Intensive Part Research Articles

Spatiotemporal shaping of high power laser pulses based on stimulated brillouin scattering

We proposed and numerically demonstrated the combination of temporal and spatial shaping of high power nanosecond laser pulses based on stimulated Brillouin scattering (SBS) in this paper. With the intensity-dependence characteristic of SBS, the higher intensity parts of the laser beam obtain higher reflectivity, and the incident non-uniform high power laser beam would be well smoothed. A parameter adjustable feedback control loop was used to tailor the output temporal profile by pre-compensating the temporal profile of the input pump. In our numerical simulation, a 3 ns super-Gaussian shaped single-frequency laser pulse with a 527 nm wavelength was used as the pump. And the heavy fluorocarbon FC-70 was chosen as the Brillouin medium. Simulation results show that the laser spatial modulation can be significantly pulled down when the energy efficiency is maintained above 90% in our beam smoothing system with suitable laser intensity. The flat-toped laser pulses both in temporal and spatial domain were demonstrated to be achievable simultaneously. The method proposed here paves a simple and effective way to optimizing the near field pattern and temporal shape of high power laser systems.

Highly Integrated Cladding Mode Stripper Array for Compact High-Power Industrial Fiber Laser.

A design integrating multiple cladding mode strippers used in fiber laser architectures into a single device is proposed. This approach can increase the compactness of fiber lasers, thus contributing to industrial laser processing applications. By offset-placing the most intense light-stripping parts, for instance, by inversing the laser injection directions or by displacing the beginning of etched sections, multiple cladding mode strippers bundled together into a single housing can have the hottest regions separated and can operate at full power simultaneously, with no evident cross-influence on each other. Two and three cladding-mode-stripper arrays have been implemented, and validation tests have been conducted with ~500-W cladding power being injected into each input port. For both arrayed devices, compared to the scenario in which only a single cladding mode stripper is working, no greater than a 2.1 °C temperature increment is generated when all components are operating concurrently, which demonstrates the effectiveness of the integration method. In this way, one half and two thirds of space/weight reduction can be realized, respectively, for the two and three cladding-mode-stripper arrays, which is meaningful, since cladding mode strippers are among the most bulky and hottest components in fiber lasers. Moreover, this integration provides a valuable reference for the miniaturization of other components, and thus, could contribute to the development fiber lasers with higher power-to-volume ratios, which would be more economical for industrial applications.

Observations of a Solar Energetic Particle Event From Inside and Outside the Coma of Comet 67P.

We analyze observations of a solar energetic particle (SEP) event at Rosetta's target comet 67P/Churyumov-Gerasimenko during 6-10 March 2015. The comet was 2.15AU from the Sun, with the Rosetta spacecraft approximately 70km from the nucleus placing it deep inside the comet's coma and allowing us to study its response. The Eastern flank of an interplanetary coronal mass ejection (ICME) also encountered Rosetta on 6 and 7 March. Rosetta Plasma Consortium data indicate increases in ionization rates, and cometary water group pickup ions exceeding 1keV. Increased charge exchange reactions between solar wind ions and cometary neutrals also indicate increased upstream neutral populations consistent with enhanced SEP induced surface activity. In addition, the most intense parts of the event coincide with observations interpreted as an infant cometary bow shock, indicating that the SEPs may have enhanced the formation and/or intensified the observations. These solar transient events may also have pushed the cometopause closer to the nucleus. We track and discuss characteristics of the SEP event using remote observations by SOHO, WIND, and GOES at the Sun, in situ measurements at Solar Terrestrial Relations Observatory Ahead, Mars and Rosetta, and ENLIL modeling. Based on its relatively prolonged duration, gradual and anisotropic nature, and broad angular spread in the heliosphere, we determine the main particle acceleration source to be a distant ICME which emerged from the Sun on 6 March 2015 and was detected locally in the Martian ionosphere but was never encountered by 67P directly. The ICME's shock produced SEPs for several days which traveled to the in situ observation sites via magnetic field line connections.

