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The hydration processes of Portland cements (PC) and blends are complicated as there are many components with great heterogeneity at different length scales. Thus, 3D nanoimaging techniques with high spatial resolution and scanning large fields of view are needed. Here, synchrotron X-ray near-field ptychographic tomography is used to investigate four pastes within 0.2 mm thick capillaries: PC with CaCl 2 , PC hydration enhanced by C-S-H nucleation seeding, PC partly substituted with metakaolin, and PC partly substituted with metakaolin and limestone. Data analysis emphasis has been placed on the characterization of amorphous components: (i) C-S-H and C-A-S-H gels; (ii) iron aluminium siliceous hydrogarnets; (iii) metakaolin; and (iv) aluminium carboaluminate, AFm-like. Synchrotron ptychotomography yields electron density and absorption coefficient tomograms and the resulting bivariate plots are instrumental for characterising these amorphous components. The attained spatial resolution, ∼220 nm, with very good contrast allowed us to determine nanofeatures including mass densities and spatial distributions of amorphous components. For instance, the C-S-H gel mass density differences between the two type of accelerated pastes are detailed. [ABSTRACT FROM AUTHOR]

Deep Neural Networks (DNNs) have gained widespread adoption in various fields; however, their computational cost is often prohibitively high due to the large number of layers and neurons communicating with each other. Furthermore, DNNs can consume a significant amount of energy due to the large volume of data movement and computation they require. To address these challenges, there is a need for new architectures to accelerate DNNs. In this paper, we propose novel neuron grouping and mapping methods for 2D-mesh Network-on-Chip (NoC)-based DNN accelerators considering both fully connected and partially connected DNN models. We present Integer Linear Programming (ILP) and simulated annealing (SA)-based neuron grouping solutions with the objective of minimizing the total volume of data communication among the neuron groups. After determining a suitable graph representation of the DNN, we also apply ILP and SA methods to map the neurons onto a 2D-mesh NoC fabric with the objective of minimizing the total communication cost of the system. We conducted several experiments on various benchmarks and DNN models with different pruning ratios and achieved an average of 40-50% improvement in communication cost. • Novel methodologies proposed for efficient 2D-mesh NoC-based DNN accelerators. • ILP and SA-based neuron grouping and mapping methods to minimize communication cost. • The proposed methods can be used for both fully connected and partially pruned DNNs. • Performance validation on diverse DNN benchmark applications. [ABSTRACT FROM AUTHOR]

Multiple Electrostatic Quadrupole Array Linear Accelerators (MEQALACs) provide an opportunity to realize compact radio- frequency (RF) accelerator structures that can deliver very high beam currents. MEQALACs have been previously realized with acceleration gap distances and beam aperture sizes of the order of centimeters. Through advances in Micro-Electro-Mechanical Systems (MEMS) fabrication, MEQALACs can now be scaled down to the sub-millimeter regime and batch processed on wafer substrates. In this paper we show first results from using three RF stages in a compact MEMS-based ion accelerator. The results presented show proof-of-concept with accelerator structures formed from printed circuit boards using a 3 × 3 beamlet arrangement and noble gas ions at 10 keV. We present a simple model to describe the measured results. We also discuss some of the scaling behaviour of a compact MEQALAC. The MEMS-based approach enables a low-cost, highly versatile accelerator covering a wide range of currents (10 μA to 100 mA) and beam energies (100 keV to several MeV). Applications include ion-beam analysis, mass spectrometry, materials processing, and at very high beam powers, plasma heating.

For over half a century, high-energy particle accelerators have been a major enabling technology for particle and nuclear physics research as well as sources of X-rays for photon science research in material science, chemistry and biology. Particle accelerators for energy and intensity Frontier research in particle and nuclear physics continuously push the accelerator community to invent ways to increase the energy and improve the performance of accelerators, reduce their cost, and make them more power efficient. The accelerator community has demonstrated imagination and creativity in developing a plethora of future accelerator ideas and proposals. The technical maturity of the proposed facilities ranges from shovel-ready to those that are still largely conceptual. At this time, over 100 contributed papers have been submitted to the Accelerator Frontier of the US particle physics decadal community planning exercise known as Snowmass’2021. These papers cover a broad spectrum of topics: beam physics and accelerator education, accelerators for neutrinos, colliders for Electroweak/Higgs studies and multi-TeV energies, accelerators for Physics Beyond Colliders and rare processes, advanced accelerator concepts, and accelerator technology for Radio Frequency cavities (RF), magnets, targets and sources. This paper provides an overview of the present state of accelerators for particle physics and gives a brief description of some of the major facilities that have been proposed, their perceived advantages and some of the remaining challenges.

