Green upgrading of SPring-8 to produce stable, ultrabrilliant hard X-ray beams.

SPring-8-II is a major upgrade project of SPring-8 that was inaugurated in October 1997 as a third-generation synchrotron radiation light source. This upgrade project aims to achieve three goals simultaneously: achievement of excellent light source performance, refurbishment of aged systems, and significant reduction in power consumption for the entire facility. A small emittance of 50 pm rad will be achieved by (1) replacing the existing double-bend lattice structure with a five-bend achromat one, (2) lowering the stored beam energy from 8 to 6 GeV, (3) increasing the horizontal damping partition number from 1 to 1.3, and (4) enhancing horizontal radiation damping by installing damping wigglers in long straight sections. The use of short-period in-vacuum undulators allows ultrabrilliant X-rays to be provided while keeping a high-energy spectral range even at the reduced electron-beam energy of 6 GeV. To reduce power consumption, the dedicated, aged injector system has been shut down and the high-performance linear accelerator of SACLA, a compact X-ray free-electron laser (XFEL) facility, is used as the injector of the ring in a time-shared manner. This allows the simultaneous operation of XFEL experiments at SACLA and full/top-up injection of the electron beam into the ring. This paper overviews the concept of the SPring-8-II project, the system design of the light source and the details of the accelerator component design.

Ultralow Potential Cathodic Electrochemiluminescence Aptasensor for Detection of Kanamycin Using Copper Nanoribbons as Coreaction Accelerator.

An ultralow cathodic potential electrochemiluminescence (ECL) aptasensor was designed, employing DNA nanoribbon template self-assembly copper nanoclusters (DNR-CuNCs) as a novel coreaction accelerator within the luminol-H2O2 system for the sensitive detection of kanamycin (KANA). Mechanistic investigations revealed that the DNR-CuNCs preferred to generate highly active hydroxyl radicals by facilitating the reduction of the coreactant H2O2 under neutral pH conditions, consequently enhancing cathodic luminescence. By the strong π-π stacking effect of KANA aptamer and graphene as a signal modulation switch, DNR-CuNCs were displaced from the electrode surface due to the affinity of KANA and its aptamer, resulting in the inhibition of the luminol-H2O2 system and a decrease in the ECL signal. Under optimal experiments, the aptasensor demonstrated exceptional sensitivity in detecting KANA within the concentration range from 1 × 10-2 to 5 × 105 pg/mL, with the detection limit as low as 0.18 fg/mL. This innovative strategy provided a novel approach to designing effective ECL emitters for monitoring food safety.

LDF-BNN: A Real-Time and High-Accuracy Binary Neural Network Accelerator Based on the Improved BNext.

Significant progress has been made in industrial defect detection due to the powerful feature extraction capabilities of deep neural networks (DNNs). However, the high computational cost and memory requirement of DNNs pose a great challenge to the deployment of industrial edge-side devices. Although traditional binary neural networks (BNNs) have the advantages of small storage space requirements, high parallel computing capability, and low power consumption, the problem of significant accuracy degradation cannot be ignored. To tackle these challenges, this paper constructs a BNN with layered data fusion mechanism (LDF-BNN) based on BNext. By introducing the above mechanism, it strives to minimize the bandwidth pressure while reducing the loss of accuracy. Furthermore, we have designed an efficient hardware accelerator architecture based on this mechanism, enhancing the performance of high-accuracy BNN models with complex network structures. Additionally, the introduction of multi-storage parallelism alleviates the limitations imposed by the internal transfer rate, thus improving the overall computational efficiency. The experimental results show that our proposed LDF-BNN outperforms other methods in the comprehensive comparison, achieving a high accuracy of 72.23%, an image processing rate of 72.6 frames per second (FPS), and 1826 giga operations per second (GOPs) on the ImageNet dataset. Meanwhile, LDF-BNN can also be well applied to defect detection dataset Mixed WM-38, achieving a high accuracy of 98.70%.

LRMP: Layer Replication with Mixed Precision for spatial in-memory DNN accelerators.

In-memory computing (IMC) with non-volatile memories (NVMs) has emerged as a promising approach to address the rapidly growing computational demands of Deep Neural Networks (DNNs). Mapping DNN layers spatially onto NVM-based IMC accelerators achieves high degrees of parallelism. However, two challenges that arise in this approach are the highly non-uniform distribution of layer processing times and high area requirements. We propose LRMP, a method to jointly apply layer replication and mixed precision quantization to improve the performance of DNNs when mapped to area-constrained IMC accelerators. LRMP uses a combination of reinforcement learning and mixed integer linear programming to search the replication-quantization design space using a model that is closely informed by the target hardware architecture. Across five DNN benchmarks, LRMP achieves 2.6-9.3× latency and 8-18× throughput improvement at minimal (<1%) degradation in accuracy.