Optimization of a line detection algorithm for autonomous vehicles on a RISC-V with accelerator

In recent years, autonomous vehicles have attracted theattention of many research groups, both in academiaand business, including researchers from leading com-panies such as Google, Uber and Tesla. This type ofvehicles are equipped with systems that are subjectto very strict requirements, essentially aimed at per-forming safe operations –both for potential passengersand pedestrians– as well as carrying out the process-ing needed for decision making in real time. In manyinstances, general-purpose processors alone cannotensure that these safety, reliability and real-time re-quirements are met, so it is common to implementheterogeneous systems by including accelerators. Thispaper explores the acceleration of a line detection ap-plication in the autonomous car environment using aheterogeneous system consisting of a general-purposeRISC-V core and a domain-specific accelerator. In par-ticular, the application is analyzed to identify the mostcomputationally intensive parts of the code and it isadapted accordingly for more efficient processing. Fur-thermore, the code is executed on the aforementionedhardware platform to verify that the execution effec-tively meets the existing requirements in autonomousvehicles, experiencing a 3.7x speedup with respect torunning without accelerator.

(Invited) Resolving a Catalytic Mechanism on an Electrode Surface: Using Time Resolution to Identify Theoretical Descriptors

Catalytic mechanisms at electrode surfaces guide the development of electrochemically controlled energy storing reactions and chemical synthesis. The intermediate steps of these mechanisms are challenging to identify experimentally but are critical to understanding the speed, stability, and selectivity of product evolution for a given energy input. One of the most studied reactions is the water-splitting reaction which breaks apart H2O into H2 and O2. In the laboratory group, we employ time-resolved optical and vibrational spectroscopy to deconstruct the energy intensive part, the oxygen evolution reaction (OER), into its component parts. The first step of this oxidative reaction, which is to release a proton and take an electron from water, has often been thought of as a theoretical “descriptor” that differentiates the OER activity of materials: if this is hard to do, then the material is less energy efficient and if it is easy to do, then a later, bond-forming step limits the energy efficiency. Yet, the formation free energy of this step had yet to be measured experimentally. Here, I will begin by summarizing the work done previously by the group: the structure and kinetics of forming these first reaction intermediates (Ti-OH*) by their optical and vibrational signatures upon driving OER with an ultrafast photo-trigger of the electrode surface (SrTiO3). I will then discuss the most recent work, which shows that by separating the reaction steps in time and optically detecting these intermediates created upon hole-transfer from the valence band, we can determine their formation free energy1. In addition to the optical spectroscopy, we employ reaction isotherm methodology borrowed from surface studies of reactions. By tuning the pH, we obtain a Langmuir isotherm on the driven surface (Figure 1) regulated by the proton transfer that increases surface hydroxylation for higher pH prior to photo-triggering OER. From the midpoint of this isotherm, one can obtain the formation free energy of Ti-OH* from valence band holes. Such an application of isotherms is new in that the product is not the final one, for which one generally knows the reaction free energy, but rather an intermediate of a reaction. Overall, the innovation of the work is to utilize kinetic measurements to obtain the calculated free energy of an intermediate reaction step at a material surface. 1I. Vinogradov, S. Singh, H. Lyle, M. Paolino, A. Mandal*, J. Rossmeisl, T. Cuk *, Nature Materials, 2022, 21, 88.Figure 1: The time-resolved optical data as a function of pH show how the population of intermediates generates a reaction isotherm (black trace). The emission (in blue) counts the intermediate Ti-OH* population. Figure 1

Belief-Propagation-Based Low-Complexity Channel Estimation and Detection for Underwater Acoustic Communications With Moving Transceivers

