Arrival Time Research Articles

670 Investigating Delay During Presentation of Trauma in Young Adults: A UK Major Trauma Centre Retrospective Audit and a Systematic Review of the Literature

Abstract Introduction The current evidence in major trauma highlights that delays at multiple points along the patient care pathway, from incident to surgery, are associated with decreased survival. The aim of this audit was to assess performance across select delay parameters in juveniles aged 16-18 presenting to an adult MTC service following a systematic review of the literature. Method Patient records were interrogated between 1/10/2022-1/3/2023 and audited against 3 national standards: (1) Ambulance Response and Transfer (7 and 45mins respectively) (2) Tranexamic Acid infusion (<3hrs) and (3) CT scan (<60mins). A systematic search was also performed using EMBASE and OVID databases (01/01/2005-/01/11/2023). All studies assessing impact of time to theatre in patients with acute trauma were considered. Results 32 consecutive patients (3F:29M) (median 18 years[16-18]) were identified within the audit period. 40%(n=13) presented following penetrating injury and 35%(n=11) following a road traffic accident. Mean time from incident to admission was 83mins[±36], from incident to tranexamic acid infusion 50mins[±35], and from admission to CT Trauma Series 61mins[+/-100]. Median length of stay was 4 days [IQR=5]. The systematic search yielded 25 studies which were included in the analysis. An Incident2Surgery framework is presented which highlights key time-critical points for diagnosis and intervention. Conclusions Local compliance to national standards for tranexamic acid infusion in appropriate patients and performance of trauma CT was excellent with poor compliance to ambulance arrival and transfer time. The proposed Incident2Surgery framework could be incorporated into mortality prediction and audit tools and assist in the assessment of interventions.

Noise Analysis of Six Pulsars and a Limit on the Gravitational Wave Background

Abstract The direct detection of ultra-low frequency gravitational waves (GWs, $10^{-9} - 10^{-6}$ Hz) using pulsar timing arrays (PTAs) is a significant application of millisecond pulsars. The initial detection of GWs in the nano-Hertz range will probably be an isotropic stochastic GW background (GWB) emitted by the combination of merging super-massive black hole binaries (SMBHBs). In this study, we utilize data from six pulsars collected with four European PTA (EPTA) telescopes to place an upper limit on the GWB amplitude $A = 2.34^{+0.75}_{-1.32} \times 10^{-15}$ (95\%) as a function of the spectral slope $\alpha = -2/3$, corresponding to a GWB generated by inspiraling SMBHBs. The posterior for the amplitude that we obtained from the six brightest EPTA pulsars is strongly consistent with previously published upper limits set by the three PTAs. We also compare the sensitivity of our reprocessed pulsar pulse times of arrival (ToAs) determined by the superior ToA creation method, which utilizes a combination of the best template generation algorithm and template-matching algorithm, with the ToAs determined by the EPTA groups. Our analysis shows that the reprocessed ToAs obtained with the superior ToA creation method yield narrower posteriors, indicating an overall increased sensitivity to GW.

Pulse‐level work state recognition of multifunction radar based on MC‐RSG

AbstractAccurate work state recognition of multifunction radar (MFR) is crucial in electronic warfare, as it helps understand the enemy's intention and evaluate potential threats. A pulse‐level work state recognition method of MFR based on the residual block with spatial attention connected gated recurrent unit by features using metric coding and correlative embedding (MC‐RSG) is proposed. Metric coding is designed to generate the distance vector with time of arrival, and the correlative embedding is performed on the distance vector and raw data features to increase the feature information by extracting feature information associated with the previous and subsequent pulses in each feature sequence, respectively. Besides, we make use of the model called RSG containing the residual block with spatial attention connected gated recurrent unit to learn the features of pulse sequences and identify the radar work state label of each pulse. The experimental work shows that the method is robust and has achieved up to 97% recognition accuracy on the test dataset under ideal observation conditions and 5% higher than the comparison network in high noise observation conditions.