Annotation. The use of channeling in crystals is quite effective for controlling the primary proton beam, but to manipulate secondary beams π, K , etc., it is necessary not only to deflect them, but also to focus them, since here the beam divergences are much higher. Focusing devices created to date are suitable for applications at TeV-class accelerators because they have small transverse dimensions. To increase the angular acceptance, a device consisting of several crystals assembled into an array is proposed. In this case, two problems are solved: a large bending angle and acceptable angular acceptance of the device are ensured, which makes it possible to use it at a beam energy of 50 GeV on the domestic U-70 accelerator. The paper presents the results of testing a new device on the U-70 beam. [ABSTRACT FROM AUTHOR]

Systolic arrays are an integral part of many modern machine learning (ML) accelerators due to their efficiency in performing matrix multiplication that is a key primitive in modern ML models. Current state-of-the-art in systolic array-based accelerators mainly target area and delay optimizations with power optimization being considered as a secondary target. Very few accelerator designs directly target power optimizations and that too using very complex algorithmic modifications that in turn result in a compromise in the area or delay performance. We present a novel Power-Intent Systolic Array (PI-SA) that is based on the fine-grained power gating of the multiplication and accumulation (MAC) block multiplier inside the processing element of the systolic array, which reduces the design power consumption quite significantly, but with an additional delay cost. To offset the delay cost, we introduce a modified decomposition multiplier to obtain smaller reduction tree and to further improve area and delay, we also replace the carry propagation adder with a carry save adder inside each sub-multiplier. Comparison of the proposed design with the baseline Gemmini naive systolic array design and its variant, i.e., a conventional systolic array design, exhibits a delay reduction of up to 6%, an area improvement of up to 32% and a power reduction of up to 57% for varying accumulator bit-widths.

Reducing cement CO2 footprint is a societal need. This is being achieved mainly by replacing an increasing amount of Portland clinker by supplementary cementitious materials. However, this comes at a price: lower mechanical strengths at early ages due to slow pozzolanic reaction(s). This is being addressed by using accelerator admixtures. In this context, calcium silicate hydrate nucleation seeding seems to have a promising future, as it can accelerate cement and pozzolanic reactions at early ages, optimising their microstructures, without compromising late strength and durability performances. In fact, these features could even be improved. Moreover, other uses are low temperature concreting, precasting, shotconcrete, etc. Here, we focus on reviewing recent reports on calcium silicate hydrate seeding using commercially available admixtures. Current knowledge on the consequences of nucleation seeding on hydration reactions and on early and late mechanical strengths is discussed. It is noted that other features, in addition to the classic alite hydration acceleration, are covered here including the enhanced ettringite precipitation and the very efficient porosity refinement, which take place in the seeded binders. Finally, because the seeded binders seem to be denser, durability properties could also be enhanced although this remains to be properly established.

The field of edge computing has grown considerably over the past few years, with applications in artificial intelligence and big data processing, particularly due to its powerful accelerators offering a large amount of hardware parallelism. As the computing power of the latest edge systems increases, applications of edge computing are being expanded to areas that have traditionally required substantially high-performant computing resources such as scientific computing. In this paper, we review the latest literature and present the current status of research for implementing high-performance computing (HPC) on edge devices equipped with parallel accelerators, focusing on software environments including programming models and benchmark methods. We also examine the applicability of existing approaches and discuss possible improvements necessary towards realizing HPC on modern edge systems.