The Coordination of Aluminum Sulfate with a Water-Soluble Block Copolymer Containing Carboxyl, Amide, Sulfonic and Anhydride Groups Providing Both Accelerating and Hardening Effects in Cement Setting.

Two water-soluble block copolymers composed of acrylic acid (AA), 2-acrylamido-2-methylpropane sulfonic acid (AMPS), and optionally maleic anhydride (MAH) were synthesized through ammonium persulfate-catalyzed free radical polymerization in water. The introduction of aluminum sulfate (AS) into the resulting mixtures significantly reduced the setting times of the paste and enhanced the mechanical strength of the mortar compared to both the additive-free control and experiments facilitated solely by pure AS. This improvement was primarily attributed to the inhibition of rapid Al3+ hydrolysis, which was achieved through coordination of the synthesized block copolymers, along with the formation of newly identified hydrolytic intermediates. Notably, the ternary copolymer (AA-AMPS-MAH) exhibited superior performance compared to that of the binary copolymer (AA-AMPS). In the early stages of cement setting, clusters of ettringite (AFt) were found to be immobilized over newly detected linkage phases, including unusual calcium silicate hydrate and epistilbite. In contrast to the well-documented role of polymers in retarding cement hydration, this study presents a novel approach by providing both accelerating and hardening agents for cement setting, which has significant implications for the future design of cement additives.

Enhanced electrochemiluminescence of CdS QDs encapsulated in IRMOF-3 for sensitive detection of human epithelial protein 4.

The advancement of pragmatic and highly-sensitive electrochemiluminescence (ECL) biosensors depends upon signal tags with high and stable signal intensity. Herein, enhanced ECL emission was obtained by encapsulating the dual-stabilizer-capped CdS QDs in a metal-organic framework (MOF), which served as a valid ECL signal tag for detecting biomarkers. Dual-stabilizer-capped CdS QDs reduce dangling bonds on the surface and improved the ECL emission. Furthermore, functionalized isoreticular metal-organic framework-3 (IRMOF-3) can not only load a large quantity of CdS QDs through the encapsulation capability but also serves as a co-reaction accelerator to promote the formation of more SO4•- from the S2O82-, further improving the ECL emission of QDs, while the integrated design of IRMOF-3 co-reaction accelerator and CdS QDs effectively shortens the electron transfer pathway and reduces the energy consumption in ECL system. Using human epithelial protein 4 (HE4) as the model of analysis, the biosensor demonstrated a broad linear range (50 fg mL-1∼50 ng mL-1) and a low detection limit (9.89 fg mL-1) under optimal operating conditions. The study provides an effective and alternative method to improve the ECL efficiency of QDs, significantly broadening their potential applications in sensing analysis, medical diagnostics, and bioimaging.

A simple and efficient method for separation of 99mTc from 100Mo targets.

99mTc is regarded as the most important medical isotope, and its supply issues have garnered significant attention. A simple and efficient separation method was performed for the production of 99mTc from 100Mo target in this study. The entire process involves accelerator irradiation, 99mTc/100Mo separation, and target material recovery. The key aspect is separation process, which including the high-temperature conversion of metal molybdenum targets and the selective solution of 99mTc with normal saline. This method can separate highly pure 99mTc within 1.5 h, with a separation efficiency exceeding 80%. The reagents used in the separation process are minimal, resulting in less radioactive waste. Additionally, the target material is easy to reclaim, with a recovery rate of over 95%.

An analytical approach to optimization of isotope production by bremsstrahlung radiation.

Based on analytical description of isotope production by bremsstrahlung (X-ray) radiation, an algorithm is proposed for calculating the optimal dimensions of a cylindrical target of given mass positioned at a given distance from a bremsstrahlung converter to ensure the maximum yield of the isotope product. The expressions are derived for the total activity and its distribution along the target axis. A technique of γ-spectrometric measuring the activity of a thick production target is proposed. The novel approach is validated by the 100Mo(γ,n)99Mo reaction induced in a natural molybdenum target by mass in the range 10-100g with the X-ray photons at an end-point energy of 40 MeV. The analytical predictions are in good agreement with the results of Monte-Carlo simulations and experiment.

