Typical Time Research Articles

Modeling nanogratings erasure at high repetition rate in commercial optical glasses

Volume nanogratings (NGs) imprinted by infrared femtosecond laser in commercial optical glasses take the form of orientable subwavelength birefringent nanostructures, being composed of an assembly of nanopores. The existence of NGs strongly depends on the laser parameters and glass composition. Therefore, in this work, we tentatively model the erasure threshold of NGs in a pulse energy - repetition rate processing window. For this purpose, we combine i) a heat diffusion model to simulate the thermal treatment experienced by the glass upon laser irradiation, and ii) the Rayleigh-Plesset equation to take into account the evolution of a nanopore size during laser processing. We first determine a criterion for nanopores erasure, falling within a typical characteristic time of few tens of ns, in which the cooling of the last laser pulse absorbed by the material is progressively cooled. Then, considering a multiple pulse regime and the dependence of the deposited pulse numbers on the thermal treatment, the modeled NGs erasure threshold follows the experimental trend. Finally, considering a steady state regime for various repetition rates, and adjusting the energy deposition (absorption coefficient or beam waist) as a function of the pulse energy, the NGs existence window can perfectly match the experimental values.

High Gradient Magnetic Fields Generated in Events on the 230 kV Electric Power Transmission Infrastructure: Human Exposure Analysis and Risk

This work presents a process for analyzing human exposure to high-gradient magnetic fields based on protection models for patients undergoing magnetic resonance examinations developed by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). A series of events presented in the electrical energy transmission infrastructure is taken, with typical currents and front times, a case of extreme failure is added, and results are presented. Subsequently, with a classic lightning signal, compliance with the exposure to this type of field in the right-of-way strip of a transmission line is verified and validated in the event of a hypothetical atmospheric discharge impact event. Finally, a simulation is implemented with space discretization techniques, establishing the signal resulting from the magnetic field generated as a function of time. The exposure is evaluated using the presented model. Only in one of the analysis cases was it found that the perception threshold is exceeded at distances less than 0.6 cm, virtually a situation in which the worker has contact with the down conductor. With the results obtained and the cases analyzed, it is concluded that failures of this type do not generate significant exposure to high-gradient magnetic fields and do not exceed the determined perception thresholds.

Robust global optimization of plasmonic filter based on Q factor analysis using graded index

Abstract To reduce the impact of uncertainties in various manufacturing processes while maintaining satisfactory performance level, we propose a robust global optimization approach for plasmonic filters based on extraordinary optical transmission by use of Q factor analysis with reasonable computational cost. The gradient index is employed as a metric for robustness, and the multiobjective genetic algorithm is selected as a global optimization tool. The figures of merit and gradient index are chosen as two objective functions with the design variables being the slit width, slit height, and period of the slit array, respectively. The finite element method is employed to investigate a variety of optical properties rigorously. The numerical optimization results demonstrate that the proposed approach provides improved effectiveness and efficiency in designing plasmonic filters under fabrication uncertainties by using Q factor analysis. The method proposed in this study enables systematic robust optimization while accounting for manufacturing uncertainties, which would be infeasible under typical time constraints. Specifically, within the proposed optimization framework, Q factor analysis can be employed due to a 20.60-times reduction in computational time. To the best of our knowledge, this represents the first robust optimization design for enhanced filter performance based on Q factor analysis in EOT, necessitating comprehensive spectrum calculations alongside fabrication tolerance considerations.

Synthesis of core-functionalised naphthalene diimides from naphthalenetetracarboxylic dianhydride using a vibratory ball mill: bromination, imidization and Heck-type reactions.

The synthesis of 9 core-functionalised naphthalene diimide (c-NDI) residues is reported via a 3-step solvent free synthesis from naphthalenetetracarboxylic dianhydride using only mechanochemical activation. Selective dibromination and subsequent dimidiation were achieved for the first time in a vibratory ball mill, resulting in the key structural intermediate, 2,6-dibromonaphthalenediimide (DBND), which is the basis for elaboration into a multitude of organic electronic materials. Our new synthesis of DBND is achieved in just 5 hours' reaction time over two steps compared to typical solution state times of 24 hours. Subsequent Heck-type cross coupling reactions, with a range of styrene residues, produced a series of c-NDIs in good yields. The Heck-type reactions are rapid (1.5 hours), require no additional heating or solvent and are tolerant of atmospheric moisture and air.