Copyright of National Academy of Sciences of Armenia Reports / Doklady Nacionalnaâ Akademiâ Nauk Armenii is the property of National Academy of Sciences of the Republic of Armenia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The structures may be exposed to fire or high temperature conditionally or accidentally. Alteration in the behavior of concrete structure is prospective under the exposure of elevated temperature. There is an urge to find the materials that can resist the alteration in physiochemical and strength properties of cementitious materials under high temperature. In the present study, the effect of elevated temperature on cement mortar consisting of additives, i.e., accelerating admixtures, and stone waste, i.e., stone slurry powder, was investigated and compared with specimens at room temperature. The aim of the study was to examine the practicability of these additives under exposure to high temperatures. The mortar specimens were exposed to various temperatures, i.e., 150°C, 300°C, 450°C, and 600°C, for the duration of one hour and compared with unheated samples. The change in mass, strength, and micro-structure of mortar specimens at elevated temperature was studied. The environmental assessment and performance evaluation of various mortar mixes were also evaluated. The mass of mortar specimens reduced as the exposure temperature of specimens was raised. The residual strength of mortar increased up to a certain temperature; afterwards, it decreased. Stone slurry powder and calcium nitrate can be used individually and in combination to resist thermal changes. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) come with many forms, such as convolutional neural networks, multilayer perceptron, and recurrent neural networks, to meet diverse needs of machine learning applications. However, existing DNN accelerator designs, when used to execute multiple neural networks, suffer from underutilization of processing elements, heavy feature map traffic, and large area overhead. In this article, we propose a novel approach, Polymorphic Accelerators, to address the flexibility issue fundamentally. We introduce the abstraction of logical accelerators to decouple the fixed mapping with physical resources. Three procedures are proposed that work collaboratively to reconfigure the accelerator for the current network that is being executed and to enable cross-layer data reuse among logical accelerators. Evaluation results show that the proposed approach achieves significant improvement in data reuse, inference latency and performance, e.g., 1.52x and 1.63x increase in throughput compared with state-of-the-art flexible dataflow approach and resource partitioning approach, respectively. This demonstrates the effectiveness and promise of polymorphic accelerator architecture. [ABSTRACT FROM AUTHOR]

This review aims to identify the typologies of business incubators (BI) and business accelerators (BA) and to define a taxonomy integrating both the BI's and BA's characteristics and services portfolio, facilitating the adoption of open innovation practices. A systematic literature review (SLR) was carried out encompassing the research topic concerning the relationship between the incubation structures and the performance of technology-based ventures. This comprehensive SLR encompasses a total of 1614 publications, aiming to advance the knowledge on BI and BA. This SLR allowed for the identification of current trends and future challenges, as well as of the most important authors, publications, and journals in this research framework. This SLR establishes a new taxonomy for BI and BA, based upon three main pillars: human capital, social capital, and organizational capital. BI and BA help in the development of new high-technology ventures, by being facilitators for open innovation practices. This SLR is limited by the literature, as the collection of publications was performed exclusively through ISI Web of Science (WoS). Further research can be made into the modes of how these structures impact open innovation practices at the regional level using a knowledge spillover approach. [ABSTRACT FROM AUTHOR]

We combine theory and evidence on incubator and accelerator programmes and their effects on urban economic development. These structured co-working programmes have grown rapidly. However, a rich descriptive literature reveals little about their impact on participants or surrounding urban areas. We situate programmes in a conceptual framework of co-location tools, theorise objectives and benefits and report findings from systematic, OECD-wide reviews of the evaluation literature. These evaluations provide evidence that accelerators and incubators raise participant employment, with accelerators also aiding access to finance. Ecosystem features such as university involvement and urban economic conditions also influence programme outcomes. However, evaluation evidence is less clear on detailed intervention design. We consider wider lessons and lay out an agenda for future research. [ABSTRACT FROM AUTHOR]

Multiplication is one of the widely used arithmetic operations in a variety of applications, such as image/video processing and machine learning. FPGA vendors provide high-performance multipliers in the form of DSP blocks. These multipliers are not only limited in number and have fixed locations on FPGAs but can also create additional routing delays and may prove inefficient for smaller bit-width multiplications. Therefore, FPGA vendors additionally provide optimized soft IP cores for multiplication. However, in this work, we advocate that these soft multiplier IP cores for FPGAs still need better designs to provide high-performance and resource efficiency. Toward this, we present generic area-optimized, low-latency accurate, and approximate softcore multiplier architectures, which exploit the underlying architectural features of FPGAs, i.e., lookup table (LUT) structures and fast-carry chains to reduce the overall critical path delay (CPD) and resource utilization of multipliers. Compared to Xilinx multiplier LogiCORE IP, our proposed unsigned and signed accurate architecture provides up to 25% and 53% reduction in LUT utilization, respectively, for different sizes of multipliers. Moreover, with our unsigned approximate multiplier architectures, a reduction of up to 51% in the CPD can be achieved with an insignificant loss in output accuracy when compared with the LogiCORE IP. For illustration, we have deployed the proposed multiplier architecture in accelerators used in image and video applications, and evaluated them for area and performance gains. Our library of accurate and approximate multipliers is opensource and available online at https://cfaed.tu-dresden.de/pd-downloads to fuel further research and development in this area, facilitate reproducible research, and thereby enabling a new research direction for the FPGA community. [ABSTRACT FROM AUTHOR]

