Programmable Systems Research Articles

Dynamic Vortex Generation, Pulsed Injection, and Rapid Mixing of Blood Samples in Microfluidics Using the Tube Oscillation Mechanism.

Here, we describe the generation of dynamic vortices in micro-scale cavities at low flow rates. The system utilizes a computer-controlled audio speaker to axially oscillate the inlet tube of the microfluidic system at desired frequencies and amplitudes. The oscillation of the tube induces transiently high flow rates in the system, which facilitates the generation of dynamic vortices inside the cavity. The size of the vortices can be modulated by varying the tube oscillation frequency or amplitude. The vortices can be generated in single or serial cavities and in a wide range of cavity sizes. We demonstrate the suitability of the tube oscillation mechanism for the pulsed injection of water-based solutions or whole blood into the cavity. The injection rate can be controlled by the oscillation characteristics of the tube, enabling the injection of liquids at ultralow flow rates. The dynamic vortices facilitate the rapid mixing of the injected liquid with the main flow. The controllability and versatility of this technology allow for the development of programmable inertial microfluidic systems for performing multistep biological assays.

A Mixed Hardware-Software Implementation of a High-Performance PMSM Controller

Implementation of the permanent magnet synchronous motor vector control implies strong time dependencies. The control process requires precise measurement of motor shaft position and winding currents to establish correct driving. The tight time dependencies are difficult to achieve using a programmatic approach. Specific controller architecture is proposed for programmable systems on chip architectures enabling operations precise timing and improved processing performance. The controller is decomposed into a dedicated hardware interface system and programmatic part for easy implementation and modification of the control algorithm. The proposed architecture offers precise and repeatable input-output operations timing and assures meeting tight time dependencies. The control algorithm is executed as an interrupt service requested by the interface system in a constant processing period with relatively weak time dependencies. Additionally, the interface system preprocesses input and output signals reducing the computation effort and saving time for algorithm computations. The specific implementation enabled improved measurement of the motor’s windings current with suppression of disturbances caused by inverter operation. There is shown an efficient implementation of Parke’s and Clarke’s transformations using specific resources of modern programmable logic devices. In opposite to the software-managed implementation presented implementation assures completing processing faster, using a minimal number of hardware resources of the FPGA platform and offering the highest flexibility of software part implementation.

Non-invasive transcranial volumetric ultrasound localization microscopy of the rat brain with continuous, high volume-rate acquisition

Rationale: Structure and function of the microvasculature provides critical information about disease state, can be used to identify local regions of pathology, and has been shown to be an indicator of response to therapy. Improved methods of assessing the microvasculature with non-invasive imaging modalities such as ultrasound will have an impact in biomedical theranostics. Ultrasound localization microscopy (ULM) is a new technology which allows processing of ultrasound data for visualization of microvasculature at a resolution better than allowed by acoustic diffraction with traditional ultrasound systems. Previous application of this modality in brain imaging has required the use of invasive procedures, such as a craniotomy, skull-thinning, or scalp removal, all of which are not feasible for the purpose of longitudinal studies. Methods: The impact of ultrasound localization microscopy is expanded using a 1024 channel matrix array ultrasonic transducer, four synchronized programmable ultrasound systems with customized high-performance hardware and software, and high-performance GPUs for processing. The potential of the imaging hardware and processing approaches are demonstrated in-vivo. Results: Our unique implementation allows asynchronous acquisition and data transfer for uninterrupted data collection at an ultra-high fixed frame rate. Using these methods, the vasculature was imaged using 100,000 volumes continuously at a volume acquisition rate of 500 volumes per second. With ULM, we achieved a resolution of 31 µm, which is a resolution improvement on conventional ultrasound imaging by nearly a factor of ten, in 3-D. This was accomplished while imaging through the intact skull with no scalp removal, which demonstrates the utility of this method for longitudinal studies. Conclusions: The results demonstrate new capabilities to rapidly image and analyze complex vascular networks in 3-D volume space for structural and functional imaging in disease assessment, targeted therapeutic delivery, monitoring response to therapy, and other theranostic applications.

Ultra-low noise, bi-polar, programmable current sources.