Research on the climate change and prediction of the temperature in Beijing

Abstract. Over the past few years, global warming has become a growing threat to the human living environment. Thus, preventing extreme temperature changes is a crucial area of study for the global community. However, temperature changes have diverse causes, making it hard to accurately calculate the data that impacts subsequent temperature forecasts. The ARIMA model is widely favoured by researchers as a typical time series prediction model. Additionally, it holds significant research value in forecasting dynamic models. This paper will use the ARIMA model to forecast temperature changes in Beijing for the next month, starting on 21 July. The findings show that the temperature remains relatively stable in the upcoming month, with minimal fluctuations. Based on historical data, this is the peak temperature in Beijing for the year. So, if the temperatures are not extremely high now, they might not get higher later. This forecast can be used as a guide for managing extreme temperatures in Beijing in the future.

Anchoring temporal convolutional networks for epileptic seizure prediction.

Objective. Accurate and timely prediction of epileptic seizures is crucial for empowering patients to mitigate their impact or prevent them altogether. Current studies predominantly focus on short-term seizure predictions, which causes the prediction time to be shorter than the onset of antiepileptic, thus failing to prevent seizures. However, longer epilepsy prediction faces the problem that as the preictal period lengthens, it increasingly resembles the interictal period, complicating differentiation.Approach. To address these issues, we employ the sample entropy method for feature extraction from electroencephalography (EEG) signals. Subsequently, we introduce the anchoring temporal convolutional networks (ATCN) model for longer-term, patient-specific epilepsy prediction. ATCN utilizes dilated causal convolutional networks to learn time-dependent features from previous data, capturing temporal causal correlations within and between samples. Additionally, the model also incorporates anchoring data to enhance the performance of epilepsy prediction further. Finally, we proposed a multilayer sliding window prediction algorithm for seizure alarms.Main results. Evaluation on the Freiburg intracranial EEG dataset shows our approach achieves 100% sensitivity, a false prediction rate (FPR) of 0.09 per hour, and an average prediction time (APT) of 98.92 min. Using the CHB-MIT scalp EEG dataset, we achieve 97.44% sensitivity, a FPR of 0.12 per hour, and an APT of 93.54 min.Significance. These results demonstrate that our approach is adequate for seizure prediction over a more extended prediction range on intracranial and scalp EEG datasets. The APT of our approach exceeds the typical onset time of antiepileptic. This approach is particularly beneficial for patients who need to take medication at regular intervals, as they may only need to take their medication when our method issues an alarm. This capability has the potential to prevent seizures, which will greatly improve patients' quality of life.

Modelling absorption and emission profiles from accretion disc winds with WINE

Fast and massive winds are ubiquitously observed in the UV and X-ray spectra of active galactic nuclei (AGNs) and other accretion-powered sources. Several theoretical and observational pieces of evidence suggest they are launched at accretion disc scales, carrying significant mass and angular momentum. Thanks to such high-energy output, they may play an important role in transferring the energy released by accretion to the surrounding environment. In the case of AGNs, this process can help to set the so-called co-evolution between an AGN and its host galaxy, which mutually regulates their growth across cosmic time. To precisely assess the effective role of UV and X-ray winds at accretion disc scales, it is necessary to accurately measure their properties, including mass and energy rates. However, this is a challenging task, due to both the limited signal-to-noise ratio of available observations and the limitations of the models currently used in the spectral analysis. We aim to maximise the scientific return of current and future observations by improving the theoretical modelling of these winds through our Winds in the Ionised Nuclear Environment (WINE) model. WINE is a spectroscopic model specifically designed for disc winds in AGNs and compact accreting sources, which couples photoionisation and radiative transfer with special relativistic effects and a three-dimensional model of the emission profiles. We explore with WINE the main spectral features associated with the disc winds in AGNs, with a particular emphasis on the detectability of the wind emission in the total transmitted spectrum. We explore the impact of the wind ionisation, column density, velocity field, and geometry in shaping the emission profiles. We simulated observations with the X-ray microcalorimeter Resolve on board the recently launched XRISM satellite and the X-IFU on board the future Athena mission. This allows us to assess the capabilities of these telescopes in the study of disc winds in X-ray spectra of AGNs for the typical physical properties and exposure times of the sources included in the XRISM performance verification phase. The wind kinematic and geometry (together with the ionisation and column density) deeply affect both shape and strength of the wind spectral features. Thanks to this, both Resolve and, on a longer timescale X-IFU will be able to accurately constrain the main properties of disc winds over a broad range of ionisation, column densities, and covering factors. We also investigate the impact of the spectral energy distribution (SED) on the resulting appearance of the wind. Our findings reveal a dramatic difference in the gas opacity when using a soft, Narrow Line Seyfert 1-like SED compared to a canonical powerlaw SED with a spectral index of $