Surface roughness represents the measure of the irregularities on the surface contributing to the local field enhancement. The traditional Fowler-Nordheim equation established for perfectly planar surfaces is not suitable for describing emission from rough surfaces. Instead, it is more appropriate to use the equation that accounts for the field enhancement factor describing the effect of the surface morphology. In superconducting radio frequency cavities, field emission may occur in the irises while the tips on the cavity surface may act as an emitter leading to the high electric field. For this study, calculations for hemispherical, cylindrical, and conical tips have been performed using a Multiphysics software package COMSOL. The focus was put on the dependence of the field enhancement factor on the shape and the radius of the protrusions. The electric field strength and the current density increase with increasing the root mean square average of the profile heights due to field enhancement at the cavity irises. The lowest value of the electric field has been achieved for the hemisphere. The calculated values for the field enhancement factors are consistent with the data from the literature, in which case the protrusion may represent a small local bump on the surface of a superconducting cavity. Based on the fit of the results, presented here, the relation between the enhancement factor and the radius has been suggested. The accurate estimation of the field emission may play a crucial role in the design of accelerators and other technological applications with requirements of extremely high precision.

ABSTRACT: This review aims to identify the typologies of business incubators (BI) and business accelerators (BA) and to define a taxonomy integrating both the BI’s and BA’s characteristics and services portfolio, facilitating the adoption of open innovation practices. A systematic literature review (SLR) was carried out encompassing the research topic concerning the relationship between the incubation structures and the performance of technology-based ventures. This comprehensive SLR encompasses a total of 1614 publications, aiming to advance the knowledge on BI and BA. This SLR allowed for the identification of current trends and future challenges, as well as of the most important authors, publications, and journals in this research framework. This SLR establishes a new taxonomy for BI and BA, based upon three main pillars: human capital, social capital, and organizational capital. BI and BA help in the development of new high-technology ventures, by being facilitators for open innovation practices. This SLR is limited by the literature, as the collection of publications was performed exclusively through ISI Web of Science (WoS). Further research can be made into the modes of how these structures impact open innovation practices at the regional level using a knowledge spillover approach.

Free-Electron Lasers are a rapidly growing field for advanced science and applications, and worldwide facilities for intense field generation, characterization and usage are becoming increasingly popular due to their peculiarities, including extremely bright, coherent, wide band tunable ultra-short pulses which are not achievable with other techniques up to now. In this review we give a thorough survey of the latest advances in the Free-Electron Laser-based field generation and detection methodologies and then present the main characteristics of a future THz/IR source, named TerRa@BriXSinO, based on a superconducting linear accelerator. The foreseen source is strongly monochromatic, with a bandwidth of 1% or smaller, highly coherent both transversally and longitudinally, with extreme versatility and high frequency tunability. After introducing the most recent and novel FEL-assisted scientific investigations, including fundamental explorations into complex systems and time-dependent interactions and material dynamics, we present our vision on the potential use of the TerRa facility and analyze some possible applications, ranging from non-linear physics under extreme conditions to polarization sensitive imaging and metamaterial-based sensing.

Objectives: We examined associations between accelerators (interventions impacting ≥2 SDG targets) and SDG-aligned well-being indicators among adolescents 16–24 years old in Zambia.Methods: We surveyed adults from 1,800 randomly sampled households receiving social cash transfers. We examined associations between accelerators (social cash transfers, life-long learning, mobile phone access) and seven well-being indicators among adolescents using multivariate logistic regressions.Results: The sample comprised 1,725 adolescents, 881 (51.1%) girls. Mobile phone access was associated with no poverty (adjusted Odds Ratio [aOR] 2.08, p < 0.001), informal cash transfers (aOR 1.82, p = 0.004), and seeking mental health support (aOR 1.61, p = 0.020). Social cash transfers were associated with no disability-related health restrictions (aOR 2.56, p = 0.004) and lesser odds of seeking mental health support (aOR 0.53, p = 0.029). Life-long learning was associated with informal cash transfers (aOR 3.49, p < 0.001) and lower school enrollment (aOR 0.70, p = 0.004). Adolescents with disabled head-of-household reported worse poverty, good health but less suicidal ideation.Conclusions: Social cash transfers, life-long learning, and mobile phone access were positively associated with well-being indicators. Adolescents living with disabled head-of-household benefited less. Governments should implement policies to correct disability-related inequalities.

