Accurate vessel trajectory prediction is essential for maritime traffic control and management. In addition to collision avoidance, accurate vessel trajectory prediction can help in planning ...navigation routes, shortening the sailing distance, and increasing navigation efficiency. Vessel trajectory prediction with automatic identification system (AIS) data has thus attracted considerable attention in the maritime industry. Original AIS data may contain noise, which limits their application in real-world maritime traffic management. To overcome this problem, this study proposes a vessel trajectory prediction method that combines data denoising and a deep learning prediction model. In this method, data denoising is realized in three steps: trajectory separation, data denoising, and standardization. First, outliers from the original AIS data samples are removed, after which the moving average model is employed to further clean up the data; finally the denoised data are standardized into uniformly distributed time-series data. Bidirectional long short-term memory (Bi-LSTM) is then applied for vessel trajectory prediction. The performance of the proposed prediction model was verified using data on the trajectories of ten vessels and comparing the results obtained with those obtained using other prediction models (exponential smoothing, autoregressive integrated moving average, support vector regression, recurrent neural network, and LSTM models); the trajectory data were downloaded from a public AIS database. The experimental results revealed that model prediction accuracy increased after the data denoising process. Specifically, the Bi-LSTM model had the lowest mean absolute error, mean absolute percentage error, and root-mean-square error, demonstrating that the proposed method is highly efficient for trajectory prediction and can help vessel traffic controllers predict accurate vessel tracks; this would enable them to take early preventive measures to avoid collisions and thus improve the efficiency and safety of maritime traffic.
In previous studies, the frequency of error factors associated with medical adverse events seems to be the only criterion for understanding the distribution of error factors in hospitals. However, ...the types of error that occur most frequently in hospitals are not necessarily the most important. Therefore, this study integrated human error analysis and fuzzy TOPSIS to reconcile this discrepancy. The purpose of the study is to identity the important human error factors in emergency departments (ED) in Taiwan. Human factors analysis and classification system (HFACS) was used to analyze 35 ED adverse events to define the error factors. Multiple criteria decision making (MCDM) methods such as analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were applied to evaluate the importance of error factors. Results showed that decision errors, crew resource management, inadequate supervision, and resource management were the important human error factors related to ED adverse events. This study recommends that MCDM should be applied to further analyze the results based on the criteria.
•The systematic method of human errors analysis and MCDM was used in this research.•HFACS was applied to analyze medical adverse events in ED.•TOPSIS and AHP were used to assess the important human error factors in ED.•Sensitivity analysis was used to inspect the robustness of the results of TOPSIS.•This is the first study to integrate human errors analysis and MCDM method in ED.
Introduction
Carina breakthrough (CB) at the right pulmonary vein (RPV) can occur after circumferential pulmonary vein isolation (PVI) due to epicardial bridging or transient tissue edema. High‐power ...short‐duration (HPSD) ablation may increase the incidence of RPV CB. Currently, the surrogate of ablation parameters to predict RPV CB is not well established. This study investigated predictors of RPV CB in patients undergoing ablation index (AI)‐guided PVI with HPSD.
Methods
The study included 62 patients with symptomatic atrial fibrillation (AF) who underwent AI‐guided PVI using HPSD. Patients were categorized into two groups based on the presence or absence of RPV CB. Lesions adjacent to the RPV carina were assessed, and CB was confirmed through residual voltage, low voltage along the ablation lesions, and activation wavefront propagation.
Results
Out of the 62 patients, 21 (33.87%) experienced RPV CB (Group 1), while 41 (66.13%) achieved first‐pass RPV isolation (Group 2). Despite similar AI and HPSD, patients with RPV CB had lower contact force (CF) at lesions adjacent to the RPV carina. Receiver operating characteristic (ROC) curve analysis identified CF < 10.5 g as a predictor of RPV CB, with 75.7% sensitivity and 56.2% specificity (area under the curve: 0.714).
Conclusion
In patients undergoing AI‐guided PVI with HPSD, lower CF adjacent to the carina was associated with a higher risk of RPV CB. These findings suggest that maintaining higher CF during ablation in this region may reduce the occurrence of RPV CB.
Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which ...regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.
The first example of one single crystal (NTOU‐5) containing two different organic‐inorganic hybrid open‐framework structures was obtained using a hydro(solvo)thermal method and structurally ...characterized by single‐crystal X‐ray diffraction. Remarkably, under the same synthetic conditions, the zinc ions are respectively coordinated by oxalic acid (OX) and 1,2,4,5‐tetrakis(imidazol‐1‐ylmethyl)benzene (TIMB) linkers to form two significantly different frameworks: anionic Zn2(OX)32− and cationic Zn(TIMB)2+ networks that interweave with each other to give an unprecedented interpenetrating structure with two differently‐bonded open‐frameworks. From the inorganic chemistry perspective, it is extremely difficult to control to which metal center the oxygen‐donor linkers or/and nitrogen‐donor ligands bind. A mixed Co/Zn analogue was also obtained by a similar method. The single‐crystal XRD and EDS analyses indicate that the octahedral Zn ions of the anionic framework are replaced by cobalt cations, whereas the Zn ions in the tetrahedral positions of the cationic networks remain intact. This leads to the formation of the interpenetrating analogue with a mixed metal composition. Furthermore, NTOU‐5 shows structural stability and efficiently removes organic dyes from aqueous solutions at concentrations of 10 ppm.
