treatments including hospitalisation. However, the contents of the algorithm were derived from requirements of MHCA in South Africa , and it An algorithm may enable clinicians in assessing patients with mental illness in terms of mental health legislation, especially for the purposes of involuntary treatment and hospitalisation. An exemplar of such is the Incapacity and Legal State Assessment Algorithm, which in this study was found to be valid and reliable in identifying whether psychiatric treatment, care or rehabilitation should be provided on a voluntary, assisted or involuntary basis or be declined by the requirements of the Mental Health Care Act in South Africa. Supported by its validity and reliability, the algorithm may be used in practice at the clinical coalface where the assessments have proven to be challenging ,4,7. It


The development of an extrapyramidal syndrome (EPS) is assumed to be a potential and important consequence of organophosphate poisoning (OP). Even though its causal relationship is firmly established, the information available in the literature regarding the orientation to be given is scarce, and its approach remains shrouded in a significant degree of uncertainty. Catatonia, as a neuropsychiatric condition, may present a marked overlap with the set of extrapyramidal symptoms developed after OP. Does the overlap between the symptoms seen in catatonia and in EPS make differential diagnosis fundamental or does it have no relevance in relation to the approach to be established?To discuss the therapeutic approach to be implemented in the extrapyramidal symptoms resulting from OP and reflect on the overlap between catatonia and EPS.Presentation of a clinical case and review of the literature.A 50-year-old woman with major depressive disorder developed a condition marked by exuberant extrapyramidal symptoms 3 weeks after OP. Significant stiffness, tremor, dysphagia and facial hypomimia were some of the symptoms observed. Therapy was started with amantadine 100mg daily, with complete resolution of the symptoms after 5 days. Follow-up revealed reversal of extrapyramidal symptoms, in the absence of any neuroimaging changes or any other neuropsychiatric manifestations.The possible overlap between catatonia and EPS is remarkable. The two conditions, regardless of their differentiation, may benefit from an identical approach using dopaminergic drugs. The use of amantadine, even in low doses, may be an option in the rapid reversal of extrapyramidal symptoms resulting from OP.No significant relationships.


Preservice teachers' preparedness, perception, and affect toward certain technology systems influence the student acquisition of science knowledge, process skills, teaching innovation, and willingness to use technology in their classroom. The purpose of this study was to explore teachers' affective responses to a virtual reality-enabled scientific experiment (VaSE) system. Fifty-one preservice teachers majoring in educational technology participated in the study. They were divided into two groups, and their reactions were measured separately on two occasions. The first occasion used a standard system following the principle of Donald Norman's affective design model (ADM). The VaSE system was then revised with a strict version of ADM before the participants' reactions were measured for a second time. The positive and negative affect scale (PANAS) was utilized for affective state evaluation. Semi-structured interviews that focused on affective experiences were organized using an ADM framework and conducted immediately after the participants used VaSE. The results indicated that the positive affect experienced by the preservice teachers was significantly enhanced, and the negative affect was significantly weakened. Academic level, gender, and prior experience were important random effect factors that impacted the affective experience. It was also revealed that participants were more likely to be affected by immersion and interactivity in terms of enhancing positive affect and were more likely to be affected by behavioral layer elements in terms of weakening negative affect. A conclusion has been drawn to provide theoretical and practical suggestions for training preservice teachers in ways that improve their ability to integrate technology into the classroom. A science-based curriculum encompasses a range of disciplines, including physics, chemistry, life science, etc. The goals of a science-based curriculum center on helping students acquire scientific knowledge and cultivate their critical thinking skills and practical abilities  can be used to display scientific experimental scenarios in science education. Lamb et al.  investigVR-enabled scientific experiments (VaSE) are grounded in a computer-generated simulation environment that embodies abstract scientific concepts, presents complex information in an easy-to-understand manner, and displays experimental phenomena that cannot be directly observed . Scholars have claimed that barriers to technology integration in class include teaching beliefs and attitudes toward using technology, but they have also suggested that research should pay special attention to the affective aspects of attitudes  Do preservice teachers experience a predominantly positive or negative affect while using VaSE?(2) Is the affective experience of preservice teachers significantly improved after the use of VaSE?(3) What affective design elements influence the experiences of preservice teachers?The VaSE system used in the current study was a self-developed VR application built around the theme Exploring the Relationship between Currents in Series Circuit see , which c*1200, two handle controllers, and a pair of laser positioners. The software compiling VaSE was a VR editor called VeryEngine. The VeryEngine, structured on the popular game engine Unity 3D, features Microsoft Excel-style editing functions so that it is easy to set parameters for virtual objects and define interactive behaviors between human and virtual objects.The hardware devices used for this study consisted of a group of HTC VIVI kits. Each kit included a high-performance computer with a high-definition screen, a wired head-mounted device (HMD) with a resolution of 2160Donald Norman's ADM Norman,  was usedTo examine the effect of emotional design, this study developed two versions of VaSE. The VaSE used for occasion 1 was implemented for pure functionality and did not include the affective responses of participants to the design pipeline. Participants invited for occasion 1 were encouraged to report their perceptions about factors that lead to negative affects. Because most of the participants mentioned low fidelity of scene, difficulty in component connection, and high false touch rate, corresponding improvements were made by mapping the factors to the visceral, behavioral, and reflective layers and updating the VaSE for occasion 2. The configurations of VaSE used on the two different occasions are presented in A combination of quantitative and qualitative methods was used in this experiment. In the quantitative research section, occasion 1 was a baseline assessment, and occasion 2 was an experimental assessment. The occasion-based configuration of VaSE was the independent variable, and the set of affective states of participants was the dependent variable. Participants' prior experience, gender, age, etc. were viewed as covariates. Qualitative research was conducted after participants finished the scientific experiment as a means of learning about the participants' affective experience.Participants for the study consisted of undergraduate students and postgraduate students who were majoring in education technology at our university in 2021. The participants had mastered corresponding instructional design skills and were willing to teach information technology courses in elementary and middle schools after graduation. They were identified as qualified preservice teachers for this study. Before the experiment, two research assistants conducted brief online or face-to-face interviews to ensure the legitimacy of the participants.Fifty-one participants were divided into two groups and assigned to the two measuring occasions. Twenty-seven senior undergraduates participated during the first occasion. The number of male participants was 13, and the number of female participants was 14. There were 22 participants who had prior experience using the immerse VR system, and 5 participants who reported having no such previous experience. At the end of the first occasion, we revised the VaSE system according to the strict version of ADM. Three months later, the second occasion of the study took place. A total of 24 students, including 17 undergraduates and 7 postgraduates, participated in this phase of the study. There were 10 men and 14 women. Twenty-two participants had prior experience with using immerse VR system, and two participants reported having no such previous experience.In order to account for potential differences in how well the participants remembered series circuits, the research assistant reviewed this concept and showed the participants the detailed operations