The availability of huge structured and unstructured data, advanced highly dense memory and high performance computing machines have provided a strong push for the development in artificial intelligence (AI) and machine learning (ML) domains. AI and machine learning has rekindled the hope of efficiently solving complex problems which was not possible in the recent past. The generation and availability of big‐data is a strong driving force for the development of AI/ML applications, however, several challenges need to be addressed, like processing speed, memory requirement, high bandwidth, low latency memory access, and highly conductive and flexible connections between processing units and memory blocks. The conventional computing platforms are unable to address these issues with machine learning and AI. Deep neural networks (DNNs) are widely employed for machine learning and AI applications, like speech recognition, computer vison, robotics, and so forth, efficiently and accurately. However, accuracy is achieved at the cost of high computational complexity, sacrificing energy efficiency and throughput like performance measuring parameters along with high latency. To address the problems of latency, energy efficiency, complexity, power consumption, and so forth, a lot of state of the art DNN accelerators have been designed and implemented in the form of application specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs). This work provides the state of the art of all these DNN accelerators which have been developed recently. Various DNN architectures, their computing units, emerging technologies used in improving the performance of DNN accelerators will be discussed. Finally, we will try to explore the scope for further improvement in these accelerator designs, various opportunities and challenges for the future research. [ABSTRACT FROM AUTHOR]

Technology startups have a positive impact on the socioeconomic development of a region, but they lack resources, seeking support organizations, such as incubators and accelerators. This work aimed to identify the differences and similarities between incubation and acceleration programs, based on the resources offered, using the Resource Based View as a theoretical perspective. For this, a qualitative approach was adopted, with the realization of a case study with the application of semi-structured interviews with an incubator and an accelerator. Five categories of resources were identified: physical, financial, technological, organizational, and human. The results showed that the incubation and acceleration programs have different characteristics, not being exclusive but complementary. [ABSTRACT FROM AUTHOR]

The physical and clinical benefits of charged particle therapy (CPT) are well recognized. However, the availability of CPT and complete exploitation of dosimetric advantages are still limited by high facility costs and technological challenges. There are extensive ongoing efforts to improve upon these, which will lead to greater accessibility, superior delivery, and therefore better treatment outcomes. Yet, the issue of cost remains a primary hurdle as utility of CPT is largely driven by the affordability, complexity and performance of current technology. Modern delivery techniques are necessary but limited by extended treatment times. Several of these aspects can be addressed by developments in the beam delivery system (BDS) which determines the overall shaping and timing capabilities enabling high quality treatments. The energy layer switching time (ELST) is a limiting constraint of the BDS and a determinant of the beam delivery time (BDT), along with the accelerator and other factors. This review evaluates the delivery process in detail, presenting the limitations and developments for the BDS and related accelerator technology, toward decreasing the BDT. As extended BDT impacts motion and has dosimetric implications for treatment, we discuss avenues to minimize the ELST and overview the clinical benefits and feasibility of a large energy acceptance BDS. These developments support the possibility of advanced modalities and faster delivery for a greater range of treatment indications which could also further reduce costs. Further work to realize methodologies such as volumetric rescanning, FLASH, arc, multi-ion and online image guided therapies are discussed. In this review we examine how increased treatment efficiency and efficacy could be achieved with improvements in beam delivery and how this could lead to faster and higher quality treatments for the future of CPT. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Sciences, Life & Applied Sciences is the property of Arab Journal of Sciences & Research Publishing (AJSRP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Adolescents experience a multitude of vulnerabilities which need to be addressed in order to achieve the Sustainable Development Goals (SDGs). In sub-Saharan Africa, adolescents experience high burden of HIV, violence exposure, poverty, and poor mental and physical health. This study aimed to identify interventions and circumstances associated with three or more targets ("accelerators") within multiple SDGs relating to HIV-affected adolescents and examine cumulative effects on outcomes.Methods: Prospective longitudinal data from 3401 adolescents from randomly selected census enumeration areas in two provinces with > 30% HIV prevalence carried out in 2010/11 and 2011/12 were used to examine six hypothesized accelerators (positive parenting, parental monitoring, free schooling, teacher support, food sufficiency and HIV-negative/asymptomatic caregiver) targeting twelve outcomes across four SDGs, using a multivariate (multiple outcome) path model with correlated outcomes controlling for outcome at baseline and socio-demographics. The study corrected for multiple-hypothesis testing and tested measurement invariance across sex. Percentage predicted probabilities of occurrence of the outcome in the presence of the significant accelerators were also calculated.Results: Sample mean age was 13.7 years at baseline, 56.6% were female. Positive parenting, parental monitoring, food sufficiency and AIDS-free caregiver were variously associated with reductions on ten outcomes. The model was gender invariant. AIDS-free caregiver was associated with the largest reductions. Combinations of accelerators resulted in a percentage reduction of risk of up to 40%.Conclusion: Positive parenting, parental monitoring, food sufficiency and AIDS-free caregivers by themselves and in combination improve adolescent outcomes across ten SDG targets. These could translate to the corresponding real-world interventions parenting programmes, cash transfers and universal access to antiretroviral treatment, which when provided together, may help governments in sub-Saharan Africa more economically to reach their SDG targets. [ABSTRACT FROM AUTHOR]