Double-Difference Tomography with a Deep Learning–Based Phase Arrival Weighting Scheme and Its Application to the Anninghe–Xiaojiang Fault Zone

Abstract High-precision seismic phase arrivals are a prerequisite for building reliable velocity models with travel-time tomography. There has recently been a growing use of seismic phase arrival data obtained through deep learning techniques in travel-time tomography research. Nevertheless, a significant challenge that has emerged pertains to the assessment of the quality of these automatic arrivals. In this article, we used PhaseNet, a deep learning method, to automatically detect the arrival times of the P wave and S wave of 3086 seismic events recorded by dense seismic arrays, obtaining 87,553 high-quality arrivals. To evaluate the quality of the arrival times subsequently used for travel-time tomography inversion, we applied a weighting scheme that includes both detection probability value and signal-to-noise ratio. This new weighting scheme can effectively reduce the overall travel-time residual by 7%. The weighted data were then used in the double-difference tomography method to invert for the crustal velocity structure of the Anninghe–Xiaojiang fault zone. The resulting new model exhibits a lateral resolution of up to 0.25° and reveals velocity anomalies that exhibit a strong correlation with major geological features and block boundaries. Notably, the presence of low-VP and low-VS in the middle crust of the Ludian–Qiaojia seismic zone suggests the existence of hot and weak felsic rocks, as well as possible fluid presence beneath the seismogenic layer of this area. This study not only validates the practicality of using deep learning-based phase picking arrivals in travel-time tomography but also proposes a new weighting scheme to refine the tomographic velocity models.

Impact of Information Provision on Tsunami Evacuation Behavior of Residents and International Tourists in Japan

Effective disaster management can help mitigate both human and financial damage. However, the absence of appropriate disaster preparedness and management efforts can increase the vulnerability of international tourists to natural disasters. International tourists differ from residents and local tourists in various ways, including limited knowledge of disasters and disaster responses, use of different languages, limited access to signs, and shelter locations and evacuation routes. This study developed an agent-based evacuation model to determine the differences in evacuation behaviors among international tourists, residents, and local tourists during a tsunami. Further, it clarified the impact of both soft and hard countermeasures such as information provision and shelter capacity expansion. Our case study was conducted in the Minato Bay area in Osaka, Japan. The simulation results revealed disparities in the evacuation behaviors between international tourists and residents in the arrival times at shelters. The enhanced sign accessibility and provision of signs in multiple languages significantly reduced the arrival time of international tourists at shelters. Consequently, it is necessary to improve disaster management plans that ensure information provision in multiple languages and the establishment of temporary shelters near tourism spots to support international tourists during disaster evacuation.

Characteristic parameters measurement and flow prediction of slug flow based on ultrasound technology

Slug flow exists over a wide range of gas and liquid flow rates. For the case of smaller liquid volume fraction, this paper proposes a method for accurately identifying the flow structure of horizontal pipe slug flow based on the ultrasonic inner wall echo signal at the top of the pipe. The arrival and departure time of the slug is determined by analyzing the amplitude of the inner wall echo signal from both the test signal and reference signal and the rate of change of the test signal, respectively. Based on the accurate flow structure identification results, characteristic parameters can be calculated including the length ratio between the liquid film zone and the slug unit (lf/lu) and the average liquid film thickness in the liquid film zone (hf). The system of equations describing the relationship between the two parameters and the two-phase flow rates is constructed. By solving it, the flow rates of gas and liquid can be predicted. Experiments are carried out with the superficial velocity of gas and liquid ranging from 0.8 to 2.5 m/s and 0.1 to 0.4 m/s, respectively, where the pipeline’s inner diameter is 50 mm. The experimental results indicate that the mean absolute percentage errors for the predicted gas and liquid flow rates are 12.9605 % and 6.3517 %, respectively.

Improved Non-contact Vibration Measurement via Acceleration-based Blade Tip Timing

The conventional displacement-blade tip timing (D-BTT) measurements often rely on Once-Per-Revolution (OPR) sensors to compute expected or theoretical time of arrival (TOA) based on rotational speed. However, integrating OPR sensors within the confined space of aero-engines presents challenges, and estimating theoretical TOA introduces computational errors, particularly for low-amplitude, high-frequency blade vibrations. This paper presents the Acceleration-based Blade Tip Timing (A-BTT) method as a solution. Building upon A-BTT, the acquisition of blade tip vibration acceleration serves not only to capture rapid changes in vibration but also to offer richer data for precise measurement of high-frequency blade vibrations. With only three blade tip timing sensors recording actual TOA without an OPR sensor, A-BTT eliminates the need for estimating expected TOA, thus mitigating calculation errors. Furthermore, by analyzing the relationship between maximum blade tip vibration acceleration and displacement during synchronous blade vibration, vibration parameters, such as natural frequency, can be directly identified without prior information such as engine orders. Simulation and experimental results validate the efficacy of the A-BTT method, demonstrating its successful application to specific aero-engine compressor rotor blades.A-BTT