of VR devices before the scientific experiment began. Each participant needed to connect circuit components and record readings through the virtual panel within 30 min. Right after they finished using the VaSE, participants filled out an affective state scale and answered a few questions about their affective experience in a semi-structured interview. Because the VaSE system was deployed in a single VR device, participants were required to participate in the experiment one at a time.The positive and negative affect scale (PANAS) developed by Watson et al.  was usedUnder the framework of Donald Norman's ADM, a semi-structured interview form centered on affected experience was developed to investigate the participants' perception of VaSE. The instrument includes 10 items. Items 1–3 correspond to the affective experience at the visceral layer and examine the sensory preferences and affective responses of participants when they are exposed to VaSE. Items 4–6 correspond to the affective experience at the behavioral layer and examine the influence of the usability, ease of use, and controllability of the VaSE system on the affective experience of the participants. Items 7–9 correspond to the affective experience of the reflective layer, which examines the participants' sense of identity and satisfaction after using the VaSE system. In the last item, the participants described the overall feeling that they experienced while using the system.To address research question 1, this study calculated the mean and standard deviation for each affective dimension. If participants have higher scores with respect to positive affect and low scores with respect to negative affect, it is more likely that they had a better affective experience while using VaSE. To answer research question 2, we stacked the data in columns because each individual has multiple measures to represent different affective states. We then used a multi-level linear model in SPSS to test the significant changes in the comprehensive affective states of the participants. The measurements for each individual were processed at level 1, and measuring occasions were processed at level 2. Level 1 estimated within-individual changes using a linear model, and level 2 estimated between-individual differences after undergoing VaSE. Academic level, prior experience, and gender were treated as random effect variables. To answer research question 3, we conducted a text analysis by categorizing the interview data and summarizing similar responses in each category.The statistics of the affective scores of participants from both occasions are shown in t = −5.104, p < 0.001), but the negative affect produced during the first occasion was significantly higher than the one produced during the second occasion . Academic grade and prior experience significantly affected the participants' positive affective experiences. Gender had no obvious influence on positive or negative affect. There was a significant interaction between academic level and prior experience and between academic level and gender. The influence of academic grades on negative affect was statistically significant, but the influence on negative affective experience was not obvious. This indicated that the affective experiences of the preservice teachers significantly improved after they used the strict version of Donald Norman's ADM.The results of the multilevel linear model are shown in The factors that influenced the positive (negative) affective experience are shown in The visceral layer that led to the positive affect on the participants mainly included strong environmental immersion, high environmental reality, and beautiful environmental presentation. The behavioral layer that caused the positive affect on participants mainly included strong system interaction, complete system functions, and realization of operations that cannot be accessible in the real world. The factors that aroused positive affect in the reflective layer mainly included novelty, no worry about the loss of experimental equipment, and a sense of accomplishment and satisfaction. In view of the responses that were measured during the first occasion, both visceral layer elements and behavioral layer elements played an important role in stimulating participants' positive affect. It can also be inferred from the frequency of reflective layer elements that the optimization of this layer can improve participants' positive affective experience.The visceral layer that caused a negative affect on participants included the low authenticity of experimental equipment, the lack of obvious experimental phenomena, and the complicated layout of the laboratory. In particular, in VaSE the wire cannot be bent, which made it more difficult to make a successful circuit connection. With respect to the behavioral layer, the factors that caused participants' negative affective experience included difficulty making a circuit connection, high false touch rate of components, complicated handle operation, and difficult control of experimental equipment. The reflective layer that caused negative affects for the participants included inconspicuous error prompts, lack of experimental help, weak conception of time, and insecurity.Many participants believed that the sense of immersion and interaction provided by the learning environment played a major role in promoting their positive affect. For example, one participant made the following statement: “The scene and the experimental apparatus are almost real. I can easily complete all the experiments, and I really have a feeling of doing them in the laboratory.” The participant seemed to have been influenced by the immersive quality of the VaSE system. In this context, the word immersion describes the way that the participant was psychologically enveloped in the experience and is related to the extent to which the system's presentation  replicates the real world. In this study, perceived immersion activated a type of psychological perception called presence, which created a sense of “being there” by means of the visible world and tangible interactions. Because the participant experienced reality, she determined that the system was usable and was able to become more engaged in the learning process.Conversely, difficulty in operating the experiment apparatus was more likely to elicit a negative affect. One participant made the following remark: “It's hard to connect the wire ends to the binding posts, and I am not sure if the node is broken again due to my other operations.” When participants failed to accomplish the tasks in the experiments, they felt unable to use VR technology and ranked their ease of interaction poorly. The negative affect was mapped to the physical perception of the usability and behavioral intentions, influencing their judgments about the value of the VR system. It also damaged their belief in the effectiveness of VaSE because a sense of frustration impeded them from completing the experimental task.The findings of this study can be summarized as follows: (1) After exposure to VaSE with Donald Norman's ADM, the positive affect that the preservice teachers experienced was significantly enhanced, and the negative affect was significantly weakened. (2) Academic level, gender, and prior experience had varying degrees of influence on affective experience. (3) Among the factors that lead to the enhancement of positive affect, participants were more likely to be affected by the immersive and interactive components of VaSE, while among the factors that lead to the weakening of negative affect, participants are more likely to be affected by behavioral layer elements.Using an optimized ADM could change the way that preservice teachers affectively experience VaSE in teacher education programs. A large number of studies support the idea that the visual design of the VR environment has a significant impact on individuals' affective social skills. This is because, for a considerable number of students, the intervention of teaching materials is mainly realized through interactive visual materials and the environment  in this study. In the model of TPCK, technological, pedagogical, and content knowledge are considered to be prerequisites for success when integrating technologies into the classroom. Because of the possible moderating effect on behavior, preservice teachers' affective responses will implicitly influence the operationalization of TPCK. In other words, preservice teachers' affective responses toward technologies may facilitate the effective implementation of these technologies in the classroom. Future work should use structural equations to model the multivariate effects on preservice teachers' affect and track their actual use in classrooms.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Southwest University. 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 identifiable images or data included in this article.TX planned and wrote the paper. LZ collected and analyzed the data. GL gave many theoretical and technical support to complete the paper. 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.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.