Kinetics of Polyampholyte Dimerization: Influence of Charge Sequences

Polyampholytes (PAs) exhibit complex behaviors in various environments influenced by their charge distribution. This study focuses on the kinetics of dimerization of PAs, aiming to elucidate the underlying mechanisms and clarify relevant characteristics of the charge sequence. We focus on PAs with non-zero net charges, employing molecular dynamics simulations and theoretical analyses to examine how charge sequences influence the rates of dimer formation and dissociation. Our findings reveal that the charge sequence of tails and the blockiness of the minority charge group markedly influence the kinetics of dimerization: large blockiness and tails with a high number of majority-type charges slow down the dissociation of dimers. Additionally, the presence of an extended (central) block of the majority charge promotes structural diversity. Within dimer states, blocks alternate between intra- and inter-chain contacts. The duration times in the dimer states are significantly longer than the typical dwell times of block inter-contacts, with a notable extension when multiple blocks are engaged. Intrinsically disordered proteins (IDPs) play crucial roles in cellular functions, primarily due to their ability to undergo rapid conformational changes and form transient complexes. These properties largely depend on the sequence of charged residues. We provide insights into the fundamental principles governing the structural and dynamical properties of polyampholytic IDP, emphasizing the importance of sequence-specific effects on both aggregation and dissociation.

An estimate of resident time of the Oort Cloud new comets in planetary region

We describe the result of our numerical orbit simulation which traces dynamical evolution of new comets coming from the Oort Cloud. We combine two dynamical models for this purpose. The first one is semi-analytic, and it models an evolving comet cloud under galactic tide and encounters with nearby stars. The second one numerically deals with planetary perturbation in the planetary region. Although our study does not include physical effects such as fading or disintegration of comets, we found that typical dynamical resident time of the comets in the planetary region is about 108 years. We also found that the so-called planet barrier works when the initial orbital inclination of the comets is small. A numerical result concerning the temporary transition of the comets into other small body populations such as transneptunian objects or Centaurs is discussed.

Temporal Autoregressive Matrix Factorization for High-Dimensional Time Series Prediction of OSS.

Open-source software (OSS) plays an increasingly significant role in modern software development tendency, so accurate prediction of the future development of OSS has become an essential topic. The behavioral data of different open-source software are closely related to their development prospects. However, most of these behavioral data are typical high-dimensional time series data streams with noise and missing values. Hence, accurate prediction on such cluttered data requires the model to be highly scalable, which is not a property of traditional time series prediction models. To this end, we propose a temporal autoregressive matrix factorization (TAMF) framework that supports data-driven temporal learning and prediction. Specifically, we first construct a trend and period autoregressive model to extract trend and period features from OSS behavioral data, and then combine the regression model with a graph-based matrix factorization (MF) to complete the missing values by exploiting the correlations among the time series data. Finally, use the trained regression model to make predictions on the target data. This scheme ensures that TAMF can be applied to different types of high-dimensional time series data and thus has high versatility. We selected ten real developer behavior data from GitHub for case analysis. The experimental results show that TAMF has good scalability and prediction accuracy.

Temporally Resolved Type III Solar Radio Bursts in the Frequency Range 3–13 MHz

Radio observations from space allow to characterize solar radio bursts below the ionospheric cutoff, which are otherwise inaccessible, but suffer from low, insufficient temporal resolution. In this Letter we present novel, high-temporal resolution observations of type III solar radio bursts in the range 3–13 MHz. A dedicated configuration of the Radio and Plasma Waves (RPW) High Frequency Receiver (HFR) on the Solar Orbiter mission, allowing for a temporal resolution as high as ∼0.07 s (up to 2 orders of magnitude better than any other spacecraft measurements), provides for the very first time resolved measurements of the typical decay time values in this frequency range. The comparison of data with different time resolutions and acquired at different radial distances indicates that discrepancies with decay time values provided in previous studies are only due to the insufficient time resolution not allowing to accurately characterize decay times in this frequency range. The statistical analysis on a large sample of ∼500 type III radio bursts shows a power low decay time trend with a spectral index of −0.75 ± 0.03 when the median values for each frequency are considered. When these results are combined with previous observations, referring to frequencies outside the considered range, a spectral index of −1.00 ± 0.01 is found in the range ∼0.05–300 MHz, compatible with the presence of radio-wave scattering between 1 and 100 R ☉.