Meta-analysis accelerator: a comprehensive tool for statistical data conversion in systematic reviews with meta-analysis.

BACKGROUND: Systematic review with meta-analysis integrates findings from multiple studies, offering robust conclusions on treatment effects and guiding evidence-based medicine. However, the process is often hampered by challenges such as inconsistent data reporting, complex calculations, and time constraints. Researchers must convert various statistical measures into a common format, which can be error-prone and labor-intensive without the right tools. IMPLEMENTATION: Meta-Analysis Accelerator was developed to address these challenges. The tool offers 21 different statistical conversions, including median & interquartile range (IQR) to mean & standard deviation (SD), standard error of the mean (SEM) to SD, and confidence interval (CI) to SD for one and two groups, among others. It is designed with an intuitive interface, ensuring that users can navigate the tool easily and perform conversions accurately and efficiently. The website structure includes a home page, conversion page, request a conversion feature, about page, articles page, and privacy policy page. This comprehensive design supports the tool's primary goal of simplifying the meta-analysis process. RESULTS: Since its initial release in October 2023 as Meta Converter and subsequent renaming to Meta-Analysis Accelerator, the tool has gained widespread use globally. From March 2024 to May 2024, it received 12,236 visits from countries such as Egypt, France, Indonesia, and the USA, indicating its international appeal and utility. Approximately 46% of the visits were direct, reflecting its popularity and trust among users. CONCLUSIONS: Meta-Analysis Accelerator significantly enhances the efficiency and accuracy of meta-analysis of systematic reviews by providing a reliable platform for statistical data conversion. Its comprehensive variety of conversions, user-friendly interface, and continuous improvements make it an indispensable resource for researchers. The tool's ability to streamline data transformation ensures that researchers can focus more on data interpretation and less on manual calculations, thus advancing the quality and ease of conducting systematic reviews and meta-analyses.

Radiotherapy for painful shoulder syndrome: a retrospective evaluation.

PURPOSE: We evaluated the efficacy of low-dose radiotherapy for painful shoulder syndrome from an orthopedic perspective. METHODS: Patients with painful shoulder syndrome were recruited for this retrospective clinical quality assessment from January 2011 to December 2017. Patients were treated with a linear accelerator or an orthovoltage device at individual doses of 0.5-1.0 Gy and total doses of 3.0-6.0 Gy. To assess response, we used the von Pannewitz score with five levels: "worsened," "unaffected," "improved," "significantly improved," and "symptom free." "Good treatment success" was defined as "significantly improved" and "symptom free." Within-group and between-group differences were statistically evaluated. RESULTS: Of 236 recruited patients (150 women, 86 men; mean age 66.3 [range 31-96] years), 180 patients underwent radiotherapy with a linear accelerator and 56 with an orthovoltage device. Fractionation was 12â€¯× 0.5 Gy in 120 patients, 6â€¯× 0.5 Gy in 74, and 6â€¯× 1 Gy in 42 patients. Treatments were completed in one series for 223 and in two series at least 6 weeks apart for 13 patients. Of the 236 patients, 163 patients (69.1%) agreed to be re-interviewed at a median of 10.5 (range 4-60) months after radiotherapy completion. Directly after radiotherapy, 30.9% (73 patients) had "good treatment success," which had increased to 55.2% (90 patients) at follow-up. CONCLUSION: Protracted pain improvement with low-dose radiotherapy is possible in painful shoulder syndrome. Patients with refractory pain because of subacromial syndrome or shoulder osteoarthritis should also be evaluated for radiotherapy.

Explore the feasibility of using spot-scanning proton arc therapy for a synchrotron accelerator-based proton therapy system - A simulation study.

OBJECTIVE: The aim of this study was to evaluate the feasibility and plan quality of spot-scanning proton arc therapy (SPArc) using a synchrotron-accelerator-based proton therapy system compared to intensity-modulated proton therapy (IMPT). APPROACH: Five representative disease sites, including head and neck, lung, liver, brain chordoma, and prostate cancers, were retrospectively selected. Both IMPT and SPArc plans are generated with the HITACHI ProBEAT PBS system's minimum MU constraints and physics beam model. The SPArc plans are generated with 2.5° sampling frequency. The static delivery time was simulated based on the previously published synchrotron delivery sequence model, and the dynamic delivery time was simulated using a proton arc gantry mechanical model integrated with the synchrotron delivery sequence. Both dosimetric plan quality and delivery efficiency are evaluated. MAIN RESULTS: A superior plan quality is reached compared with the IMPT plans generated for the same disease site. However, a relatively prolonged static and dynamic delivery time post new challenge, as static time increased by 49.22% and dynamic time 59.10% on average. SIGNIFICANCE: This study presents the first simulation results of delivering the SPArc plans using a synchrotron-accelerated proton therapy system. The result shows its feasibility and limitations, which could guide future development.