Detection and manipulation of radially polarized terahertz (THz) radiation is essential for many applications. A new measurement scheme is proposed for the diagnosis of radially polarized THz radiation from a longitudinal dc-biased plasma filament, by introducing a movable metal mask. The amplitude and spectrum of the radially polarized THz beam was measured with a <110>-cut ZnTe crystal, where the THz beam pattern was modulated by the mask. Based on this measurement scheme, it was demonstrated that the amplitude and spectrum of the radially polarized THz radiation from the longitudinal dc-biased filament could be manipulated by controlling the strength and the location of the dc-biased field. Radially polarized terahertz (THz) radiation is a special THz vector beam whose polarization direction is along the radial direction in the beam cross section . LongituRecently, THz radiation from laser plasmas has attracted broad interest due to its high damage threshold and ultrabroad spectral bandwidth, compared with other methods ,16,17,18In this paper, a new method is proposed for the measurement of radially polarized THz radiation from a plasma filament with a longitudinally oriented external electric field. The waveform and corresponding spectrum of the radially polarized THz pulse from a plasma filament can be distinguished and obtained by electro–optic (EO) sampling technique with a <110>-cut ZnTe crystal, by modulating the THz beam pattern with a movable metal mask. Based on this measurement scheme, it will be demonstrated that the amplitude and spectrum of the radially polarized THz radiation from a longitudinally dc-biased filament can be manipulated by control of the amplitude and the location of the external electric field, respectively. This paper is organized as follows. In zE in THz radiation from plasma filaments with an external electric field can be either radially polarized   or lineayE, at the focal plane . Thus, we could roughly determine the boundary of the THz beam pattern by scanning the metal mask across the whole THz beam profile in y direction. In the measurement, we could obtain the horizontally polarized and the vertically polarized THz electric fields at the focal plane by rotating the angles of a half-wave plate (HWP) and a ZnTe crystal in the electro–optic sampling system [d was changed from 0 to L, the horizontal and the vertical components of the linearly polarized THz signal became larger with the increase in d. For the radially polarized THz beam, however, its vertical components increased from zero to a maximum, when d changed from 0 to L/2. For d larger than L/2, the THz signals from the upper half of the radially polarized THz beam (with inversed polarization) canceled the THz signals from the lower half, leading to a decrease in total THz vertical components at the focal plane. Meanwhile, the horizontal THz components from a radially polarized THz beam remained at zero when moving the mask vertically  because the horizontal THz components from the left half and the right half of this THz beam canceled each other at the focal plane. In order to improve the accuracy of our experiment, being certain that radially polarized THz radiation had been measured, we also measured the THz radiation by moving the metal mask in the opposite direction, as shown in z = L (corresponding to upper edge of the THz beam pattern) and z = 0 (corresponding to lower edge of the THz beam pattern). In this case, d was defined as the distance between the upper edge of the THz beam pattern and the upper edge of the mask, while the horizontally polarized and the vertically polarized THz signals were defined as To determine the spatial distribution of the THz radiation from plasma filaments, we first placed the metal mask so as to completely block the THz beam pattern. Then the mask was moved upwards along the g system ,23. Here Eylower a, respecy-axis, was placed just after the silicon wafer to control the THz beam pattern that reached the detector.The experimental setup for the generation and the detection of the THz radiation from laser-induced air plasmas is sketched in y-axis). d. The signals with y-axis). As a result, the radially polarized THz radiation did not contribute to the measured horizontally polarized THz components, d, as shown in d = 50 mm in ownwards a,b, respic field . In thisd L = 50 mm) As mentioned above, not only a radially polarized THz beam, but also a linearly polarized THz beam were generated in our experiment when applying a longitudinally oriented dc-bias to the filament. This was due to a slight deviation in the direction the dc-bias with respect to the propagation direction of the laser beam, which induced a transverse component of the external electric field to the plasma filament responsible for the generation of the linearly polarized THz beam . We willd. Therefore, it can be derived that:d. In d, denoted as For the linearly polarized THz beam, the vertical THz components should have the same relation to the mask location In this way, we can obtain the waveform and the one dimensional spatial distribution of the vertical components of the radially polarized THz beam. In the same way, the radially polarized THz signal can be obtained by scanning the mask downwards as:Based on Equations (1)–(5), the vertical components of the radially polarized THz beam when scanning the mask upwards and downwards, are shown in c are the dielectric constant and the speed of the light in vacuum, respectively, and d d2WdωBased on the above mask method, the amplitude of the radially polarized THz radiation can be manipulated by adjusting the amplitude of the longitudinal external electric field. ectively .zd = 0 mm was measured when the location of the left piece of the electrodes was at the beginning of the filament, while the THz spectrum marked with zd = 10 mm was measured when the location of the electrodes was changed by 10 mm towards the tailing of the filament. It was notable that the radially polarized THz radiation from the beginning of the filament was comparably lower than that from the tailing of the filament. This could be interpreted by the fact that the plasma density was a little bit higher at the location of the geometric focus. By this technique, we could smoothly tune the peak frequency of the radially polarized THz signal from 0.17 THz to 0.21 THz.With this longitudinally dc-biased filament, we could also slightly manipulate the peak frequency of the radially polarized THz radiation, except for its amplitude. In a long plasma filament, the plasma density along the filament is not homogeneous. We extended the length of the filament to 2 cm by increasing the laser energy to 4 mJ. We demonstrated the diagnosis of the radially polarized THz radiation from a longitudinal dc-biased laser plasma filament by introducing a movable metal mask. The amplitude and spectrum of the radially polarized THz beam was measured with a <110>-cut ZnTe crystal by modulating the THz beam pattern with the mask. Meanwhile, the linearly polarized components of the THz radiation from this dc-biased filament could be well distinguished from the THz pulses withradial polarization. The measured 1-D spatial distribution of the radially polarized THz radiation matched well with the simulation, according to the transition-Cherenkov model. Based on the mask method, the amplitude, as well as the spectrum of the radially polarized THz radiation, was manipulated by adjusting the amplitude and location of the external electric field, respectively. This work provides a new method of simultaneously measuring radially polarized and linearly polarized THz radiation, which has wide relevance in THz applications.