Thermalization and hotspot formation around small primordial black holes

We quantitatively analyze a basic question: what is the stationary solution of the background plasma temperature profile around a black hole (BH)? One may naively expect that the temperature profile continuously decreases from the Hawking temperature at the surface of the BH towards an outer region. We show analytically and numerically that this is not the case because local thermal equilibrium cannot be maintained near the surface of the BH and also because the high-energy particles emitted from Hawking radiation cannot be instantaneously thermalized into the background plasma. The temperature profile has a plateau within a finite distance from the BH, and even the overall amplitude of background temperature at a distance far away from the BH is significantly suppressed compared with the naive expectation. The main reason for these counterintuitive results comes from the fact that the size of the BH is too small that particles of Hawking radiation goes far away within the typical time scale of interactions.

Design of an FPGA-Based Controller for Fast Scanning Probe Microscopy.

Atomic-scale imaging using scanning probe microscopy is a pivotal method for investigating the morphology and physico-chemical properties of nanostructured surfaces. Time resolution represents a significant limitation of this technique, as typical image acquisition times are on the order of several seconds or even a few minutes, while dynamic processes-such as surface restructuring or particle sintering, to be observed upon external stimuli such as changes in gas atmosphere or electrochemical potential-often occur within timescales shorter than a second. In this article, we present a fully redesigned field programmable gate array (FPGA)-based instrument that can be integrated into most commercially available standard scanning probe microscopes. This instrument not only significantly accelerates the acquisition of atomic-scale images by orders of magnitude but also enables the tracking of moving features such as adatoms, vacancies, or clusters across the surface ("atom tracking") due to the parallel execution of sophisticated control and acquisition algorithms and the fast exchange of data with an external processor. Each of these measurement modes requires a complex series of operations within the FPGA that are explained in detail.

Single-photon elimination in liquid scintillation counting with pulse shape discrimination and delayed coincidence

Liquid scintillation counting is widely used in the rapid measurement of beta activity in environmental and biological samples. However, the single-photons generated by chemiluminescence and photoluminescence in liquid scintillation cocktails seriously affect the measurement accuracy of low-energy beta activity. A novel method based on the combination of the signal characteristic analysis and selective gate to eliminate the single-photon signal was developed. A preprocessing circuit made of a fast response time photomultiplier tube (PMT, Hamamatsu R9420), two charge-sensitive preamplifiers (CSP), two comparators, an analog switch and delay-line devices were designed and developed to verify the feasibility and effectiveness. The output signals from the last dynode were characterized in the pulse time and were used to discriminate the beta signals from the single-photon ones. The beta signals were “tagged” through pulse width detection, pulse width-amplitude transform and pulse-height discrimination with the first comparator, the first CSP and the second comparator. The “tagged” beta signal were applied to control the analog switch. The anode signals were specially delayed and then selected by the analog switch to achieve the single-photon signal elimination. Liquid scintillation cocktails containing 14C or NaOH used as beta or single-photon sources were provided to verify the feasibility of the principle. The results showed that the typical fall time of the single-photon and beta signal was 16.05ns and 43.17ns. The single-photon rejection ratio is 2.76 × 10−3 ± 3.89 × 10−5, and the detection efficiency is up to 93.02%±0.59%.