The effect of water mist nozzle settings on fire suppression of electric vehicles in garages

In recent years, along with the widespread use of electric vehicles (EV), EV fires have occurred frequently. However, few studies have investigated EV fires in confined spaces. To address this gap, this paper aims to explore the different aspects of fire evolution of EVs as well as examining the suppression effect of different water mist (WM) settings on these fires. Multiple simulations are carried out, using the Fire Dynamics Simulator (FDS) simulation tool, considering different numbers and working pressures of WM devices. The results highlighted that the number of WM devices had a more significant effect on the fire. Peak heat release was reduced by 17% and peak arrival time was delayed by 26% using 6 MPa with 3 nozzles compared to 0 nozzles. Additionally, it leads to accelerated mixing of the smoke layer with the air layer. Moreover, it was shown that the closer to the fire source in the vertical direction, the greater the degree of peak temperature decrease. In this regard, the maximum reduction in the measured temperature was around 70%.

Acoustic emission source localization for complex structure with multi-holes based on heuristic adaptive pathfinding and gradient descent method

Space debris poses a safety hazard to the operation of spacecraft, and the study of impact localization for spacecraft structures is of significance for the timely discovery of the impact location and the safeguarding of spacecraft and personnel safety. However, existing studies have mainly focused on continuous structures, and discontinuous structures of spacecraft with portholes and orifice-containing valves have been understudied. Therefore, in this article, the shortest propagation path algorithm of the signal and the acoustic emission source localization method applicable to multi-holes discontinuities structures are proposed. After calculating the signal arrival time difference, the localization method calculates the shortest propagation path of Lamb wave in complex multi-holes structure by the heuristic adaptive path-finding algorithm, which calculates distance differences traveled by the signal propagation to each sensor. The heuristic adaptive path-finding algorithm first constructs a map set based on the geometrical features of the structure, after which it searches for each partial path in the final path by heuristic computation to identify the shortest signal propagation trajectory. The objective function is established based on the target structural characteristics and sensor position parameters, of which the parameters of the equations are optimized based on the new travel difference-of-distance values generated from the results of the heuristic adaptive pathfinding calculation. Finally, the acoustic emission source coordinates are updated with a gradient descent strategy, which has an average localization error of 0.956 cm in 252 experiments and can effectively realize the impact localization calculation of multi-holes complex structures.

Dam break analysis of Ajwa dam during an extreme flood event in Vishwamitri basin

ABSTRACT Floods are one of the most common natural calamities and the disastrous action of flood becomes stringent when the floods are caused by dam failures. It is quite difficult to predict the failure of dam however the technique of dam break analysis provides an effective way to understand the flood wave generated due to assumed failure of dam. The present work focuses on dam break analysis of Ajwa dam constructed on river Surya, a tributary of river Vishwamitri. The work is divided into two parts. The first part consists of hydrological modeling of Vishwamitri basin using SWAT model and estimates the flood for 20-year return period and further calibrating and validating the model in SWATCUP 2019 using SUFI2 algorithm. The maximum flood calculated from SWAT model is taken as lateral inflow in dam break model setup. The breach parameters have been adopted as per the guidelines provided by Central Water Commission. Time of arrival of dam break flood at important locations downstream of Ajwa dam has been identified. The results reflect the potential of such a study to encompass the emergency action plans to safeguard the public and property in case of the possible flood event due to dam break.

Location Based Blood Donor Finding System

Abstract: This research paper delineates the creation and execution of an application based on serverless architecture, aimed at simplifying blood donation by enabling location-based donor searches. The system primarily uses cloud services such as API Gateway, Lambda Functions, and DynamoDB on popular cloud platforms. Google Maps API integration provides a dynamic mapping solution for a better user experience. This application allows a donor and blood bank to register their details including her GPS coordinates, thus providing users with an efficient and real-time way to find a donor nearby. Serverless architecture ensures cost efficiency, scalability, and seamless management of resources. API Gateway and Lambda functions are us ed to create RESTful APIs and facilitate communication between applications and databases. The DynamoDB database is used to store donor information, ensuring data persistence, reliability, and easy retrieval. Users can use the application to search for donors based on their current location and view the results on an interactive map. The system optimizes the blood donation process by calculating and displaying important information such as distance to the donor’s location, direction, and estimated time of arrival.

