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Ion microbeam technology and its applications at the TIARA facility of JAEA Takasaki were summarized. In 1990, R&D of microbeam technology for TIARA was initiated in order to use an ion beam for analysis, radiation effect studies, or fabrication by the micro or nanometer scale. Three different types of ion microbeam systems with high-spatial resolutions were constructed and techniques of micro-PIXE, single ion hit and particle beam writing (PBW) were developed and applied widely in science and technology. Superior performance of these microbeams, on the other hand, was based on the highest quality of beams from the accelerators, the cyclotron in particular, which were also an important part of the R&D at TIARA.

Analysis of trace element in coal fly ash has been brought to the attention of the general public in recent years primarily as it concerns in pollution problem with coal-fired power plants. Indian coal used in the thermal power plants has quite high content of ash (upto 55%). Therefore, in order to assess the environmental impact of the coal fuel cycle, coal fly ash samples from Captive Power Plant (CPP) of National Aluminium Company (NALCO) in Angul industrial area have been analysed for heavy elements by PIXE technique. Sample preparation procedures, experimental setup and spectrum analysis are discussed.

Not only in the field of high-performance computing (HPC), field programmable gate arrays (FPGAs) are a soaringly popular accelerator technology. However, they use a completely different programming paradigm and tool set compared to central processing units (CPUs) or even graphics processing units (GPUs), adding extra development steps and requiring special knowledge, hindering widespread use in scientific computing. To bridge this programmability gap, domain-specific languages (DSLs) are a popular choice to generate low-level implementations from an abstract algorithm description. In this work, we demonstrate our approach for the generation of numerical solver implementations based on the multigrid method for FPGAs from the same code base that is also used to generate code for CPUs using a hybrid parallelization of MPI and OpenMP. Our approach yields in a hardware design that can compute up to 11 V-cycles per second with an input grid size of 4096$\times$4096 and solution on the coarsest using the conjugate gradient (CG) method on a mid-range FPGA, beating vectorized, multi-threaded execution on an Intel Xeon processor.

History has shown that energetic particles can be useful for medical applications. From the time, in 1895 when Roentgen discovered X-rays, and in 1913 when Coolidge developed the vacuum X-ray tube, energetic particles have been an important tool for medicine. Development of the appropriate tool for effective and safe radiotherapy requires an in-depth understanding of the application and constraints. Various solutions are possible and choices must be analyzed on the basis of the suitability for meeting the requirements. Some of the requirements of charged particle therapy are summarized and various accelerator options are described and discussed.

About 30 years ago, I was among several students mentored by Professor Yang at Stony Brook to enter the field of particle accelerator physics. Since then, I have been fortunate to work on several major accelerator projects in USA and in China, guided and at times directly supported by Professor Yang. The field of accelerator physics is flourishing worldwide both providing indispensable tools for fundamental physics research and covering an increasingly wide spectrum of applications beneficial to our society.

In this paper, we have studied particle collision around a spinning dilaton black hole in 2 + 1 dimensions. This black hole is a solution to the low-energy string theory in 2 + 1 dimensions. Time-like geodesics are presented in detail and the center-of-mass (CM) energy of two-particle collision at the horizon of a spinning black hole is considered. We noticed that there is a possibility of the two masses to create infinite CM energy.

In this paper, we have studied particle collision around a rotating acoustic black hole in 2 + 1 dimensions. This black hole is analog to a fluid flow in a draining bath tub with a sink. Center of mass energy for two-particle collision at the horizon of the rotating acoustic black hole is considered. There is a possibility of the two-mass collision to create infinite center of mass energy for certain fine tuning of the parameters of the theory.

Given their 2.2 μs lifetime, muons must be accelerated fairly rapidly for a neutrino factory or muon collider. Muon bunches tend to be large. Progress in fixed field, alternating gradient (FFAG) lattices to meet these challenges are reviewed. FFAG magnets are naturally wide; low momentum muons move from the low field side of a gradient magnet to the high field side as they gain energy. This can be exploited to do double duty and allow a large beam admittance without unduly increasing the magnetic field volume. If the amount of RF must be reduced to optimize cost, an FFAG ring can accommodate extra orbits. I describe scaling FFAGs in which the bends in each magnet are energy independent and non-scaling FFAGs in which the bends in each magnet do vary with muon energy. In all FFAG designs the sum of the bends in groups of magnets are constant; otherwise orbits would not close. Ways of keeping the accelerating beam in phase with the RF are described. Finally, a 1 MeV proof of principle scaling FFAG has been built at KEK and began accelerating protons in June 2000 with a 1 kHz repetition rate.