Manganese-52 ground (52gMn) is a positron emitter and its beneficial properties make it a strong candidate for positron emission tomography (PET) imaging. Furthermore, the PET isotope 52gMn has been proposed as a suitable candidate for combination with proteins and antibodies. Moreover, Mn2+ has a paramagnetic property, thus the Mn isotope is ideal for use in bimodal PET/magnetic resonance (MR) images as a traceable nuclide, that can provide anatomical, molecular and physiological information of tissues. In this work, the theoretical calculation of the cross-section to produce 52Mn based on EMPIRE 3.2.2 code was carried out, focusing the attention on the optimization of the code parameters. The calculated cross-sections, obtained considering the effect of different level density models of the code, were compared with the experimental ones, to produce 52Mn isotopes by deuteron beam irradiation in the energy range up to 35 MeV on natCr target. At the same time, the co-produced 54Mn, 51Cr and 48V from natCr(d,X) nuclear reactions have been investigated. The results are also compared with the data taken from the online TENDL library of different versions. [ABSTRACT FROM AUTHOR]

Time synchronization faces an increasing performance demand nowadays. This is particularly common in different segments, such as new scientific infrastructures, power grid, telecommunications or fifth-generation (5G) wireless networks. All of them share the need for a time synchronization technology offering a very low synchronization error along large networks. The new version of the IEEE-1588-2019 protocol offers a considerable performance improvement thanks to the high accuracy profile based on white rabbit (WR). The original WR implementation guarantees a synchronization accuracy below 1 ns for a small number of cascaded nodes. This contribution evaluates the performance degradation when a considerable number of devices are deployed in cascaded configurations. In order to improve the performance, different delay measurement implementations have been evaluated in a series of experiments. The results prove the considerable benefits of our implementation against the current WR implementation. [ABSTRACT FROM AUTHOR]

This article describes international experience in the area of setup and development of accelerators as the source of innovations, including innovations in the sphere of digital economy. This research also presents main characteristics of accelerators, their classification and main differences from business-incubators. It also includes analysis of main activity indicators of leading accelerators in the world, based on the data of Global Accelerator Network, as well as ranking of different types of accelerators. There is also analysis of the current situation in Belarus with accelerators, including main problems as well as recommendations on further development.

The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high‐performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high‐performance accelerators along with dataflow control. Furthermore, the processing of various neural networks (NNs) requires a flexible memory architecture, programmable control scheme, and automated optimizations. We first propose an efficient architecture with flexibility while operating at a high frequency despite the large memory and PE‐array sizes. We then improve the efficiency and usability of our architecture by automating the optimization algorithm. The experimental results show that the architecture increases the data reuse; a diagonal write path improves the performance by 1.44× on average across a wide range of NNs. The automated optimizations significantly enhance the performance from 3.8× to 14.79× and further provide usability. Therefore, automating the optimization as well as designing an efficient architecture is critical to realizing high‐performance DNN accelerators.