Ultrasensitive Electrochemiluminescence Biosensor with ZIF-67@MXene as an Efficient Co-Reaction Accelerator and Plasmonic Nanozyme as a Smart Signal Amplification Probe.

Exploring novel electrochemiluminescence (ECL) co-reaction accelerators to construct ultrasensitive sensing systems is a prominent focus for developing advanced ECL sensors. However, challenges still remain in finding highly efficient accelerators and understanding their promoting mechanisms. In this paper, ZIF-67@MXene nanosheet composites, with highly conductive in-plane structure and confined-stable pore/channel, are designed to act as high-efficient co-reaction accelerators and achieve a significant enhancement in the luminol-H2O2 based ECL system. Mechanism investigation suggests that hydroxyl radicals (·OH) and singlet oxygen (1O2) can be selectively and preferentially generated on ZIF-67@MXene due to the stable and efficient absorption of ·OH and 1O2, leading to a remarkable enhancement in the ECL efficiency of luminol (830%). Finally, by designing a plasmonic NH2-MIL-88@Pd nanozyme, an "on-off" switch immunosensor is constructed for the detection of prostate-specific antigen (PSA). Based on the multiple signal amplification effect, the linear detection range for PSA is expanded by three orders of magnitude. The detection limit is also improved from 1.44 × 10-11 to 9.1 × 10-13 g mL-1. This work proposes an effective method for the preparation of highly efficient co-reaction accelerators and provides a new strategy for the sensitive detection of cancer markers.

Intermediate-grained kernel elements pruning with structured sparsity.

Neural network pruning provides a promising prospect for the deployment of neural networks on embedded or mobile devices with limited resources. Although current structured strategies are unconstrained by specific hardware architecture in the phase of forward inference, the decline in classification accuracy of structured methods is beyond the tolerance at the level of general pruning rate. This inspires us to develop a technique that satisfies high pruning rate with a small decline in accuracy and has the general nature of structured pruning. In this paper, we propose a new pruning method, namely KEP (Kernel Elements Pruning), to compress deep convolutional neural networks by exploring the significance of elements in each kernel plane and removing unimportant elements. In this method, we apply a controllable regularization penalty to constrain unimportant elements by adding a prior knowledge mask and obtain a compact model. In the calculation procedure of forward inference, we introduce a sparse convolution operation which is different from the sliding window to eliminate invalid zero calculations and verify the effectiveness of the operation for further deployment on FPGA. A massive variety of experiments demonstrate the effectiveness of KEP on two datasets: CIFAR-10 and ImageNet. Specially, with few indexes of non-zero weights introduced, KEP has a significant improvement over the latest structured methods in terms of parameter and float-point operation (FLOPs) reduction, and performs well on large datasets.

Long-term beam output stability of an accelerator-based boron neutron capture therapy system.

BACKGROUND: Accelerator-based boron neutron capture therapy (AB-BNCT) systems are becoming commercially available and are expected to be widely used in hospitals. To ensure the safety of BNCT, establishing a quality assurance (QA) program and properly managing the stability of the system are necessary. In particular, a high level of beam output stability is required to avoid accidents because beam output is a major factor in patient dose. However, no studies have analyzed the long-term beam output stability of AB-BNCT systems. PURPOSE: This study aimed to retrospectively analyze the long-term stability of the beam output by statistical process control (SPC) based on the QA results over 3 years. METHODS: The data analyzed are the results of daily QA (DQA) and weekly QA (WQA) in an AB-BNCT system and were taken between June 2020 and September 2023. The evaluation of the stability of the beam output was based on the reaction rate between gold and neutrons calculated using the activation foil method using a gold foil. In DQA, which can be performed in a short time, the gold foil was applied directly to the beam irradiation aperture in air. In WQA, measurements were performed at the phantom surface, 2-cm depth, and 6-cm depth using a dedicated water phantom. The acquired data were retrospectively analyzed by individuals and a moving range chart (I-MR chart), exponentially weighted moving average control chart (EWMA chart), and several process capability indexes (PCIs). RESULTS: Over 99% of the DQA I-MR chart results were within control limits, whereas the WQA I-MR chart results showed that 1.8%, 4.1%, and 2.0% of the measurements exceeded the control limits at the surface, 2-cm depth, and 6-cm depth, respectively. The variation in the reaction rate of the gold foil before and after the replacement of the target was <0.5%. The EWMA chart results revealed no significant beam output drift for either DQA or WQA. Most measured data were normal based on the results of the Anderson-Darling test and met the requirements for PCI evaluation; most PCI values were >1.0; however, the Cpmk of DQA and the 2- and 6-cm depth WQAs between August 2021 and November 2022 in treatment course 2 were 0.83, 0.77, and 0.87, respectively, which were <1.0. CONCLUSIONS: The long-term stability of beam output was confirmed using SPC in an AB-BNCT system. The results of the control chart revealed no significant variation or drift in the beam output, and the quantitative evaluation using PCI revealed high stability. A routine QA program will enable us to provide safe BNCT.