Mix it up: For the first time, zinc ions are coordinated either by oxygen‐donor ligands or by nitrogen‐donor linkers in the same synthetic conditions to form significantly distinct anionic and cationic networks that interweave with each other to give an unprecedented class of interpenetrating structure with two differently‐bonded open‐frameworks, NTOU‐5. A mixed metal analogue was also obtained by a similar synthesis method. Moreover, NTOU‐5 efficiently achieves water remediation by removing organic dyes from aqueous solutions, even at low concentration (10 ppm).
The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement ...strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology.
•The systematic method of HEI analysis and MCDM was provided in this research.•HFACS and RCA were applied to analyze latent human errors.•Fuzzy TOPSIS was utilized to assess the improvement strategy of latent human errors.•Sensitivity analysis was used to inspect the robustness of the results of Fuzzy TOPSIS.•This is the first study to assess human errors by HFACS and Fuzzy TOPSIS.
Tide is a phenomenon of water level change caused by gravity. Tidal level forecasting is not only a key theoretical topic but also crucial in coastal and ocean engineering applications. The waiting ...time before a cargo ship enters a port affects the efficiency of cargo transportation, the tidal difference affects the establishment of turbine generators, and an excessive tidal water level reduces vessel safety. With the proliferation of information technology, the application of deep learning models in the analysis and study of hydrological problems has become increasingly common. This study proposed a deep learning model to predict the tidal water level. A forecasting model was developed on the basis of the long short-term memory (LSTM) recurrent neural network for predicting the water levels of 17 harbors in Taiwan. Tidal water level data for 21 years were collected from different observation stations. To objectively evaluate model performance, the developed model was compared with six other forecasting models in terms of the mean absolute percentage error (MAPE) and root mean square error (RMSE) of the forecasting results. The results indicated that the LSTM model had the lowest forecasting error for the tidal water level for up to 30 days. The average MAPE and RMSE values for the developed model were 6.97% and 0.049 m, respectively; thus, the model could effectively reduce the overlapping problems caused by machine learning methods in continuous forecasting.
Sensory gating describes neurological processes of filtering out redundant or unnecessary stimuli during information processing, and sensory gating deficits may contribute to the symptoms of ...schizophrenia. Among the three components of auditory event-related potentials reflecting sensory gating, P50 implies pre-attentional filtering of sensory information and N100/P200 reflects attention triggering and allocation processes. Although diminished P50 gating has been extensively documented in patients with schizophrenia, previous studies on N100 were inconclusive, and P200 has been rarely examined. This study aimed to investigate whether patients with schizophrenia have P50, N100, and P200 gating deficits compared with control subjects.
Control subjects and clinically stable schizophrenia patients were recruited. The mid-latency auditory evoked responses, comprising P50, N100, and P200, were measured using the auditory-paired click paradigm without manipulation of attention. Sensory gating parameters included S1 amplitude, S2 amplitude, amplitude difference (S1-S2), and gating ratio (S2/S1). We also evaluated schizophrenia patients with PANSS to be correlated with sensory gating indices.
One hundred four patients and 102 control subjects were examined. Compared to the control group, schizophrenia patients had significant sensory gating deficits in P50, N100, and P200, reflected by larger gating ratios and smaller amplitude differences. Further analysis revealed that the S2 amplitude of P50 was larger, while the S1 amplitude of N100/P200 was smaller, in schizophrenia patients than in the controls. We found no correlations between sensory gating indices and schizophrenia positive or negative symptom clusters. However, we found a negative correlation between the P200 S2 amplitude and Bell's emotional discomfort factor/Wallwork's depressed factor.
Till date, this study has the largest sample size to analyze P50, N100, and P200 collectively by adopting the passive auditory paired-click paradigm without distractors. With covariates controlled for possible confounds, such as age, education, smoking amount and retained pairs, we found that schizophrenia patients had significant sensory gating deficits in P50-N100-P200. The schizophrenia patients had demonstrated a unique pattern of sensory gating deficits, including repetition suppression deficits in P50 and stimulus registration deficits in N100/200. These results suggest that sensory gating is a pervasive cognitive abnormality in schizophrenia patients that is not limited to the pre-attentive phase of information processing. Since P200 exhibited a large effect size and did not require additional time during recruitment, future studies of P50-N100-P200 collectively are highly recommended.
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