Nowadays, the search for novel active materials for laser devices is proceeding faster and faster thanks to the development of innovative materials able to combine excellent stimulated emission properties with low-cost synthesis and processing techniques. In this context, amplified spontaneous emission (ASE) properties are typically investigated to characterize the potentiality of a novel material for lasers, and a low ASE threshold is used as the key parameter to select the best candidate. However, several different methods are currently used to define the ASE threshold, hindering meaningful comparisons among various materials. In this work, we quantitatively investigate the ASE threshold dependence on the method used to determine it in thin films of dye-polymer blends and lead halide perovskites. We observe a systematic ASE threshold dependence on the method for all the different tested materials, and demonstrate that the best method choice depends on the kind of information one wants to extract. In particular, the methods that provide the lowest ASE threshold values are able to detect the excitation regime of early-stage ASE, whereas methods that are mostly spread in the literature return higher thresholds, detecting the excitation regime in which ASE becomes the dominant process in the sample emission. Finally, we propose a standard procedure to properly characterize the ASE threshold, in order to allow comparisons between different materials. The first demonstration of lasing from organic dyes in solution in 1966  encouragMore recently, another class of active materials has drawn increasing attention: lead halide perovskites, which initially were investigated for their possible use as active materials in photovoltaic devices ,15,16,17A common step in the characterization of a novel active material for laser applications is the analysis of its Amplified Spontaneous Emission (ASE) properties, which can be performed without any resonator providing optical feedback. The active material is deposited in form of a thin film in order to obtain a planar asymmetric waveguide and the ASE is observed by applying the variable pump intensity (VPI) method, i.e., by acquiring the photoluminescence (PL) spectra as a function of the excitation energy density. At low excitation densities, the PL spectra show only spontaneous emission, while, for excitation densities that are high enough, the ASE band starts to be visible, inducing a line shape variation, a spectral narrowing, and a stronger increase of the output intensity.The ability of a material to amplify radiation is typically quantified by an ASE threshold, with the sample with the lowest threshold considered the most suitable for the realization of a laser device. However, the ASE threshold does not have a unique definition and several methods have been adopted to determine it, making comparison between different values extremely difficult. A first step in the investigation of the ASE threshold dependence on the determination method was performed on polymeric active waveguides , evidencTo investigate the generality of this result, in this work, we study the ASE threshold dependence on its determination method for a total of seven thin films of lead halide perovskites of different dimensionality, and organic dyes embedded in polymeric matrices. In particular, we determine the ASE threshold of four different perovskite samples, with different dimensionality and chemical composition (fully inorganic or hybrid organic-inorganic), namely, bstrate) , a polychin film , and a qite film . For theite film  and two ite film , and rosite film , respectNo threshold: papers that do not provide any estimate of the ASE threshold [hreshold ,42,43;Qualitative: papers that provide an ASE threshold value, but do not specify how they calculate it [ulate it ,45;Slope general: the ASE threshold is defined as the point of slope change in the plot of the emission intensity as a function of the excitation density, without specifying what type of emission intensity is detected [detected ,47,48,49Slope total integrated: the slope variation is determined from the input–output plot of the total intensity, integrated across the sample emission spectral range [al range ,51,52,53Slope peak: the slope variation is determined from the input–output plot of the intensity at the ASE peak wavelength [velength ,54,55,56Slope ASE integrated: the slope variation is determined from the input–output plot of the spectrally integrated contribution of the ASE emission, separated from the spontaneous emission peak [ion peak ,57;FWHM/2: the ASE threshold is defined as the excitation density at which the emission full width at half maximum (FWHM) becomes one half of the FWHM value obtained at low excitation density, corresponding to the spontaneous emission value [on value ,59;FWHM narrowing: the ASE threshold is defined as the excitation density that corresponds to the beginning of the narrowing of the line [the line ,61;FWHM crossing: the ASE threshold is determined as the excitation density of the crossing point between the two best-fit lines describing the constant FWHM at low excitation density and the FWHM narrowing regime [g regime ,63,64;Visual: the ASE threshold is defined as the excitation density at which the spectral lineshape starts to change due to the appearance of an early-stage ASE band [ASE band ,65,66,67Gain: the ASE threshold is defined as the excitation density at which the net gain of the material becomes zero [mes zero ;Numerical: the ASE threshold is determined numerically starting from an analytical expression that describes the increase of ASE intensity with the excitation density [ density .As a first step, deep research on the state of the art was undertaken. In particular, we performed a Scopus search looking for all papers containing the following strings of words, “Amplified–Spontaneous–Emission–Dye–Film” and “Amplified–Spontaneous–Emission–Perovskite”, through a “Title–Abstract–Key" search type. In this way, we selected all the papers dealing with ASE in dye-doped and perovskite films, excluding all the papers on solutions or lasers. We found and analyzed 112 and 129 papers for dye-polymer blends and perovskites, respectively, evidencing the existence of several different methods to determine the ASE threshold. In particular, these include:By looking at the percentage distribution of the different methods see , it can As first samples, we investigated two fully inorganic h NCsub, a–c and wh NCsub, d–f HMDS-The excitation density dependence of the PL spectra of the NCsub sample shows a spontaneous emission band centered at about 530 nm at excitation densities below ible see a. The lopeak see b, obtainases see c. The exWe then performed a similar analysis for the NC sample. The PL spectra see d show thFWHM see f, which We then performed the same analysis starting from the excitation density dependence of the PL spectra of the quasi-2D and ples see , obtainithod see . The higthod see .The PL spectra of SRhB dye embedded in a pHEMA matrix as a function of the excitation intensity  across threshold .The analysis of the total integrated intensity, the ASE integrated intensity and the ASE peak intensity is provided in Finally, starting from the photoluminescence measurements, we also investigated the dependence of the spectral linewidth on the excitation intensity see c. In thigregates , can be In order to take into account this behavior, we adapted the We then performed a similar analysis on rosamine4 and perylene orange samples, whose spectral features and results descriptions are reported in hold see .A complete overview of the method dependence of ASE thresholds for all the investigated samples is provided by First of all, in all the samples the lowest value is obtained either from