Integrated Amorphous Carbon Film Temperature Sensor with Silicon Accelerometer into MEMS Sensor.

Amorphous carbon (a-C) has promising potential for temperature sensing due to its outstanding properties. In this work, an a-C thin film temperature sensor integrated with the MEMS silicon accelerometer was proposed, and a-C film was deposited on the fixed frame of the accelerometer chip. The a-C film was deposited by DC magnetron sputtering and linear ion beam, respectively. The nanostructures of two types of films were observed by SEM and TEM. The cluster size of sp2 was analyzed by Raman, and the content of sp2 and sp3 of the carbon film was analyzed by XPS. It showed that the DC-sputtered amorphous carbon film, which had a higher sp2 content, had better temperature-sensitive properties. Then, an integrated sensor chip was designed, and the structure of the accelerometer was simulated and optimized to determine the final sizes. The temperature sensor module had a sensitivity of 1.62 mV/°C at the input voltage of 5 V with a linearity of 0.9958 in the temperature range of 20~150 °C. The sensitivity of the sensor is slightly higher than that of traditional metal film temperature sensors. The accelerometer module had a sensitivity of 1.4 mV/g/5 V, a nonlinearity of 0.38%, a repeatability of 1.56%, a total thermomechanical noise of 509 µg over the range of 1 to 20 Hz, and an average thermomechanical noise density of 116 µg/√Hz, which is smaller than the input acceleration amplitude for testing sensitivity. Under different temperatures, the performance of the accelerometer was tested. This research provided significant insights into the convenient procedure to develop a high-performance, economical temperature-accelerometer-integrated MEMS sensor.

An FPGA-Based YOLOv5 Accelerator for Real-Time Industrial Vision Applications.

The You Only Look Once (YOLO) object detection network has garnered widespread adoption in various industries, owing to its superior inference speed and robust detection capabilities. This model has proven invaluable in automating production processes such as material processing, machining, and quality inspection. However, as market competition intensifies, there is a constant demand for higher detection speed and accuracy. Current FPGA accelerators based on 8-bit quantization have struggled to meet these increasingly stringent performance requirements. In response, we present a novel 4-bit quantization-based neural network accelerator for the YOLOv5 model, designed to enhance real-time processing capabilities while maintaining high detection accuracy. To achieve effective model compression, we introduce an optimized quantization scheme that reduces the bit-width of the entire YOLO network-including the first layer-to 4 bits, with only a 1.5% degradation in mean Average Precision (mAP). For the hardware implementation, we propose a unified Digital Signal Processor (DSP) packing scheme, coupled with a novel parity adder tree architecture that accommodates the proposed quantization strategies. This approach efficiently reduces on-chip DSP utilization by 50%, offering a significant improvement in performance and resource efficiency. Experimental results show that the industrial object detection system based on the proposed FPGA accelerator achieves a throughput of 808.6 GOPS and an efficiency of 0.49 GOPS/DSP for YOLOv5s on the ZCU102 board, which is 29% higher than a commercial FPGA accelerator design (Xilinx's Vitis AI).

Cavity ionization chamber responses in the JAEA and the NMIJ high-energy photon reference fields for radiation protection.