Features of Bearing on Underwater Object Using Phase Information of a Differential Stereo Sensor

Introduction. Safety of navigation and development of underwater mineral deposits require the accurate detection of various underwater objects. The literature discusses the issues of tracking their motion and trajectory. Sonar methods are proposed to maintain high accuracy of underwater object positioning. High accuracy of the bearing of stereo sensors with an ultrashort base is noted. However, this equipment is sensitive to the sampling rate of the signals, which causes “sampling noise”. There are no publicly available publications dedicated to the solution to this problem. The presented study is designed to fill this gap. This work is aimed to study the possibility of obtaining data clarifying information about the bearing of underwater objects through using the phase information about echoed probing signals and an additional procedure for resampling the source data.Materials and Methods. The location of the object was determined using the experimental complex for studying hydroacoustic sensors created by V.A. Shirokov and V.N. Milich at the Udmurt Federal Research Center, the Ural Branch of the Russian Academy of Sciences. A stereo sensor with a small base (30 mm) was used compared to the distance to the object (≈800–900 mm). Digital filtering methods and mathematical apparatus of correlation analysis of return hydroacoustic signals obtained by the phase method were used for data processing.Results. The results of comparing two methods for determining the bearing on an object are presented: by the difference in the time of arrival of the pulse-leading edges and by the maximum of the cross-correlation function (CCF). The change in bearing as the object moves, is graphically shown. The use of the leading edge of the signal caused small outliers of values along the entire bearing curve (less than 0.12 rad). At the maximum CCF, emissions were recorded only in some areas, but they were quite significant (about 0.17 rad). It showed how to select points corresponding to a smoother and more valid object trajectory, and how to work with erroneous points. The presented method of error correction can be implemented programmatically. With a quasi-harmonious signal, rare measurements of the original signal are interpolated by frequent calculated values. Thanks to this virtual increase in the sampling rate (oversampling), intermediate indicators can be recorded in the digitized source data. Interpolation of the signal values by a cubic spline allowed us to obtain 20 points for 1 period of the signal instead of 5 points in the original version. In this case, the trajectory formed with the maximum CCF is more correct.Discussion and Conclusion. The direction-finding problem can be solved with the accuracy required for practical application. Taking into account the factor of smoothness and continuity of the object's trajectory makes it possible to qualitatively correct the selection of the maximum of the cross-correlation function of the stereo sensor signals. The proposed methods have great potential for the development of underwater vision systems.

Expressway Vehicle Arrival Time Estimation Algorithm Based on Electronic Toll Collection Data

Precise travel time prediction benefits travelers and traffic managers by enabling anticipation of future roadway conditions, thus aiding in pre-trip planning and the development of traffic control strategies. This approach contributes to reducing travel time and alleviating traffic congestion issues. To achieve real-time state perception of vehicles on expressways, we propose an algorithm to estimate the arrival time of vehicles in the next segment using Electronic Toll Collection (ETC) data. Firstly, the characteristics of ETC data and GPS data are meticulously described. We devise algorithms for data cleaning and fusion, subsequently segmenting the vehicle journey into multiple sub-segments. In the following step, feature vectors are constructed from the fused data to detect service areas and analyze the expressway segment characteristics, vehicle traits, and the influence of service areas. Finally, an algorithm utilizing LightGBM is introduced for estimating the arrival time of vehicles at various segments, corroborated by empirical tests using authentic traffic data. The MAE of the algorithm is recorded as 20.1 s, with an RMSE of 32.6 s, affirming its efficacy. The method proposed in this paper can help optimize transportation systems for improving efficiency, alleviating congestion, reducing emissions, and enhancing safety.

Are Wearable Photoplethysmogram-Based Heart Rate Variability Measures Equivalent to Electrocardiogram? A Simulation Study.