Achieving reliable communications with low complexity is challenging for underwater acoustic communications with moving transceivers, where the time-varying channels need to be estimated and tracked accurately and data detection needs to be performed with low complexity. In this article, with the use of a superimposed training (ST) scheme, we address this challenge by developing a low-complexity channel estimation and tracking algorithm, which is then integrated with low-complexity data detection in the frequency domain. ST is used to acquire improved channel-tracking capability. Based on belief propagation, we design a message-passing-based low-complexity bidirectional channel estimation (LCE-MP) algorithm, where all computational intensive parts are handled by the fast Fourier transform (FFT) algorithm, thereby achieving very efficient implementation with logarithmic complexity. Specifically, a message-passing-based fast information collection algorithm is presented to acquire “local” channel estimates, followed by the fusion of local channel estimates to achieve a “global” estimate of the channel. It is shown that the computational complexity per channel tap is only in a logarithmic level for the channel estimation and tracking. Moreover, the ST-scheme-based LCE-MP algorithm is combined with FFT-based data detection and decoding, which are performed in an iterative manner. The overall complexity of channel estimation and data detection is in a logarithmic level, and the system delivers excellent performance thanks to the joint processing. Field experiments were carried out in Jiaozhou Bay in 2019, and the experimental results verify the effectiveness of the proposed technique.

Mid-infrared chalcogenide slot waveguide plasmonic resonator sensor embedded with Au nanorods for surface-enhanced infrared absorption spectroscopy

The problem of a traditional waveguide plasmonic resonator sensor is that part of the near-field intensity enhanced area is confined in the waveguide dielectric layer, which decreases the interaction effect between light and analyte. In order to solve this problem, a novel mid-infrared (MIR) chalcogenide (ChG) slot waveguide plasmonic resonator (SWGPR) sensor embedded with Au nanorods was proposed, where Au nanorods were used as antenna for enhancing mode coupling with the waveguide through resonance at the absorption wavelength of the analyte. The antenna parameters were optimized to make the resonance wavelength align with the absorption wavelength of the analyte. The proposed waveguide structure provides a sufficient sensing area and increases the electric field enhancement factor to > 6400. Polymethyl methacrylate (PMMA) and styrene were adopted as the analyte for sensing performance evaluation. The normalized absorption reaches 23.31 when the maximum extinction coefficient of PMMA is 0.08, which is at least 7 times higher than other silicon-on-insulator (SOI) waveguide plasmonic resonator sensors. The proposed waveguide structure provides a new idea for the design of other waveguide plasmonic resonator sensors with high sensing performance and has the potential for biochemical sensing.

FastQSL: A Fast Computation Method for Quasi-separatrix Layers

Magnetic reconnection preferentially takes place at the intersection of two separatrices or two quasi-separatrix layers, which can be quantified by the squashing factor Q, whose calculation is computationally expensive due to the need to trace as many field lines as possible. We developed a method (FastQSL) optimized for obtaining Q and the twist number in a 3D data cube. FastQSL utilizes the hardware acceleration of the graphics processing unit and adopts a step-size adaptive scheme for the most computationally intensive part: tracing magnetic field lines. As a result, it achieves a computational efficiency of 4.53 million Q values per second. FastQSL is open source, and user-friendly for data import, export, and visualization.

Generation of collimated vortex gamma-rays from intense Poincaré beam–plasma interaction

We report on numerical calculations in which a multi-petawatt γ-ray beam is generated using a novel configuration based on fully structured light irradiating an overdense plasma waveguide. We analyze how the relativistic laser pulse efficiently confines and accelerates plasma electrons to GeV-scale energies and drives a quasi-static field that induces magneto-bremsstrahlung radiation. Multiphoton Compton scattering of electrons in the intense part of the laser also occurs although the radiated energy-density is comparatively lower. The emitted γ-rays carry orbital angular momentum, are highly collimated, and account for upwards of 15% of the incident field energy in one particular case. A comparison of the laser-to-particle angular momentum and energy transfer efficiencies is made between the cases of irradiation by a circularly polarized Laguerre–Gauss mode and one type of full Poincaré beam, and it is found that the latter yields an order-of-magnitude enhancement. The essential characteristics of the interaction are validated with three-dimensional particle-in-cell simulations that include quantum electrodynamical effects.