the application of the visual or the Moving to a deeper analysis of the results obtained from the three methods exploiting the input–output intensity plots, we evidence that for three samples , it is not possible to find a slope change from the ture see . This reThe importance of the contribution of the spontaneous emission to the analyzed intensity in the determination of the ASE threshold is also confirmed by the values obtained by the application of the other two output intensity-based methods: The general similarity between the values obtained from the intensity plots and from the FWHM/2 method, and the evidence that the In order to obtain better evidence of the kind of information that ASE thresholds coming from different methods can provide, for each sample we have compared a PL spectrum at low excitation density as a reference for the spontaneous emission lineshape, the PL spectrum acquired at the excitation density closest to the lowest threshold, and the one closest to the hold see . We can The choice of the method to be adopted to determine the ASE threshold is thus strictly related to the definition of the threshold itself, and to the kind of information that one wants to obtain. Since at low pump densities only the spontaneous emission exists, one possibility is to define the ASE threshold as the minimum excitation density that allows one to detect the amplification of the radiation. From this perspective, the best method is the one providing the lowest experimental value. On the other hand, from a practical point of view, it could be useful to determine the excitation regime at which the ASE is strong enough to start to dominate over the spontaneous emission. Concerning the first option, we found that the minimum ASE threshold values are obtained from the application of the visual and FWHM deviation  with respect to perovskite waveguides , even if the dependence on the method is similar.The strongly reduced extent of the variation among ASE thresholds in perovskite NCs and 3D films is ascribed to the higher efficiency of the ASE process compared to the dye-polymer samples. This results in a narrower excitation density range in which the transition from a regime of pure spontaneous emission to a regime of ASE dominance takes place, making the difference among the ASE thresholds obtained from different methods small. This attribution is also confirmed by the higher difference between the values obtained for the quasi-2D film, that is, the sample showing the smoother transition from spontaneous emission to ASE-dominated spectra.We selected two classes of active materials whose ASE properties had already been investigated ,38,39,40ization) , a bulk rovskite , and a trovskite .As dye-doped polymer samples, we chose three reference active molecules: SRhB , rosaminVPI measurements for perovskite samples PL and ASE measurements on the films were performed using an LTB MNL 100 nitrogen laser  as excitation source, delivering 3 ns pulses at 337 nm with a repetition rate of 10 Hz. The pump laser was focused by a cylindrical lens in order to obtain a rectangular stripe of 4 mm length and 80 VPI measurements for dye-polymer samples The thin film samples were optically pumped at 532 nm with 20 ns FWHM pulses from a frequency-doubled Q-switched Nd:YAG laser , operated at a 15 Hz repetition rate; the pump radiation was vertically or horizontally polarized. The light incident on the sample was perpendicular to the film surface and focused in a stripe shape spot of 150 A full description of the sample preparation and the ASE measurement set-ups can be found in the corresponding original papers ,38,39,401.Visual methodFor each sample, we determined the ASE threshold by investigating the excitation density dependence of the PL spectra lineshape, intensity, or linewidth. In particular:The threshold was determined by observing the PL spectrum lineshape when the excitation density is increased, considering as threshold the lowest excitation density value that allows the observation of a variation of the spectral line-shape, due to the ASE band appearance.2.Slope variation in the output intensity plot-based methodsThese methods consider the ASE threshold as the excitation density value at which the slope of increase of the spontaneous emission intensity with the excitation density grows due to the contribution of the ASE intensity.The slope variation excitation density is obtained as the crossing point between a linear best-fit line of the initial intensity increase and a following linear increase, with higher slope where the intensity increase becomes stronger. The error bar on the crossing point is obtained by determining a best-fit line range, varying the intercept of the best-fit lines within one standard deviation from the best-fit value, and determining the excitation density range between the crossing points of the extreme best-fit lines.In the d in Ref . Finally3.FWHM-based methodsThese methods quantify the ASE threshold by analyzing the spectral FWHM dependence on the excitation density. As the ASE band is narrower than the spontaneous emission one, the ASE appearance typically leads to a line narrowing.In order to have a quantitative description of this behavior, we performed a best fit with a constant or linearly decreasing function at low excitation density, a linear fit for the line narrowing excitation density range, and finally a best fit to a constant for high excitation densities. The intervals of the best-fit functions are determined by changing the constant term in the fit function within one standard deviation as obtained by the fitting procedure, and they are used to estimate the uncertainty of the threshold values.method: starting from the first point that deviates for more than one standard deviation from the initial constant/linear best fit, the ASE threshold value is calculated as the average between the excitation density value of this point and the one immediately before; semidispersion is used as maximum error and converted to statistical error;method: the ASE threshold is given by the excitation density value of the crossing point between the initial constant/linear fit at low excitation densities and the following decreasing linear fit. The intersection of the error lines are used for the determination of the ASE threshold error;FWHM/2 method: the ASE threshold is given by the excitation density at which the FWHM halves with respect to the initial value obtained at low excitation density (line-width of the spontaneous emission spectrum). In the samples showing a FWHM variation before the ASE-induced line narrowing, we considered as reference the spectral linewidth of the PL spectrum at the lowest excitation density.Starting from the best-fit curves, the ASE threshold was determined with three different methods:In this work, we have quantitatively investigated the ASE threshold dependence on the method used to determine it for dye-doped polymeric and lead halide perovskite thin films.We have analyzed the ASE properties of three dye-doped polymer and four lead halide perovskite thin films and quantitatively compared the ASE threshold values obtained with the application of the seven methods most spread in the literature. We have also demonstrated that the best way to determine the beginning of the ASE process is the determination of the lowest excitation density that allows the observation of a variation of the spontaneous emission line-shape. In addition, we have shown that the methods most spread in the literature based on the slope change in the intensity growth with the excitation density allow the determination of the excitation regime in which ASE becomes the dominant emission process. In particular, the slope change of the intensity at the ASE peak wavelength provided the best compromise between reliable threshold values and ease of application. Finally, we have demonstrated that the quantitative difference between the two kinds of ASE thresholds strongly depends on the strength of the ASE increase above the threshold, from about 30% in samples with efficient ASE  to more than six times in samples with gradually increasing ASE.Our results and their general validity for different classes of active materials clearly demonstrate that great care must be taken before using the ASE threshold values in comparisons between different active materials.In order to allow a complete and correct characterization of the ASE properties of a novel material and a meaningful quantitative comparison with already existing materials, we strongly suggest determining the beginning of the ASE by applying the visual method and the dominance of ASE by applying the