Spectroscopic determination of Deborah numbers in membrane-mimetic bolaamphiphile assemblies

The remarkable stability of Archaebacteria and their resistance to extreme environmental conditions, such as high temperature (hot springs), high salinity (salt marsh), high acidity (volcanic environment), or low temperature (Arctic or Antarctic) is mostly due to their very stable membranes. Membranes of Archaebacteria are composed of tetraethers from the lipid family of bolaamphiphiles. The concern in our laboratory is to synthesize bolaamphiphiles that could form vectors with function to carry drugs toward target cells in the body. The new family of bolamphiphiles synthesized has one polar head based on a sugar moiety and the other polar head is glycine betaine, both issued from natural sources (sugar beet, wheat). They are interconnected with a hydrocarbon chain of 12 methylène units. One side hydrocarbon chain, of 8 methylène units is attached to the anomeric position of the sugar moiety. These two molecules are named N-(12-Betainylamino-Dodecane)-octyl β-D-Glucofuranosiduronamide Chloride, abbreviated C8C12 and N-(12-Betainylamino-Dodeca-5,7-diynyl)-octyl β-D-Glucofuranosiduronamide Chloride, abbreviated C8C12X2. These bolaamphiphile molecules organize in membrane-mimetic lamellar structures (Lc, Lα, L). They undergo a thermal phase transition upon heating. When cooled back to room temperature, they remain in the undercooled high-temperature phase. To follow the relaxation back to the thermodynamically stable phase at 20 °C, the small-angle and wide-angle X-ray spectra were recorded every hour. The Deborah number (De), defined as De = time of relaxation/time of observation, is a dimensionless number often used in rheology to characterize the fluidity of materials under specific flow conditions. It was evaluated for supramolecular structures of two type of bolaamphiphiles, as the De(C8C12) = 35 and the De(C8C12X2) = 62. These values are typical for solid-like behavior, which is in accordance with the sticky, paste-like, brownish aspect of these bolaamphiphile assemblies. The time of relaxation was the time for bolaamphiphiles to regain their thermodynamically stable phase at 20 °C and the time of observation was 1 h, the typical time of recording between two subsequent spectra.

Experimental study on the influence of fiber characteristics on the working property of underwater flowable solidified soil: Flowability, anti-dispersion, strength and anti-scour resistance

A series of laboratory tests were conducted to investigate the properties of fiber-reinforced underwater flowable solidified soil (UFSS) as a novel material for scour protection in marine structures. The tests included flowability, underwater anti-dispersion, unconfined compressive strength (UCS), and anti-scour resistance. Results showed that adding fibers reduced UFSS's flowability and significantly enhanced its underwater anti-dispersion, exhibiting a similar trend with increasing fiber content. Increasing fiber length initially decreased and then increased flowability, with the opposite trend for anti-dispersion. The least favorable fiber lengths for flowability were 6 mm for PVA fiber and 9 mm for both basalt and glass fibers, whereas these lengths were optimal for anti-dispersion. Fibers improved both UCS and anti-scour resistance of UFSS, with both properties first increasing and then decreasing as fiber content and length increased. Excessive fiber content or length reduced both properties. In this study, the optimal fiber content for improving UCS was 0.3% for PVA and 0.2% for basalt and glass fibers, with an optimal length of 6 mm for all three. An empirical exponential relationship between UCS, critical scour resistance velocity, and critical scour shear stress at typical times (t = 3 h, 5 h) was established for rapid prediction of UFSS's anti-scour resistance.

Prerelaxation in quantum, classical, and quantum-classical two-impurity models

We numerically study the relaxation dynamics of impurity-host systems, focusing on the presence of long-lived metastable states in the nonequilibrium dynamics after an initial excitation of the impurities. In generic systems, an excited impurity coupled to a large bath at zero temperature is expected to relax and approach its ground state over time. However, certain exceptional cases exhibit metastability, where the system remains in an excited state on timescales largely exceeding the typical relaxation time. We study this phenomenon for three prototypical impurity models: a tight-binding quantum model of independent spinless fermions on a lattice with two stub impurities, a classical-spin Heisenberg model with two weakly coupled classical impurity spins, and a tight-binding quantum model of independent electrons with two classical impurity spins. Through numerical integration of the fundamental equations of motion, we find that all three models exhibit similar qualitative behavior: complete relaxation for nearest-neighbor impurities and incomplete or strongly delayed relaxation for next-nearest-neighbor impurities. The underlying mechanisms leading to this behavior differ between models and include impurity-induced bound states, emergent approximately conserved local observables, and exact cancellation of local and nonlocal dissipation effects. Published by the American Physical Society 2024

Impact and Mechanism of Medium and Small Flood Regulation in the Three Gorges Reservoir on the Phytoplankton in Tributary Bays