Solving Electromagnetic Scattering Problems With Tens of Billions of Unknowns Using GPU Accelerated Massively Parallel MLFMA

In this article, a massively parallel approach of the multilevel fast multipole algorithm (PMLFMA) on graphics processing unit (GPU) heterogeneous platform, noted as GPU-PMLFMA, is presented for solving extremely large electromagnetic scattering problems involving tens of billions of unknowns, In this approach, the flexible and efficient ternary partitioning scheme is employed at first to partition the MLFMA octree among message-passing interface (MPI) processes. Then, the computationally intensive parts of the PMLFMA on each MPI process, matrix filling, aggregation and disaggregation, and so on are accelerated by using the GPU. Different parallelization strategies in coincidence with the ternary parallel MLFMA approach are designed for GPU to ensure high computational throughput. Special memory usage strategy is designed to improve computational efficiency and benefit data reusing. The CPU/GPU asynchronous computing pattern is designed with the OpenMP and compute unified device architecture (CUDA), respectively, for accelerating the CPU and GPU execution parts and computation time overlapped. GPU architecture-based optimization strategies are implemented to further improve the computational efficiency. Numerical results demonstrate that the proposed GPU-PMLFMA can achieve over three times speedup, compared with the eight-threaded conventional PMLFMA. Solutions of scattering by electrically large and complicated objects with about 24 000 wavelengths and over 41.8 billion unknowns are presented.

Education and Radicalization; Is There Any Causative Relationship? A Case Study of Pakistan

The concept of radicalization has remained an intense part of human history. The features of this process are significant to understand human behaviour and encountering the social construction of any society. Several studies suggest that radicalization or extremism can be described as violent expressions, manifesting in the shape of extreme views, ideology or acts of violence against any individual, community, sect or even country. For this, several countries have spent substantial financial resources to pledge such threats and a spate of legislation to safeguard their respective national security. Research into radicalization, unfortunately, does not pay much consideration to education. This is extraordinary and may also, possibly, misses an important effect on the process of radicalization. Therefore, this study establishes a cognitive approach towards this term and examines whether radicalization has any linkage or causative relations with education as well. For this study, we have borrowed different denotations and connotations of radicalization and education by numerous scholars to determine the interconnectivity between radicalization and education. After going through existing the literature review, we establish that radicalization and education have strong connections. Education, be that formal or informal, can be used as an extensive tool to radicalize youth anywhere in the world. In this regard, we have studied Pakistan’s history vis-à-vis its education system in religious seminaries and public schools. We determine that the government of Pakistan has accepted the reality that its education system at the public schools and Madrassahs have remained an instrument to radicalize the youth in the country, which has raised fear for the internal security of Pakistan and for global security as well. In the end, we suggest that despite numerous steps by the Government of Pakistan, the international community must come up to assist Pakistan in terms of revitalizing its overall education system vis-à-vis curriculum changes to evade any further (emerging) extremism, which is rooted through radical textbooks at the public schools.

Increasing the efficiency of computer-aided design of documentation for testing, diagnostics and repair of replaceable elements of radio electronic equipment

The article is devoted to increasing the efficiency of field repair of samples of weapons and military equipment (WME) of air defence (AD), in particular – field repair of structural replaceable elements (SRE) of radio electronic equipment (REE) using interactive electronic repair manuals (IERM). Repair of REE SRE makes up a significant part of the total labour intensity of field repair of WME samples.

Novel Self-Adaptive Shale Gas Production Proxy Model and Its Practical Application.

Recently, production optimization has gained increasing interest in the petroleum industry. The most computationally intensive and critical part of the production optimization process is the evaluation of the production function performed by the numerical reservoir simulator. Employing proxy models as a substitute for the reservoir simulator is proposed for alleviating this high computational cost. In this study, a new approach to construct adaptive proxy models for production optimization problems is proposed. An adaptive difference evolution algorithm (SaDE) optimized least-squares support vector machine (LSSVM) is used as an approximation function, while training is performed using a self-adaptive response surface experimental design (SaRSE). SaDE selects the optimal hyperparameters of LSSVM during the training process to improve the prediction accuracy of the proxy model. Cross-validation methods are used in the recursive training and network evaluation phases. The developed method is used to optimize the production of block gas reservoir models. Computational results confirm that the developed adaptive proxy model outperforms traditional regression methods. It is further verified that when the experimental data are updated, the alternative model still has high prediction accuracy when performing the objective function evaluation. The results show that the proposed proxy modeling approach enhances the entire optimization process by providing a fast approximation of the actual reservoir simulation model with better accuracy.