A dosimeter should ideally be calibrated in a reference field with similar energy and doserate to that which the dosimeter is being used to measure. Environments around nuclear reactors and radiation therapy facilities have high-energy photons with energies exceeding that of60Co gamma rays, and controlling exposure to these photons is important. The Japan Atomic Energy Agency and National Metrology Institute of Japan have high-energy reference fields with energies above several megaelectronvolts for different types of accelerators. Their reference fields have different fluence-energy distributions. In this study, the energy dependencies of the two-cavity ionization chambers, which are often used by secondary standard laboratories, were experimentally and computationally evaluated for each high-energy field. These results agreed well within the relative expanded uncertainties (k= 2), and their capabilities for air kerma measurements in each high-energy reference field were confirmed. Therefore, the capabilities of the air-kerma measurements were verified in the two high-energy reference fields.

Design of a mixed material moderator in a beam-shaping assembly for proton accelerator-based boron neutron capture therapy.

Boron Neutron Capture Therapy is being promoted with the development of accelerator neutron sources, and many new accelerator-based BNCT facilities are being built. In Particle Accelerator Facility project of Sun Yat-sen University, we plan to build a terminal for BNCT research based on an 8 MeV, CW 3 mA proton accelerator. In this paper, we present a beam-shaping assembly for this proton accelerator with such low 24 kW beam power, using composite moderator materials composed of five elements: Mg, Al, F, O, and Li. The calculation result of FLUKA with ENDF/B and JENDL libraries shows that the epithermal neutron beam flux is 1.57×109n/cm2/s with the CW 3 mA proton beam. The fast neutron component and the gamma ray component under free-air condition are 1.49×10-13Gy∙cm2 and 8.12×10-14Gy∙cm2 respectively, in line with IAEA-TECDOC-1223 design recommendations. The thermal analysis shows that the maximum temperature of beryllium target is 706.5 K, and the structure materials of BSA do not melt.

Multifraction stereotactic radiotherapy utilizing inhomogeneous dose distribution for brainstem metastases: a single-center retrospective analysis.

Brainstem metastases are challenging to manage owing to the critical neurological structures involved. Although stereotactic radiotherapy (SRT) offers targeted high doses while minimizing damage to adjacent normal tissues, the optimal dose fractionation remains undefined. This study evaluated the efficacy and safety of multifraction SRT with an inhomogeneous dose distribution. This retrospective study included 31 patients who underwent 33 treatments for 35 brainstem lesions using linear accelerator-based multifraction SRT (30 Gy in five fractions, 35 Gy in five fractions or 42 Gy in 10 fractions) with an inhomogeneous dose distribution (median isodose, 51.9%). The outcomes of interest were local failure, toxicity and symptomatic failure. The median follow-up time after brainstem SRT for a lesion was 18.6 months (interquartile range, 10.0-24.3 months; range, 1.8-39.0 months). Grade 2 toxicities were observed in two lesions, and local failure occurred in three lesions. No grade 3 or higher toxicities were observed. The 1-year local and symptomatic failure rates were 8.8 and 16.7%, respectively. Toxicity was observed in two of seven treatments with a gross tumor volume (GTV) greater than 1 cc, whereas no toxicity was observed in treatments with a GTV less than 1 cc. No clear association was observed between the biologically effective dose of the maximum brainstem dose and the occurrence of toxicity. Our findings indicate that multifraction SRT with an inhomogeneous dose distribution offers a favorable balance between local control and toxicity in brainstem metastases. Larger multicenter studies are needed to validate these results and determine the optimal dose fractionation.

A national survey of medical staffs' required capability and workload for accelerator-based boron neutron capture therapy.

This study aimed to identify the required capabilities and workload of medical staff in accelerator-based boron neutron capture therapy (BNCT). From August to September 2022, a questionnaire related to the capabilities and workload in the accelerator-based BNCT was administered to 12 physicians, 7 medical physicists and 7 radiological technologists engaged in BNCT and 6 other medical physicists who were not engaged in BNCT to compare the results acquired by those engaged in BNCT. Only 6-21% of patients referred for BNCT received it. Furthermore, 30-75% of patients who received BNCT were treated at facilities located within their local district. The median required workload per treatment was 55 h. Considering additional workloads for ineligible patients, the required workload reached ~1.2 times longer than those for only eligible patients' treatment. With respect to capabilities, discrepancies were observed in treatment planning, quality assurance and quality control, and commissioning between medical physicists and radiological technologists. Furthermore, the specialized skills required by medical physicists are impossible to acquire from the experience of conventional radiotherapies as physicians engaged in BNCT were specialized not only in radiation oncology, but also in other fields. This study indicated the required workload and staff capabilities for conducting accelerator-based BNCT considering actual clinical conditions. The workload required for BNCT depends on the occupation. It is necessary to establish an educational program and certification system for the skills required to safely and effectively provide BNCT to patients.