This paper presents an overview of recent results from accelerator based neutrino experiments. We also review the status of experiments which are being planned for the near future. While most emphasis and interest of late is on neutrino oscillation experiments, we discuss non-oscillation experiments which will produce important results on cross sections.

Cancer is a dreadful disease that will affect one in three people at some point in their life; radiotherapy is used in more than half of all cancer treatment, and contributes about 40% to the successful treatment of cancer. Charged Particle Therapy uses protons and other light ions to deliver the lethal dose to the tumor while being relatively sparing of healthy tissue and, because of the finite range of the particles, is able to avoid giving any dose to vital organs. While there are adequate technologies currently available to deliver the required energies and fluxes, the two main technologies (cyclotrons and synchrotrons) have limitations. PAMELA (the Particle Accelerator for MEdicaLApplications) uses the newly-developed non-scaling Fixed Field Alternating Gradient accelerator concepts to deliver therapeutically relevant beams. The status of the development of the PAMELA conceptual design is discussed.

We report a detailed simulation of a bunched electron-beam accelerated in a TE${}_{113}$ cylindrical cavity immersed in a static inhomogeneous magnetic field using a relativistic full electromagnetic particle-in-cell (PIC). This type of acceleration concept is known as Spatial AutoResonance Acceleration (SARA) in which the magnetic field profile is such that it keeps the electron-beam in the acceleration regime along their trajectories. In this work, the numerical experiments are carried out including a bunched electron-beam with the concentrations in the range $10^8$–$10^9$cm${}^{-3}$ in a TE${}_{113}$ cylindrical microwave field, at a frequency of 2.45 GHz and an amplitude of 15 kV/cm. The electron energy reaches values up to 250 keV without significant unfocusing effect that can be used as a basis to produce hard X-ray. Additionally, a comparison between the data obtained from the full electromagnetic PIC simulations and the results derived from the relativistic Newton–Lorentz equation in a single particle approximation is carried out.

Dielectric Laser Acceleration (DLA) achieves the highest gradients among structure-based electron accelerators. The use of dielectrics increases the breakdown field limit, and thus the achievable gradient, by a factor of at least 10 in comparison to metals. Experimental demonstrations of DLA in 2013 led to the Accelerator on a Chip International Program (ACHIP), funded by the Gordon and Betty Moore Foundation. In ACHIP, our main goal is to build an accelerator on a silicon chip, which can accelerate electrons from below 100 keV to above 1 MeV with a gradient of at least 100 MeV/m. For stable acceleration on the chip, magnet-only focusing techniques are insufficient to compensate the strong acceleration defocusing. Thus, spatial harmonic and Alternating Phase Focusing (APF) laser-based focusing techniques have been developed. We have also developed the simplified symplectic tracking code DLAtrack6D, which makes use of the periodicity and applies only one kick per DLA cell, which is calculated by the Fourier coefficient of the synchronous spatial harmonic. Due to coupling, the Fourier coefficients of neighboring cells are not entirely independent and a field flatness optimization (similarly as in multi-cell cavities) needs to be performed. The simulation of the entire accelerator on a chip by a Particle In Cell (PIC) code is possible, but impractical for optimization purposes. Finally, we have also outlined the treatment of wake field effects in attosecond bunches in the grating within DLAtrack6D, where the wake function is computed by an external solver.

We show that the scattering of radiation on a traversable wormhole forms a vortex in the radiation energy flux. Then, if the wormhole possesses also a magnetic fields, the vortex accelerates charged particles along the magnetic lines and such a system works as an accelerator. If the vortex is small, the system reaches the stationary state, when the income of the kinetic energy reradiates completely in the form of the synchrotron radiation. Such a mechanism allows us to relate a part of observed sources of the synchrotron radiation to magnetic wormholes.

In rendering two-dimensional (2D) vector graphics, edge lists are often so large that their handling hinders the desired operation of portable devices. This paper proposes and evaluates an efficient edge-list handling method for a 2D vector graphics hardware accelerator. The proposed method selects edges that span the next scanline from among those spanning the current scanline and stores them in a small list in the internal memory. An edge list is assigned to each scanline and it stores only those edges that have not appeared in previous edge lists. Given that most active edges span only a few scanlines, the internal list can be small and implemented in the accelerator, whereas the edge lists are held in the external memory. Experimental results show that the proposed method can reduce external memory access by 23.4%–76.6% for the benchmark images considered compared to the prior methods.