We present the design process and implementation of fully open-source, ultra-low noise programmable current source systems in two configurations. Although originally designed as coil drivers for Optically Pumped Magnetometers (OPMs), the device specifications make them potentially useful in a range of applications. The devices feature a bi-directional current range of ±10 and ±250 mA on three independent channels with 16-bit resolution. Both devices feature a narrow 1/f noise bandwidth of 1Hz, enabling magnetic field manipulation for high-performance OPMs. They exhibit a low noise of 146 pA/Hz and 4.1 nA/Hz, which translates to 15 and 16 ppb/Hz noise relative to full scale.

Rationally Designed DNA-Based Scaffolds and Switching Probes for Protein Sensing.

The detection of a protein analyte and use of this type of information for disease diagnosis and physiological monitoring requires methods with high sensitivity and specificity that have to be also easy to use, rapid and, ideally, single step. In the last 10 years, a number of DNA-based sensing methods and sensors have been developed in order to achieve quantitative readout of protein biomarkers. Inspired by the speed, specificity, and versatility of naturally occurring chemosensors based on structure-switching biomolecules, significant efforts have been done to reproduce these mechanisms into the fabrication of artificial biosensors for protein detection. As an alternative, in scaffold DNA biosensors, different recognition elements (e.g., peptides, proteins, small molecules, and antibodies) can be conjugated to the DNA scaffold with high accuracy and precision in order to specifically interact with the target protein with high affinity and specificity. They have several advantages and potential, especially because the transduction signal can be drastically enhanced. Our aim here is to provide an overview of the best examples of structure switching-based and scaffold DNA sensors, as well as to introduce the reader to the rational design of innovative sensing mechanisms and strategies based on programmable functional DNA systems for protein detection.

Технології реалізації штучного інтелекту як сервісу на основі апаратних прискорювачів

The subject of study in this article is modern technologies, tools and methods of building AI systems as a service using FPGA as a platform. The goal is to analyze modern technologies and tools used to develop FPGA-based projects for systems that implement artificial intelligence as a service and to prepare a practical AI service prototype. Task: to analyze the evolution of changes in the products of leading manufacturers of programmable logic devices and experimental and practical examples of the implementation of the paradigm of continuous reprogramming of programmable logic; analyze the dynamics of changes in the development environment of programmable logic systems for AI; analyze the essential elements of building projects for AI systems using programmable logic. According to the tasks, the following results were obtained. The area of application of hardware implementation of artificial intelligence for on-board and embedded systems including airspace industry, smart cars and medical systems is analyzed. The process of programming FPGA accelerators for AI projects is analyzed. The analysis of the capabilities of FPGA with HBM for building projects that require enough of high speed memory is performed. Description languages, frameworks, the hierarchy of tools for building of hardware accelerators for AI projects are analyzed in detail. The stages of prototyping of AI projects using new FPGA development tools and basic DPU blocks are analyzed. The parameters of the DPU blocks were analyzed. Practical steps for building such systems are offered. The practical recommendations for optimizing the neural network for FPGA implementation are given. The stages of neural network optimization are provided. The proposed steps include pruning of branches with low priority and the use of fixed point computations with custom range based on the requirements of an exact neural network. Based on these solutions, a practical case of AI service was prepared, trained and tested. Conclusions. The main contribution of this study is that, based on the proposed ideas and solutions, the next steps to create heterogeneous systems based on the combination of three elements are clear: AI as a service, FPGA accelerators as a technology for improving performance, reliability and security, and cloud or Edge resources to create FPGA infrastructure and AI as service. The development of this methodological and technological basis is the direction of further R&D.

Compressive property and shape memory effect of 3D printed continuous ramie fiber reinforced biocomposite corrugated structures

The present work aimed to study the quasi-static compression behaviors of 3D printed continuous ramie fiber reinforced biocomposite corrugated structures (CFCSs) with excellent shape memory effects. The in-plane compression test was conducted to evaluate the effects of cell shapes, fiber volume fraction (f v) and addition of fiber on the compression behaviors and energy absorption (EA) characteristics of the corrugated structures. The results showed that the compression property and EA capacity of the 3D printed CFCSs increased with decreasing f v and the addition of continuous ramie yarn. The 3D printed continuous ramie fiber reinforced biocomposite with inverted trapezoid cell shape corrugated structures (CFITCSs) outperformed other cell shapes in the compression strength and specific EA. The analytical model for the in-plane compression strength of CFITCSs was derived, and predictions were in good agreement with measurements. In addition, continuous natural fiber reinforced composite structure for shape memory was proposed for the first time. The shape recovery testing results demonstrated that 3D printed CFCSs had the potential to be a key element of lightweight programmable smart systems.