Spectroscopic diagnostic of oscillating electric fields in edge plasmas

AbstractThe changes of plasma radiative properties in the presence of oscillating electric fields can be used for a diagnostic of the electric fields in the edge plasma. We present the modelling of hydrogen line shapes emitted in edge plasmas where powerful radio frequency (RF) waves are launched. RF waves are used for plasma heating and current drive, and understanding the details of their coupling to the plasma is an important issue in tokamak physics. Our model relies on a computer simulation of the plasma microfield and retains the emitter quantum evolution by solving numerically the Schrödinger equation. We calculate Lyman and Balmer lines of hydrogen in conditions where a significant part of the central intensity is transferred to satellite components under the simultaneous effects of the oscillating field and stochastic plasma microfield.

>50 MW peak power, high brightness Nd:YAG/Cr4+:YAG microchip laser with unstable resonator.

We demonstrated a flat-convex unstable cavity Nd:YAG/Cr4+:YAG ceramic air-cooled microchip laser (MCL) generating a record 37.6 and 59.2 MW peak power pulses with an energy of 17.0 and 24.1 mJ and a width of 452 and 407 ps at 20 Hz by using a uniform power square and hexagon pump, respectively. For hexagon pump, the near field hexagon donut beam was changed in to a Bessel-like beam in far field, whose beam quality was estimated as 2nd moment M2 of 7.67. The brightness scale of unstable resonator MCL was achieved up to 88.9 TW/(sr·cm2) in contrast with flat-flat cavity MCL. However, the high intense center part of Bessel-like beam increased its brightness effectively more than 8 times, up to 736 TW/(sr·cm2).

Recognition of gasoline in fire debris using machine learning: Part II, application of a neural network

The recognition of ignitable liquid (IL) residues in fire debris is a resource intensive but key part of an arson investigation. Due to the highly diverse and heavily loaded chemical matrix of fire debris samples, combined with the broad chemical composition of IL, the interpretation of the laboratory analysis results is a very challenging task for the forensic examiner. Fire debris samples are commonly analyzed using gas chromatography coupled to mass spectrometry (GC-MS). This method delivers both the total ion chromatogram (TIC) with the individually separated compounds and the underlying mass spectrum of each of the separated compounds. In this study, a completely new approach for the recognition of gasoline in fire debris samples is presented. First, the GC-MS data, including retention time, signal intensity, and mass spectrum is converted into a bitmap image. Five different data-to-image conversion approaches are tested, and their advantages and limitations are discussed. Subsequently, a convolutional neural network (CNN) is utilized to allocate the generated images to the classes “with gasoline” or “without gasoline”. The applied approaches to generate a digital image and the pattern recognition of the CNN perform very well in the classification of unknown test samples. Depending on the data-to-image generation approach used, the rate of correct sample classification in the test dataset is between 95% and 98%. The machine learning approach in this study, as well as the complementary method presented in an accompanying article, are not only useful for the recognition of gasoline in fire debris but are equally applicable to any additional areas in which the interpretation of complex chromatographic and mass spectrometric is required.

On computing the similarity of trapezoidal fuzzy sets using an Automated Area Method

This paper provides a new Automated Area Method (AAM) for computing the Jaccard similarity of non-normal trapezoidal fuzzy sets (with triangles and rectangles as special cases), needed, e.g. in XAI for rule-based fuzzy systems, Computing With Words using the Perceptual Computer, Perceptual reasoning, etc. The most intensive part of the Jaccard similarity computation is computing the area under the minimum of two fuzzy sets. The AAM does this very efficiently by initially using figures for the 40 possible cases of the minimum of two non-normal trapezoidal type-1 FSs, and by then providing area formulas for each of them using simple geometry. Flowcharted algorithms are then provided for automatically determining which of the 40 cases one is in, which do not need any figures, and only need the coordinates of the vertices of the two non-normal trapezoidal type-1 FSs. Examples are provided that illustrate these new results, both for type-1 and interval type-2 FSs. The AAM can also be used to compute other similarity measures and to compute the subsethood between fuzzy sets.