Although the convolutional neural network (CNN) has exhibited outstanding performance in various applications, the deployment of CNN on embedded and mobile devices is limited by the massive computations and memory footprint. To address these challenges, Courbariaux and co-workers put forward binarized neural network (BNN) which quantizes both the weights and activations to $\pm$1. From the perspective of hardware, BNN can greatly simplify the computation and reduce the storage. In this work, we first present the algorithm optimizations to further binarize the first layer and the padding bits of BNN; then we propose a fully binarized CNN accelerator. With the Shuffle–Compute structure and the memory-aware computation schedule scheme, the proposed design can boost the performance for feature maps of different sizes and make full use of the memory bandwidth. To evaluate our design, we implement the accelerator on the Zynq ZC702 board, and the experiments on the SVHN and CIFAR-10 datasets show the state-of-the-art performance efficiency and resource efficiency.

Convolutional neural network (CNN) is one of the most promising algorithms that outweighs other traditional methods in terms of accuracy in classification tasks. However, several CNNs, such as VGG, demand a huge computation in convolutional layers. Many accelerators implemented on powerful FPGAs have been introduced to address the problems. In this paper, we present a VGG-based accelerator which is optimized for a low-cost FPGA. In order to optimize the FPGA resource of logic element and memory, we propose a dedicated input buffer that maximizes the data reuse. In addition, we design a low resource processing engine with the optimal number of Multiply Accumulate (MAC) units. In the experiments, we use VGG16 model for inference to evaluate the performance of our accelerator and achieve a throughput of 38.8GOPS at a clock speed of 150MHz on Intel Cyclone V SX SoC. The experimental results show that our design is better than previous works in terms of resource efficiency.

In recent decades, convolutional neural network (CNN) has become essential in many real-time applications due to its massive computational ability. But its use in portable devices is limited due to its high computation requirements. This paper proposes a novel One-Pass Processing Element (OPPE) to mitigate this limitation. The proposed OPPE removes redundant computations by eliminating those with zeros that leads to low area as well as low power consumption. The proposed OPPE model is evaluated with the help of VGG-16-based CNN accelerator. The proposed OPPE design reduces the number of four-input LUTs by 5.19%, 15.91%, 10.06% and 4.93% and the power consumption by 4.26%, 7.36%, 5.81% and 1.55% when compared with the conventional processing element (PE), activation gating PE, weight gating PE and zero gating PE, respectively. The proposed CNN accelerator design using OPPE achieves high throughput with less resource utilization.

The Facility for Rare Isotope Beams (FRIB) Project has entered the phase of beam commissioning starting from the room-temperature front end and the superconducting linac segment of first 15 cryomodules. With the newly commissioned helium refrigeration system supplying 4.5K liquid helium to the quarter-wave resonators and solenoids, the FRIB accelerator team achieved the sectional key performance parameters as designed ahead of schedule accelerating heavy ion beams above 20MeV/u energy. Thus, FRIB accelerator becomes world’s highest-energy heavy ion linear accelerator. We also validated machine protection and personnel protection systems that will be crucial to the next phase of commissioning. FRIB is on track towards a national user facility at the power frontier with a beam power two orders of magnitude higher than operating heavy-ion facilities. This paper summarizes the status of accelerator design, technology development, construction, commissioning as well as path to operations and upgrades.

The following topics are under this section:

• Boston-based Singapore start-up gains FDA approval for AI-powered analytics engine for physiological monitoring
• Singapore’s first private co-working laboratory and office space
• Research partnership between Bayer and RIKEN innovation to boost drug discovery opportunities
• Digital healthcare company concludes initial round of training for licensed doctors to practice telemedicine in Southeast Asia.
• Australia’s largest start-up accelerator becomes Singapore’s first HealthTech accelerator
• Gilead Sciences, Inc. announces Biktarvy^® is now available via the National Health Insurance scheme in Taiwan
• Actinogen Medical demonstrates novel approach to treating cognitive impairment
• Singapore-based MedTech company announced as winner of 2019 Asia Pacific Showcase Competition at The MedTech Forum
• Three-dimensional model of blood vessel “on-a-chip”

About 80 years ago Rutherford [1] expressed the hope that particles could be accelerated to energies exceeding those occurring in radioactivity, enabling the study of nuclei and their constituents. Physicists and engineers have more than met this challenge, and today the LHC (Large Hadron Collider) at CERN, Geneva is about to accelerate protons to 7 trillion (7 × 10¹²) eV. Here we describe some of the crucial steps that have gotten us there.