While SHA-2 is a ubiquitous cryptographic hashing primitive, its role in emerging application domains, e.g. blockchains or trusted IoT components, has made the acceleration of SHA-2 very challenging due to new stringent classes of requirements, especially implementation cost and energy efficiency. The survey discusses these emerging applications and their fundamental requirements. Then, the work presents a comprehensive review of the different design techniques available in the literature for SHA-2 acceleration. The main focus of the presentation is placed on the impact of each design technique on the area, energy, power, and performance of the resulting accelerator, guiding the designer through the identification of the appropriate technique mixes which meet the constraints of any given application.

Open innovation programmes related to data and artificial intelligence have interested European policy-makers as a means of supporting startups and small and medium-sized enterprises to succeed in the digital economy. We discuss the objectives behind the typical service offerings of such programmes and propose a case for exploring how they align with the motivations of individual companies who are targeted by these initiatives. Using a qualitative analysis of 50 startup applications from the Data Market Services Accelerator programme, we find that applicants wrote most frequently about fundraising, acceleration and data skills. A smaller number of startups expressed interest in services related to standardization or legal guidance on General Data Protection Regulation and intellectual property rights, which are some of the ongoing priority areas for the European Commission. We discuss how the value propositions of these less desired offerings can be amplified by appealing the existing business motivations of data-driven startups.

Coherent emission coming from relativistic charged bunches is of great interest in a wide range of user-oriented applications and high-resolution diagnostics. The complete characterization of such emission is therefore important in view of a complete understanding of its potential. Here we present a complete temporally-resolved characterization of the radiation emitted by ultra-short relativistic electron bunches using a temporal diagnostic based on electro-optical sampling with a few tens fs of temporal resolution. We have characterized, for the first time to our knowledge, the evolution of the radiation (in THz range) both in amplitude and direction of propagation by varying the detection (i.e. the observer) position from the near to the far field (FF) range. Results show that in the near-field regime the emitted radiation propagates collinearly with the electron beam; while, approaching the FF regime, the radiation behaves as the classical Cherenkov radiation.

The physical and clinical benefits of charged particle therapy (CPT) are well recognized. However, the availability of CPT and complete exploitation of dosimetric advantages are still limited by high facility costs and technological challenges. There are extensive ongoing efforts to improve upon these, which will lead to greater accessibility, superior delivery, and therefore better treatment outcomes. Yet, the issue of cost remains a primary hurdle as utility of CPT is largely driven by the affordability, complexity and performance of current technology. Modern delivery techniques are necessary but limited by extended treatment times. Several of these aspects can be addressed by developments in the beam delivery system (BDS) which determines the overall shaping and timing capabilities enabling high quality treatments. The energy layer switching time (ELST) is a limiting constraint of the BDS and a determinant of the beam delivery time (BDT), along with the accelerator and other factors. This review evaluates the delivery process in detail, presenting the limitations and developments for the BDS and related accelerator technology, toward decreasing the BDT. As extended BDT impacts motion and has dosimetric implications for treatment, we discuss avenues to minimize the ELST and overview the clinical benefits and feasibility of a large energy acceptance BDS. These developments support the possibility of advanced modalities and faster delivery for a greater range of treatment indications which could also further reduce costs. Further work to realize methodologies such as volumetric rescanning, FLASH, arc, multi-ion and online image guided therapies are discussed. In this review we examine how increased treatment efficiency and efficacy could be achieved with improvements in beam delivery and how this could lead to faster and higher quality treatments for the future of CPT.

Side-channel attacks can break mathematically secure cryptographic systems leading to a major concern in applied cryptography. While the cryptanalysis and security evaluation of Post-Quantum Cryptography (PQC) have already received an increasing research effort, a cost analysis of efficient side-channel countermeasures is still lacking. In this work, we propose a masked HW/SW codesign of the NIST PQC finalists Kyber and Saber, suitable for their different characteristics. Among others, we present a novel masked ciphertext compression algorithm for non-power-of-two moduli. To accelerate linear performance bottlenecks, we developed a generic Number Theoretic Transform (NTT) multiplier, which, in contrast to previously published accelerators, is also efficient and suitable for schemes not based on NTT. For the critical non-linear operations, masked HW accelerators were developed, allowing a secure execution using RISC-V instruction set extensions. With the proposed design, we achieved a cycle count of K:214k/E:298k/D:313k for Kyber and K:233k/E:312k/D:351k for Saber with NIST Level III parameter sets. For the same parameter sets, the masking overhead for the first-order secure decapsulation operation including randomness generation is a factor of 4.48 for Kyber (D:1403k) and 2.60 for Saber (D:915k).