The sub-signals are performed with different conversions according to their standard deviation to assure that the local information’s security is guaranteed. Meanwhile, the parameters such as wavelength and diffraction distance are considered as additional keys, which can enhance the overall security. Then, inverse wavelet packet transform is applied to reconstruct the image, and a second scrambling is implemented. In order to handle and manage the parameters used in the scheme, the public key cryptosystem is applied. Finally, experiments and security analysis are presented to demonstrate the feasibility and robustness of the proposed scheme.In this paper, aiming to solve the problem of vital information security as well as neural network application in optical encryption system, we propose an optical image encryption method by using the Hopfield neural network. The algorithm uses a fuzzy single neuronal dynamic system and a chaotic Hopfield neural network for chaotic sequence generation and then obtains chaotic random phase masks. Initially, the original images are decomposed into sub-signals through wavelet packet transform, and the sub-signals are divided into two layers by adaptive classification after scrambling. The double random-phase encoding in 4 In the development of digital technology and computer industry, the requirements for information confidentiality has attracted increasing attention. In order to provide protection to multimedia applications, many algorithms have been developed during the past several decades. The application of optical methods in information security has become a hot trend due to its inherent capabilities of parallel processing ,2,3,4,5.Hopfield neural network, proposed for the first time by Hopfield in 1982 , is a tyIn recent years, chaotic systems have been combined with different cryptosystems and technologies for image encryption, such as compression sensing ,29 and Df system, and the second layer is encrypted by double random phase encoding in Fresnel domain. After inverse wavelet packet transform, the obtained image is secondarily scrambled. In addition, the keys used in the process of encryption are integrated and hidden by RSA cryptosystem. Finally, simulation experiments demonstrate the feasibility and security of the proposed method.In this paper, a chaotic Hopfield neural network and fuzzy single neuronal dynamic system are combined with a hybrid optical method to construct a new encryption method. In this scheme, the input image is decomposed into sub-signals through wavelet packet transform, and the sub-signals are divided into two layers by adaptive classification after scrambling. The chaotic random-phase masks are constructed by chaotic sequences. The first layer of sub-signals is encrypted by double random phase encoding (DRPE) in 4The single neuronal dynamical system in Hopfield neural network was proposed by Xu et al. in 2021 . The matified in . HoweverIn this work, we consider the triangular form of fuzzy number as Equation (2), and the full presentation of fuzzy number can be found in ,43,44..k and z.Considering This paper considers a 3-neuron Hopfield network of the form:When the 3-neuron Hopfield network applies the weight matrix, the system can display chaotic behavior. The dynamic behavior of the chaotic Hopfield network is complex and suitable for image encryption. Two large prime numbers . Then, DRPE of Fresnel transform is performed on sub signals of the second layer as in Equation (19):f system or Fresnel transform, Step 7: Perform DRPE of 4Step 8: Sub-signals are transformed into Step 9The keys used in the process of encryption are divided into three sequences. The first sequence includes initial values of chaotic Hopfield neural network and parameters of Arnold scrambling  is used as the criterion for quantitative analysis of the difference between the original image and decrypted image.The relationship between CC of the decrypted image and initial values is obtained, as shown in Due to the discernibility of information in plaintext images, adjacent pixels are usually highly correlated. Therefore, the reduction of the correlation between adjacent pixels of the cipher images is necessary . The calf system and Fresnel domain with Hopfield neural network to address inherent limitation of random matrix construction. The correlation coefficients of four encrypted images using various schemes are also demonstrated in It should be noted that the scheme combines double random phase encoding in 4Histogram analysis is the statistic of the number of times each value appears, in order to demonstrate the distribution of pixel values . The hisDue to the simple content of binary images, the traditional methods are not applicable sometimes. To test the performance of the algorithm on binary images, the results of encryption are shown in k is the noise strength and k = 0.01, k = 0.05 and k = 0.1 are shown in In practice, the cipher images may be affected by noise. We consider the robustness of our algorithm against noise by polluting the encrypted images of Lena with Gaussian random noise, which is expressed as:The comparative analysis among different schemes is demonstrated in f system and Fresnel domain based on chaotic system. The chaotic sequences are constructed by applying a fuzzy single neuronal dynamic system and a Hopfield chaotic neural network. The plaintext image is decomposed into sub-signals by wavelet packet transform, and then the sub-signals are scrambled. By adaptive classification, the sub-signals are divided into two layers. The first layer and second layer are encrypted in 4f system and Fresnel domain, thus completing the hybrid encryption. After inverse wavelet packet transform, the encrypted image is obtained through another scrambling. The RSA cryptosystem is applied to the allocation and management of the keys used in the scheme. Numerical simulations have demonstrated the security and effectiveness of the proposed scheme. The suggested scheme implements selective encryption of the local image, which improves the protection efficiency of vital information. It should be noted that the fuzzy numbers effectively enhance the stability and key space of the single neuronal dynamic system, and different fuzzy numbers other than triangular may be applicable to more chaotic systems. In addition, the feasibility of combining the chaotic Hopfield neural network with optical methods to construct an image encryption scheme has been verified. In further work, the application of other neural networks or chaotic systems may have more positive effects on optical image encryption.This paper proposes an optical image encryption method using double random-phase encoding in 4