Traditional electrocardiography (ECG)-derived heart rate variability (HRV) and photoplethysmography (PPG)-derived "HRV" (termed PRV) have been reported interchangeably. Any potential dissociation between HRV and PRV could be due to the variability in pulse arrival time (PAT; time between heartbeat and peripheral pulse). This study examined if PRV is equivalent to ECG-derived HRV and if PRV's innate error makes it a high-quality measurement separate from HRV. ECG data from 1084 subjects were obtained from the PhysioNet Autonomic Aging dataset, and individual PAT dispersions for both the wrist (n = 42) and finger (n = 49) were derived from Mol et al. (Exp Gerontol. 2020; 135: 110938). A Bayesian simulation was constructed whereby the individual arrival times of the PPG wave were calculated by placing a Gaussian prior on the individual QRS-wave timings of each ECG series. The standard deviation (σ) of the prior corresponds to the PAT dispersion from Mol et al. This was simulated 10,000 times for each PAT σ. The root mean square of successive differences (RMSSD) and standard deviation of N-N intervals (SDNN) were calculated for both HRV and PRV. The Region of Practical Equivalence bounds (ROPE) were set a priori at ± 0.2% of true HRV. The highest density interval (HDI) width, encompassing 95% of the posterior distribution, was calculated for each PAT σ. The lowest PAT σ (2.0 SD) corresponded to 88.4% within ROPE for SDNN and 21.4% for RMSSD. As the σ of PAT increases, the equivalence of PRV and HRV decreases for both SDNN and RMSSD. The HDI interval width increases with increasing PAT σ, with the HDI width increasing at a higher rate for RMSSD than SDNN. For individuals with greater PAT variability, PRV is not a surrogate for HRV. When considering PRV as a unique biometric measure, SDNN may have more favorable measurement properties than RMSSD, though both exhibit a non-uniform measurement error.

Evidence for Rapid Variability at High Energies in GRBs

Abstract Intrinsic variability was searched for in arrival times of six gamma-ray bursts (GRBs) at high energies – between 30 MeV and 2 GeV – detected by the Fermi satellite’s Large Area Telescope (LAT). The GRBs were selected from the Fermi LAT catalog with preference for events with numerous photons, a strong initial pulse, and measured redshifts. Three long GRBs and three short GRBs were selected and tested. Two different variability-detection algorithms were deployed, one counting photons in pairs, and the other multiplying time gaps between photons. In both tests, a real GRB was compared to 1000 Monte-Carlo versions of itself smoothed over a wide range of different timescales. The minimum detected variability timescales for long bursts (GRB 080916C, GRB 090926A, GRB 131108A) was found to be (0.005, 10.0, 10.0) seconds for the photon pair test and (2.0, 20.0, 10.0) seconds for the time-gap multiplication test. Additionally, the minimum detected variability timescales for the short bursts (GRB 090510, GRB 140619B, GRB 160709A) was found to be (0.05, 0.01, 20.0) seconds for the photon pair test and (0.05, 0.01, 20.0) seconds for the gap multiplication test. Statistical uncertainties in these times are about a factor of 2. The durations of these variability timescales may be used to constrain the geometry, dynamics, speed, cosmological dispersion, Lorentz-invariance violations, weak equivalence principle violations, and GRB models.

Late Neolithic collective burial reveals admixture dynamics during the third millennium BCE and the shaping of the European genome.

The third millennium BCE was a pivotal period of profound cultural and genomic transformations in Europe associated with migrations from the Pontic-Caspian steppe, which shaped the ancestry patterns in the present-day European genome. We performed a high-resolution whole-genome analysis including haplotype phasing of seven individuals of a collective burial from ~2500 cal BCE and of a Bell Beaker individual from ~2300 cal BCE in the Paris Basin in France. The collective burial revealed the arrival in real time of steppe ancestry in France. We reconstructed the genome of an unsampled individual through its relatives' genomes, enabling us to shed light on the early-stage admixture patterns, dynamics, and propagation of steppe ancestry in Late Neolithic Europe. We identified two major Neolithic/steppe-related ancestry admixture pulses around 3000/2900 BCE and 2600 BCE. These pulses suggest different population expansion dynamics with striking links to the Corded Ware and Bell Beaker cultural complexes.