The Paradigmatic and Syntagmatic Priming Effect of Part of Speech Representation

Part of speech feature is the representation between syntactic morphology and semantic category. Priming effect experiment can test the correlation between the parts of speech feature and the lexical processing process. This article puts forward part of speech representation paradigmatic and syntagmatic effect hypotheses. The experiments applied the design pattern of 3 (part of speech: noun by predicate by nonword) ∗ 2 (interval time: 50 by 500 milliseconds) ∗3 (English level: elementary by intermediate by advanced). Subjects are requested to make options of the part of speech of the target words. This study shows that when Chinese English learners extract an individual word, their choices are still influenced by part of speech factor without the restrictions of constructive syntagmatic semantic conditions. Both the syntagmatic and paradigmatic effects are verified. Part of speech priming effect intensity is influenced by the English acquisition levels of the subjects.

Značaj gajenja združenih usjeva povrtarskih biljaka u zaštiti od štetočina

Vegetable production is one the most intensive and profitable parts of agricultural production, which is manifested in the level of yield per area unit, output, net profit and participation of human work. During the vegetation period, vegetable plants are exposed to the attack of numerous harmful organisms (pests, diseases, weeds, etc.) that can completely compromise vegetable production. Except of insects, which make up the most numerous group of pests, vegetables are damaged by mites, nematodes, snails, rodents and birds. The insects species from different orders: Hemiptera, Thysanoptera, Coleoptera, Lepidoptera and Diptera, damage above organs and underground parts of vegetable plants, often causing their complete decay, especially if the number of species has increased. In order to preserve the environmental conservation and human health, it is necessary to apply the concept of integrated pest control, which includes the application of chemical measures only when necessary, in a way that preserves natural enemies and pollutes the environment as little as possible. In this regard, the aim is to find different methods and ways of growing vegetables to reduce pest infestation, where mixed cropping or consociations of different vegetables and vegetables together with medicinal plants has many advantages. The most important of that is less exposure and reduced pest attack due to the positive interaction of cultivated plants.

FPGA Acceleration of 3GPP Channel Model Emulator for 5G New Radio

The channel model is by far the most computing intensive part of the link level simulations of multiple-input and multiple-output (MIMO) fifth-generation new radio (5G NR) communication systems. Simulation effort further increases when using more realistic geometry-based channel models, such as the three-dimensional spatial channel model (3D-SCM). Channel emulation is used for functional and performance verification of such models in the network planning phase. These models use multiple finite impulse response (FIR) filters and have a very high degree of parallelism which can be exploited for accelerated execution on Field Programmable Gate Array (FPGA) and Graphics Processing Unit (GPU) platforms. This paper proposes an efficient re-configurable implementation of the 3rd generation partnership project (3GPP) 3D-SCM on FPGAs using a design flow based on high-level synthesis (HLS). It studies the effect of various HLS optimization techniques on the total latency and hardware resource utilization on Xilinx Alveo U280 and Intel Arria 10GX 1150 high-performance FPGAs, using in both cases the commercial HLS tools of the producer. The channel model accuracy is preserved using double precision floating point arithmetic. This work analyzes in detail the effort to target the FPGA platforms using HLS tools, both in terms of common parallelization effort (shared by both FPGAs), and in terms of platform-specific effort, different for Xilinx and Intel FPGAs. Compared to the baseline general-purpose central processing unit (CPU) implementation, the achieved speedups are 65X and 95X using the Xilinx UltraScale+ and Intel Arria FPGA platform respectively, when using a Double Data Rate (DDR) memory interface. The FPGA-based designs also achieved ~3X better performance compared to a similar technology node NVIDIA GeForce GTX 1070 GPU, while consuming ~4X less energy. The FPGA implementation speedup improves up to 173X over the CPU baseline when using the Xilinx UltraRAM (URAM) and High-Bandwidth Memory (HBM) resources, also achieving 6X lower latency and 12X lower energy consumption than the GPU implementation.