A study of the peen forming of thin stainless steel metal foils (50  Shot peening is widely used to enhance the properties of tool bodies by introducing near-surface compressive residual stresses, which also improves fatigue resistance, crack initiation, and propagation . This isIt was quickly observed that LSP could be used to modify the geometry of the treated materials using the plastic changes (due to compressive stresses on the surface) produced by the shock waves . This teSample thickness has been demonstrated to be an important characteristic, along with pulse energy. If the plastic layer generated by the shock wave is relatively small in depth and length, there will be a rapid stress gradient in which the sample surface suffers maximum compression. This induces a bending moment in the beam direction (positive bending angle or convex curvature). However, if the deformation reaches the other side of the sample thickness, the plastic deformation will rebound so that the bending moment is applied in the opposite direction (negative bending angle or concave curvature) .LSP can be considered to be a cold process, since it is primarily mechanical in nature. The main idea of LSP is to use the shock wave generated by the plasma but, in order to do so, it is necessary to ablate the material, which will change the surface temperature. When a standard high-pulse-energy ns laser is used, the repetition rate will be around the tens of hertz, which allows the sample to cool down between pulses. Ultrashort lasers—pico-(ps), and femtosecond (fs) lasers—exhibit other advantages such as finer and more uniform microstructure and improved microhardness . Such laA practical industrial example of this technique is the manufacture of suspended magnetic heads for hard disks . It can The current paper studies the bending induced in thin 316 stainless steel samples and how this bending depends on the energy per pulse, the treated area, the distance between lines, and the repetition rate. Two magnitudes are studied: the bending angle and the radius of the curvature. Throughout the study, it is intended to demonstrate that the material can be bent accurately, inducing surface tensions as a function of the values of the parameters previously listed. The study also shows that the bending effect is local, and it cannot be scaled by increasing the repetition rate, because the increase in temperature relaxes the superficial stresses previously induced.This research uses a diode-pumped solid-state ps-pulsed laser (Ekspla Atlantic 355-60), working at X-axis , starting and ending at least First, A working experiment sketch is shown in The diameter of the zone affected by a focused single-laser pulse measured by confocal microscopy was The length The non-laser-treated regions remain straight, and the deformation is limited to the irradiated area. Therefore, the slopes of the non-treated zones can be compared, and the angle A set of experiments was carried out to study the effect of pulse energy Although, in principle, In the previous analysis, the length of the treated area was varied, but According to Stuart et al., ps and fs lasers should be capable of performing ablation without increasing (or at least doing so only slightly) the temperature of the sample surface . HoweverTo understand the effect of ions see  and a neThe results presented in Traditionally in LSP processes, the repetition rate is so low (on the order of the hertz or tens of hertz) that the sample is always able to cool down completely between pulses. Therefore, the repetition rate has no impact on the process. However, the experiments conducted here were performed using repetition rates that were higher by orders of magnitude. In the simulations presented in eviously ,20 in anIt has been shown that relaxation is affected by the residual stress state itself and by the material state, such as the material type and its microstructure . Howeverx of 1 µm and 20 µm separation between lines; one sample was scanned at 20 Regarding the mechanical properties of the samples, hardness tests were carried out using a Shimadzu DUH-211S dynamic ultra-micro hardness tester. The T-shaped parts were too thin and deformed for the analysis to be performed, so the same process was carried out on thicker stainless steel 316L samples (2 mm), in order to prevent them from bending because of the laser interaction. On these new thicker parts, there was no improvement in hardness compared to the non-treated sample. The value in Vickers of the substrate was (294 ± 22) HV, whereas the samples were treated using 111 µJ energy pulses, and PThe parameters that were frequently used were energy pulse between The effect of Varying LSP with ps lasers usually assumes that the pulse time is short enough to avoid thermal effects, and thus the effect of the repetition rate has been neglected, but if that were the reason, experiments using the same


The sense of touch is fundamental for a one-to-one mapping between the environment and a robot that physically interacts with the environment. Herein, we describe a tactile fingertip design that can robustly detect interaction forces given data collected from a camera. This design is based on the photoelastic effect observed in silicone matter. Under the force applied to the silicone rubber, owing to the stress-induced birefringence, the light propagating within the silicone rubber is subjected to the angular phase shift, where the latter is proportional to the increase in the image brightness in the camera frames. We present the calibration and test results of the photoelastic sensor design on a bench using a robot arm and with a certified industrial force torque sensor. We also discuss the applications of this sensor design and its potential relationship with human mechano-transduction receptors. We achieved a force sensing range of up to 8 N with a force resolution of around 0.5 N. The photoelastic tactile fingertip is suitable for robot grasping and might lead to further progress in robust tactile sensing. Physical interaction with the environment is always accompanied by mechanical stimuli, for which the human body is endowed with mechanisms to sense it. Peripheral terminals of the human somatosensory system transduce sensory stimuli into signals that propagate to the central nervous system . TransduOn the other hand, research in robot manipulation anticipated the need for optical tactile sensors that are more robust and indifferent to the external electromagnetic fields ,13. ThisMechanical properties of the aforementioned sensors, share to some extent similarities with other types of sensors, which are based on different transduction methods but that use silicone rubber, for example, hall effect sensors to detect the magnetic field generated by magnets embedded within a rubber ,10,15,16Several works employed fine optical structures in tactile robotics. Authors of  presentephotoelastic optical tactile sensors discussed in the following.Due to a relatively high density of transducers in RGB cameras, designers were competing to achieve higher spatial resolution by manufacturing thin and malleable reflective surfaces to capture small geometrical features of contact patterns ,23,24,25Bertholds et al.  were amoWith time, the use of the photoelastic effect evolved into tactile sensing technology. Several normal, shear, and torque sensors working on the photoelastic effect were developed. Dynamic tactile sensor by the authors of  could meThe authors of  developeIn this paper, we focus on straightforward manufacturing process and durability rather than the detection of geometrical features on the sensing surface. We conjectured that a standard camera-based tactile sensing system  built ofThe contribution of this work is a tactile sensing approach in reference to the photoelastic mechano-transduction ,36,37,38The novelty of our approach is the structure of the tactile sensor. We combined a photoelastic silicone rubber with opaque silicone rubber. The hardness of the rubbers are different. Photoelastic