The regulation of small- and medium-sized floods （RSMF） has become the main mode of regulation in the flood season of the Three Gorges Reservoir （TGR）. To study the response of phytoplankton in the tributary bays of the TGR to the RSMF, a typical eutrophic tributary of the TGR, Xiangxi River, was investigated for the spatiotemporal distribution characteristics of phytoplankton and nutrients in the main and tributary streams from 2020 to 2021. The response characteristics of phytoplankton in the tributary bays to the RSMF were analyzed. The results indicated that during the RSMF, the chlorophyll a （Chl-a） in the water body of the Xiangxi River decreased with the increase in the water level in front of the dam, whereas during the reservoir impounding at the end of flood season, the concentration of Chl-a increased again. During the RSMF, the Chlorophyta and Diatoma were the main communities of planktonic algae in the Xiangxi River. The phytoplankton community changed with the RSMF. When the water level fluctuation increased, diatoms were the main species, whereas when the water level fluctuation was small, blue and green algae were the main species. The concentration of Chl-a was more sensitive to changes in TN concentration. When the flow velocity was >0.25 m·s-1 or the suspended sediment content was >10 mg·L-1, the concentration of Chl-a in the water was inhibited. After 2010, the typical outbreak time of algal blooms in the Xiangxi River Reservoir Bay shifted to the flood season, with only two non-flood season algal blooms. Further attention needs to be paid to the response of algal blooms in the reservoir to small- and medium-sized flood control during the flood season.

Optimization of saliva sampling methods for analysis of bile acids by UHPLC-MS

This study investigated methods for sampling bile acids in saliva, a potential non-invasive diagnostic biofluid. Bile acids have been implicated in causing damage and permanent changes to the esophageal mucosa and increasing the risk of developing Barrett's esophagus, a condition that can potentially progress to esophageal cancer. Three saliva collection methods were compared: spitting, Salivette® swabs, and Salivette Cortisol® swabs. Spitting emerged as the superior method with the highest recoveries and the least interference, likely due to Salivette swabs retaining bile acids or introducing unknown interferences. All saliva samples were analyzed by UHPLC-MS/MS using the Zorbax RRHD Eclipse Plus C18 column (3 × 50 mm, 1.8 µm) in gradient elution of 0.1 % formic acid in water and methanol. Saliva sample stability was assessed over 14 days, reflecting typical storage times. The levels of detected bile acids were stable for the measured period (RSD ≤ 22 %) and no degradation was observed. Bile acid levels in saliva fluctuated throughout the day, with the greatest changes observed for glycine-conjugated bile acids after meals. To minimize sampling variability, saliva collection by spitting after overnight fasting is recommended for future studies. Our findings are applicable for standardized bile acid sampling and are currently applied in a large clinical study evaluating bile acids as potential susceptibility markers for Barrett's esophagus diagnostics.

Real-time data processing in colorimetry camera-based single-molecule localization microscopy via CPU-GPU-FPGA heterogeneous computation.

Because conventional low-light cameras used in single-molecule localization microscopy (SMLM) do not have the ability to distinguish colors, it is often necessary to employ a dedicated optical system and/or a complicated image analysis procedure to realize multi-color SMLM. Recently, researchers explored the potential of a new kind of low-light camera called colorimetry camera as an alternative detector in multi-color SMLM, and achieved two-color SMLM under a simple optical system, with a comparable cross-talk to the best reported values. However, extracting images from all color channels is a necessary but lengthy process in colorimetry camera-based SMLM (called CC-STORM), because this process requires the sequential traversal of a massive number of pixels. By taking advantage of the parallelism and pipeline characteristics of FPGA, in this paper, we report an updated multi-color SMLM method called HCC-STORM, which integrated the data processing tasks in CC-STORM into a home-built CPU-GPU-FPGA heterogeneous computing platform. We show that, without scarifying the original performance of CC-STORM, the execution speed of HCC-STORM was increased by approximately three times. Actually, in HCC-STORM, the total data processing time for each raw image with 1024 × 1024 pixels was 26.9 ms. This improvement enabled real-time data processing for a field of view of 1024 × 1024 pixels and an exposure time of 30 ms (a typical exposure time in CC-STORM). Furthermore, to reduce the difficulty of deploying algorithms into the heterogeneous computing platform, we also report the necessary interfaces for four commonly used high-level programming languages, including C/C++, Python, Java, and Matlab. This study not only pushes forward the mature of CC-STORM, but also presents a powerful computing platform for tasks with heavy computation load.