Digital Control and Power Systems for the Pegasus-III Experiment

The PEGASUS-III experiment is a solenoid-free, low aspect ratio spherical tokamak that will serve as a dedicated U.S. platform for comparative nonsolenoidal tokamak plasma startup studies. Approximately 175 megavolt-ampere (MVA) of reconfigured and expanded programmable power systems, 7 MJ of new stored energy, and new digital control and protection systems for the facility are being commissioned to support PEGASUS-III upgrades. These include: increased toroidal field (0.15–0.6 T); new divertor and poloidal field coils; increased pulse length; local and coaxial helicity injectors for solenoid-free plasma initiation; radio frequency (RF) systems for heating and current drive; and a diagnostic neutral beam (DNB). A new real-time digital control system implements 16 proportional-integral differential (PID) feedback controllers with 25 kHz loop rates to control the electromagnets and helicity injectors. The poloidal field coils, helicity injector arc currents, and toroidal field are driven by 36 3.6 MVA (4 kA, 900 V) insulated-gate bipolar transistor (IGBT) buck converters. Helicity injector bias voltage and current will be provided by a set of four 10.8 MVA multi-level buck converters (MLBCs). Each is comprised of an 1800 V integrated gate-commutated thyristor (IGCT) stage and a ±900 V IGBT stage in series, providing controllable <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I_{\mathrm {inj}}\le 4$ </tex-math></inline-formula> kA at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {inj}}\le 2.7$ </tex-math></inline-formula> kV. A field programmable gate array (FPGA)-based digital fault protection system multiplexes controller commands to individual power semiconductors in these supplies, monitors their operational status, and executes shutdown sequences within <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10~\mu \text{s}$ </tex-math></inline-formula> of fault detection. An 80 kV, 4 A zero-voltage-switching (ZVS) resonant converter with < 1% output ripple is under development for the DNB and is being evaluated as a topology to drive RF sources.

Site-specific genome editing in treatment of inherited diseases: possibility, progress, and perspectives.

Advancements in genome editing enable permanent changes of DNA sequences in a site-specific manner, providing promising approaches for treating human genetic disorders caused by gene mutations. Recently, genome editing has been applied and achieved significant progress in treating inherited genetic disorders that remain incurable by conventional therapy. Here, wepresent a review of various programmable genome editing systems with their principles, advantages, and limitations. We introduce their recent applications for treating inherited diseases in the clinic, including sickle cell disease (SCD), β-thalassemia, Leber congenital amaurosis (LCA), heterozygous familial hypercholesterolemia (HeFH), etc. We also discuss the paradigm of exvivo and in vivo editing and highlight the promise ofsomatic editing and the challenge of germline editing. Finally, wepropose future directions in delivery, cutting,and repairing to improve the scope of clinical applications.

PO203 / #915 LONGITUDINAL DATA FROM THE TARGETED DRUG DELIVERY (TDD) PRODUCT SURVEILLANCE REGISTRY: PUMP POCKET LOCATION: E-POSTER VIEWING

TDD with programmable intrathecal drug delivery systems (IDDS) has been approved for cancer and noncancer pain treatment since 1991 and severe spasticity since 1992. Early clinical IDDS studies specified an “abdominal pocket” as the pump implant location, resulting in this as the defined on-label location. Alternate pump implant locations are often necessary for patient-specific reasons, but full evaluation of the risks and benefits of these alternate pump sites has not been performed. Presented here is an evaluation of real-world registry data on the potential risks and benefits of alternate pump implant locations.

Creating programmable 5G systems for the Industrial IoT

A steadily growing number of factories, plants, mines and ports around the world are exploring the potential of 5G technology and considering how best to deploy it. This is to be expected, since 5G has been designed with vertical use cases in mind, and industrial automation systems are one of the most promising segments.