Real-Time Method and Implementation of Head-Wave Extraction for Ultrasonic Imaging While Drilling

Extracting head waves and subsequently uploading their results from the downhole to the surface system in real time could improve the real-time guidance of ultrasonic imaging logging while drilling (UILWD) for drilling operations. To realize the downhole real-time extraction of head waves in this logging, three aspects were explored in this study. First, an improved energy ratio head-wave arrival extraction algorithm based on the weighting coefficients and characteristic functions, along with an amplitude detection method relying on peak-to-peak values, was proposed. Second, an echo reception pre-processing analog circuit and a digital signal processing circuit based on FPGA were designed. A pipeline algorithm was developed in FPGA to extract the arrival time and amplitude of the head wave. Finally, software simulations, laboratory tests, and field experiments related to this method were conducted. Our results showed that the real-time head-wave extraction method demonstrated a strong anti-noise ability in real time. The maximum relative error of the arrival time was less than 5%. The relative error of the amplitude was acceptable, and 90% of this value was within 5%. Through the measurement, the time of processing a single-channel waveform by a downhole algorithm was less than 15 ms, thus meeting the requirements for the real-time processing of downholes.

Analisis Tingkat Pelayanan Atas Kepuasaan Pelanggan Penyedia Barang Logistik Yang Akan Di Asuransikan Pada PT Kereta Api (Persero ) Medan Labuhan

The level of customer satisfaction with logistics goods provider services, especially PT Kereta Api (Persero) Medan Labuhan, is the main focus in this analysis. Through a survey of 35 respondents using local and long-distance train services, six main aspects of service were evaluated: ticket sales service, arrival time, cabin cleanliness, security, air circulation, and arrival time at destination. The results illustrate that despite improvements in some aspects, such as arrival times and safety, additional areas, including cabin cleanliness and air circulation, still have plenty of space for further development. According to these results, if we want to make train travel better for everyone, we need to pay close attention to these elements.

Development of a predictive algorithm for patient survival after traumatic injury using a five analyte blood panel.

Severe trauma can induce systemic inflammation but also immunosuppression, which makes understanding the immune response of trauma patients critical for therapeutic development and treatment approaches. By evaluating the levels of 59 proteins in the plasma of 50 healthy volunteers and 1000 trauma patients across five trauma centers in the United States, we identified 6 novel changes in immune proteins after traumatic injury and further new variations by sex, age, trauma type, comorbidities, and developed a new equation for prediction of patient survival. Blood was collected at the time of arrival at Level 1 trauma centers and patients were stratified based on trauma level, tissues injured, and injury types. Trauma patients had significantly upregulated proteins associated with immune activation (IL-23, MIP-5), immunosuppression (IL-10) and pleiotropic cytokines (IL-29, IL-6). A high ratio of IL-29 to IL-10 was identified as a new predictor of survival in less severe patients with ROC area of 0.933. Combining machine learning with statistical modeling we developed an equation ("VIPER") that could predict survival with ROC 0.966 in less severe patients and 0.8873 for all patients from a five analyte panel (IL-6, VEGF-A, IL-21, IL-29, and IL-10). Furthermore, we also identified three increased proteins (MIF, TRAIL, IL-29) and three decreased proteins (IL-7, TPO, IL-8) that were the most important in distinguishing a trauma blood profile. Biologic sex altered phenotype with IL-8 and MIF being lower in healthy women, but higher in female trauma patients when compared to male counterparts. This work identifies new responses to injury that may influence systemic immune dysfunction, serving as targets for therapeutics and immediate clinical benefit in identifying at-risk patients.

PORT PERFORMANCE IN THE PERSPECTIVE OF SHIP ARRIVAL AND DEPARTURE REPORT DATA

The seaport as a gateway to the regional, national and international economy must pay attention to the performance of operational services, including the level of service quality of ships, goods and port facilities. Activities at the port such as sea transportation operations must be reported to the Port Operator in accordance with the format of the ship arrival and departure report (LK3) which includes the type of ship, docking terminal, arrival time data and departure time from the Port. One perspective of port performance measurement is ship service which can be measured from how long the ship is at the terminal until it leaves the port. This research method uses a quantitative approach and the Data Envelopment Analysis (DEA) method. This study aims to determine the statistical approach and measure port performance, namely turnaround time and performance efficiency. The results of the study for 2022 obtained for the type of container ship, Tanjung Emas Port has a turnaround time of 23 hours while Tanjung Priok Port and Tanjung Perak Port are more than 24 hours and port performance efficiency with DEA efficient rating value Ѳ =1 at Tanjung Priok and Tanjung Perak ports.