rubber is softer than opaque rubber. The hard rubber is designed as tactile fingertip  that intThe rest of the letter is structured in the following way: In The concept of the proposed photoelastic sensor is illustrated in The photoelastic effect and its numerical simulation for the photoelastic layer are described first. More details on modeling the light propagation can be found elsewhere, e.g., . The fabTo measure the stress-induced birefringence (dependence of refractive index on the polarization of propagating light) a typical setup of two polarizers is employed. The light emitted from an array of LEDs is prepolarized vertically by the polarizer. The polarized light then propagates through a compressible transparent layer, whose refractive index depends on the applied pressure. The beam’s polarization is then analyzed by recording the light intensity transmitted through analyzer by using a photosensitive matrix (a photosensor of a web camera). Since the light intensity function has a higher quality factor at minima, the polarizer and analyzer have an orthogonal orientation. All the details of photoelasticity theory are described in ™. All the details of the numerical calculations are described in To demonstrate the working mechanism of the stress-induced angular phase shift and its applicability to a sensor, the numerical simulations were performed using a commercial numerical solver COMSOL MultiphysicsF and A are the force and contact area, respectively. The corresponding relative change in the refractive index The obtained numerical results are shown in 10−4 see . Such a To create the stress  on the oThe photoelastic layer was formed by molds manufactured using a rapid prototyping printer based on fused deposition modeling . To avoid light reflection on the sensing rubber’s boundaries and ensure the sensor’s optimal performance, it is vital to have smooth surfaces of the photoelastic layer. To this end, a gasket (thin layer of the glassy film) was placed between the 3D printed mold and the transparent sides of the silicone. Such a fabrication process allows the creation of a transparent photoelastic layer with smooth surfaces.A two-component silicone resin was used to fabricate the sensing and pressing parts. For the transparent photoelastic part of the sensor, we used softer silicone  was used to observe the photoelastic effect by capturing the change of the intensity of light at 30 frames per second. To keep the frame rate in this range, the exposition of the camera was manually set to a low level (200 in the range between 3 to 2047 in the camera software), which prevents the saturation of the camera sensor’s by the light. The camera’s focus was also set to the minimum focus distance to ensure that the LED array stays focused  of the LEDs array is 40 mm). The camera’s diagonal field of view (FOV) is The LEDs are connected in series. The light intensity was controlled by the current that we supply to our custom-made 3 × 3 array of LEDs , with the supplied voltage of 14.5 V and a current of 100 mA. As a result, diodes emitted light with the intensity equivalent luminance of 180 Lux, which was measured using a Digital Lux Meter . A denser array of LEDs was used instead of a single LED to increase the uniformity of the light intensity and reduce the effect of the diffraction inside the photoelastic layer. In addition, distributed high-power LEDs are more convenient for heating power management.A 6-axis force/torque sensor  with an accuracy of 1% was used as ground truth  for calibration, see In this section, we describe the calibration of the photoelastic layer and discuss its force sensing characteristics when the sensor is attached to the robot end-effector.The PhotoElasticFinger was calibrated to estimate the normal force in SI units. Since our sensor is made of soft silicone resin, hysteresis is unavoidable in rubber-like material, since they act as mechanical low-pass filters . The meaTo decrease the effect of hysteresis and find a fit line, we performed measurements quasi-statically .To map the light intensity values captured by the camera into the force measurements, we implemented a piece-wise approximation function, which is drawn on the average fitting line between loading and unloading curves. The piece-wise consists of two parts, rising non-linear, and constant linear parts. The first part of the piece-wise function is used to estimate the forces up to 2 N. The second part of the piece-wise approximation function is derived for higher forces between 2 N and 8 N.To verify this approximation function, which to some extent disregards the real hysteresis of the silicone rubber, we performed several experiments that involve dynamic change of the contact force. We quantify the negative effect of hysteresis with Root-Mean-Square Error (RMSE) between the estimated and actual forces.‘rosbag’ service in ROS. Gray areas in the graph represent the deviation of the forces from both sensors. The position of the gripper (green line) is shown in the same time scale as the Cartesian distance units shown on the right-hand side axes (green). One can observe two features. First, there is higher variance in estimated force for the small displacement (0–2 mm) than for the maximum (5 mm) compression. Second, a constant bias between the actual and estimated force is present. Whereas the first feature is caused by the sensitivity during the absence of light  of the photoelastic silicone. Among these two limitations, the retardation time, which is present in the soft sensors, sets the main limit to the dynamic response of the photoelastic sensor. However, the durability and softness of the silicone-based sensors can outperform other sensing approaches, especially during precise manipulation.We summarized the characteristics of the sensor in The proposed PhotoElasticFinger sensor can detect contact forces from 0.5 N to 8 N. The sensor uses a commodity camera to capture the changes of transmitted light through the photoelastic layer due to the polarization angle shift caused by the stress-induced birefringence. With the emerging soft robotics, where maintaining the proper contact between the robot and the environment is crucial for proper control, there is a fundamental need for soft rubber sensors. To enable soft robot—object interactions, we propose to use a hyperelastic silicone resin. Despite its obvious disadvantages, such as low bandwidth, the proposed sensor provides high sensitivity and proper grip control for the particular hardness of the resin. Moreover, in many robot—object manipulation scenarios, numerous try-and-error trials are necessary , demandiThus, in the proposed sensor, the displacement of the fingertip caused by the deformation of the soft pad is an important mediator that serves as a safe buffer between the environment and robot end-effector. On top of that, the methods used are computationally cheap, requiring only measuring the intensity of the transmitted light. In contrast, stiffer materials can provide faster response time (or lower retardation times), but their intrinsic dispersion results in more intricate patterns , demandiIt should be noted that the approach described in this paper would fail to detect multiple contact points. This, however, could be mitigated by merging the photoelastic layer with multiple smaller fingertips and applying image processing techniques to analyze the regions of the silicone where intensity change occurs.Besides the multiple contact point sensing, there is a need for detecting torsional and lateral forces with their applications in slip detection ,45,46. IFor future work, we plan to detect the tangential force and torsion that can be integrated in a sensory-motor control of a touch-driven robot arm by applying deep learning techniques, e.g., ,48. The