Centralised connectivity-preserving transformations for programmable matter: A minimal seed approach

We study a model of programmable matter systems consisting of n devices lying on a 2-dimensional square grid which are able to perform the minimal mechanical operation of rotating around each other. The goal is to transform an initial shape A into a target shape B. We investigate the class of shapes which can be constructed in such a scenario under the additional constraint of maintaining global connectivity at all times. We focus on the scenario of transforming nice shapes, a class of shapes consisting of a central line L where for all nodes u in S either u∈L or u is connected to L by a line of nodes perpendicular to L. We prove that by introducing a minimal 3-node seed it is possible for the canonical shape of a line of n nodes to be transformed into a nice shape of n−1 nodes. We use this to show that a 4-node seed enables the transformation of nice shapes of size n into any other nice shape of size n in O(n2) time. We leave as an open problem the expansion of the class of shapes which can be constructed using such a seed to include those derived from nice shapes.

Tunable light-induced dipole-dipole interaction between optically levitated nanoparticles.

Arrays of optically trapped nanoparticles have emerged as a platform for the study of complex nonequilibrium phenomena. Analogous to atomic many-body systems, one of the crucial ingredients is the ability to precisely control the interactions between particles. However, the optical interactions studied thus far only provide conservative optical binding forces of limited tunability. In this work, we exploit the phase coherence between the optical fields that drive the light-induced dipole-dipole interaction to couple two nanoparticles. In addition, we effectively switch off the optical interaction and observe electrostatic coupling between charged particles. Our results provide a route to developing fully programmable many-body systems of interacting nanoparticles with tunable nonreciprocal interactions, which are instrumental for exploring entanglement and topological phases in arrays of levitated nanoparticles.

Case Studies of Robots and Automation as Health/Safety Interventions in Small Manufacturing Enterprises.

This paper reviews the experiences of 63 case studies of small businesses (< 250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were: CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: Snack Foods; Photographic Film, Paper, Plate, and Chemical; Machine Shops; Leather Good and Allied Products; Plastic Products; and Iron and Steel Forging. This review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors and improved process productivity in most cases.

Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care.

To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets.

Construction for Health; Reversing the Impacts

The health of humans and the planet are the most vital contemporary issues and essential components of the Sustainable Development Goals (SDGs). Scientists and professionals strive for integrated, evolving, healthy, and sustainable solutions encompassing biodiversity and industrial ecology, while offering viable economic attainments. The building industry, especially construction, is an extensive economic counterpart that largely influences health on various levels. On a practical scale, most direct or indirect impacts on health are related to conventional construction systems (CCSs), particularly their materialisations and implementation methods. Therefore, from a global perspective, emerging technologies or remodelled methods to accomplish sustainable use, reuse, and recycling, and improving the planet’s health to ensure the wellbeing of its inhabitants, are crucial. The current research is part of a broader study on “programmable construction systems” (PCSs), concentrating on “programmable construction materials” (PCMs) for health. Therefore, issues are reviewed, relevancies are addressed, and health-oriented concepts are discussed. Example concepts of formulation and the simplified toolkit creations follow the problems’ sources in a case study, providing insight into the resulting multiscale impacts on real-life practices. The results prove the method’s potential and validate its simplicity and applicability through an abstract examination of a newly built case study. Finally, the summarised outcomes of other extensive studies on societal preferences also confirm the feasibility of the hypothesis (i.e., the healthy materialisation) also from a social perspective.

Rational engineering of natural polyhydroxyalkanoates producing microorganisms for improved synthesis and recovery.

Microbial production of biopolymers derived from renewable substrates and waste streams reduces our heavy reliance on petrochemical plastics. One of the most important biodegradable polymers is the family of polyhydroxyalkanoates (PHAs), naturally occurring intracellular polyoxoesters produced for decades by bacterial fermentation of sugars and fatty acids at the industrial scale. Despite the advances, PHA production still suffers from heavy costs associated with carbon substrates and downstream processing to recover the intracellular product, thus restricting market positioning. In recent years, model-aided metabolic engineering and novel synthetic biology approaches have spurred our understanding of carbon flux partitioning through competing pathways and cellular resource allocation during PHA synthesis, enabling the rational design of superior biopolymer producers and programmable cellular lytic systems. This review describes these attempts to rationally engineering the cellular operation of several microbes to elevate PHA production on specific substrates and waste products. We also delve into genome reduction, morphology, and redox cofactor engineering to boost PHA biosynthesis. Besides, we critically evaluate engineered bacterial strains in various fermentation modes in terms of PHA productivity and the period required for product recovery.

A Heterogeneous In-Memory Computing Cluster for Flexible End-to-End Inference of Real-World Deep Neural Networks

Deployment of modern TinyML tasks on small battery-constrained IoT devices requires high computational energy efficiency. Analog In-Memory Computing (IMC) using non-volatile memory (NVM) promises major efficiency improvements in deep neural network (DNN) inference and serves as on-chip memory storage for DNN weights. However, IMC’s functional flexibility limitations and their impact on performance, energy, and area efficiency are not yet fully understood at the system level. To target practical end-to-end IoT applications, IMC arrays must be enclosed in heterogeneous programmable systems, introducing new system-level challenges which we aim at addressing in this work. We present a heterogeneous tightly-coupled clustered architecture integrating 8 RISC-V cores, an in-memory computing accelerator (IMA), and digital accelerators. We benchmark the system on a highly heterogeneous workload such as the Bottleneck layer from a MobileNetV2, showing <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$11.5\times $ </tex-math></inline-formula> performance and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$9.5\times $ </tex-math></inline-formula> energy efficiency improvements, compared to highly optimized parallel execution on the cores. Furthermore, we explore the requirements for end-to-end inference of a full mobile-grade DNN (MobileNetV2) in terms of IMC array resources, by scaling up our heterogeneous architecture to a multi-array accelerator. Our results show that our solution, on the end-to-end inference of the MobileNetV2, is one order of magnitude better in terms of execution latency than existing programmable architectures and two orders of magnitude better than state-of-the-art heterogeneous solutions integrating in-memory computing analog cores.

Engineered Cas12i2 is a versatile high-efficiency platform for therapeutic genome editing

The CRISPR-Cas type V-I is a family of Cas12i-containing programmable nuclease systems guided by a short crRNA without requirement for a tracrRNA. Here we present an engineered Type V-I CRISPR system (Cas12i), ABR-001, which utilizes a tracr-less guide RNA. The compact Cas12i effector is capable of self-processing pre-crRNA and cleaving dsDNA targets, which facilitates versatile delivery options and multiplexing, respectively. We apply an unbiased mutational scanning approach to enhance initially low editing activity of Cas12i2. The engineered variant, ABR-001, exhibits broad genome editing capability in human cell lines, primary T cells, and CD34+ hematopoietic stem and progenitor cells, with both robust efficiency and high specificity. In addition, ABR-001 achieves a high level of genome editing when delivered via AAV vector to HEK293T cells. This work establishes ABR-001 as a versatile, specific, and high-performance platform for ex vivo and in vivo gene therapy.

Redefining rail systems verification and validation: The safety/security STAIRCASE model

Safety critical functions of the engineered railway need to perform at levels of integrity that are so high that an acceptable failure rate cannot be demonstrated through testing alone. Where such functions need to be implemented in complex programmable electronic systems certain design, build and test requirements are defined in technical standards and these are deemed to ensure that the correct level of systematic integrity is achieved. These approaches are based on assumptions around how system requirements are managed and delivered which are increasingly challenging to meet in practice. In particular the V&amp;V lifecycle used in functional safety standards and emerging cyber security design standards is idealised. It assumes a top-down cascade of requirements for each delivery project. The approaches have become the de-facto standard internationally and are now mandated to an extent in European railway safety regulations. This paper proposes a different approach: a new lifecycle model that aligns better with the reality of the modern global supply chain and the order in which asset design and project delivery activities are actually undertaken to improve the ability to proactively manage safety.This leads to a fundamental change in the assurance philosophy to bring a simpler and more understandable approach. A framework for applying this approach is set out along with further research objectives to deliver the solution in practice.