Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and newgeneration intelligent manufacturing. New-generation intelligent manufacturing represents an indepth integration of new-generation artificial intelligence (AI) technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs) reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for ‘‘parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China.
Systems for ambient assisted living (AAL) that integrate service robots with sensor networks and user monitoring can help elderly people with their daily activities, allowing them to stay in their homes and live active lives for as long as possible. In this paper, we outline the AAL system currently developed in the European project Robot-Era, and describe the engineering aspects and the service-oriented software architecture of the domestic robot, a service robot with advanced manipulation capabilities. Based on the robot operating system (ROS) middleware, our software integrates a large set of advanced algorithms for navigation, perception, and manipulation. In tests with real end users, the performance and acceptability of the platform are evaluated.
A growing number of?three-dimensional (3D)-print-ing processes have been applied to tissue engineering. This paper presents a state-of-the-art study of 3D-printing technologies?for tissue-engineering applications, with particular focus on the development of a computer-aided scaffold design system; the direct 3D printing of functionally graded scaffolds; the modeling of selective laser sintering (SLS) and fused deposition modeling (FDM) processes; the indirect additive manufacturing of scaffolds, with both micro and macro features; the development of a bioreactor; and 3D/4D bioprinting. Technological limitations will be discussed so as to highlight the possibility of future improvements for new 3D-printing methodologies for tissue engineering.
With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI) has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the development of AI 2.0 are given.
The most promising strategies in tissue engineering involve the integration of a triad of biomaterials, living cells, and biologically active molecules to engineer synthetic environments that closely mimic the healing milieu present in human tissues, and that stimulate tissue repair and regeneration. To be clinically effective, these environments must replicate, as closely as possible, the main characteristics of the native extracellular matrix (ECM) on a cellular and subcellular scale. Photo-fabrication techniques have already been used to generate 3D environments with precise architectures and heterogeneous composition, through a multi-layer procedure involving the selective photocrosslinking reaction of a light-sensitive prepolymer. Cells and therapeutic molecules can be included in the initial hydrogel precursor solution, and processed into 3D constructs. Recently, photo-fabrication has also been explored to dynamically modulate hydrogel features in real time, providing enhanced control of cell fate and delivery of bioactive compounds. This paper focuses on the use of 3D photo-fabrication techniques to produce advanced constructs for tissue regeneration and drug delivery applications. State-of-the-art photo-fabrication techniques are described, with emphasis on the operating principles and biofabrication strategies to create spatially controlled patterns of cells and bioactive factors. Considering its fast processing, spatiotemporal control, high resolution, and accuracy, photo-fabrication is assuming a critical role in the design of sophisticated 3D constructs. This technology is capable of providing appropriate environments for tissue regeneration, and regulating the spatiotemporal delivery of therapeutics.
Functional crystals are the basic materials for the development of modern science and technology and are playing key roles in the modern information era. In this paper, we review functional crystals in China, including research history, significant achievements, and important applications by highlighting the most recent progress in research. Challenges for the development of functional materials are discussed and possible directions for development are proposed by focusing on potential strengths of these materials.
Magnetic helical micro- and nanorobots can perform 3D navigation in various liquids with a sub-micrometer precision under low-strength rotating magnetic fields (<10 mT). Since magnetic fields with low strengths are harmless to cells and tissues, magnetic helical micro/nanorobots are promising tools for biomedical applications, such as minimally invasive surgery, cell manipulation and analysis, and targeted therapy. This review provides general information on magnetic helical micro/nanorobots, including their fabrication, motion control, and further functionalization for biomedical applications.
Additive manufacturing and 3D printing technology have been developing rapidly in the last 30 years, and indicate great potential for future development. The promising future of this technology makes its impact on traditional industry unpredictable. 3D printing will propel the revolution of fabrication modes forward, and bring in a new era for customized fabrication by realizing the five “any”s: use of almost any material to fabricate any part, in any quantity and any location, for any industrial field. Innovations in material, design, and fabrication processes will be inspired by the merging of 3D-printing technology and processes with traditional manufacturing processes. Finally, 3D printing will become as valuable for manufacturing industries as equivalent and subtractive manufacturing processes.
In this paper, we review the current state-of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering: neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity (via a neuroimaging modality) through a neural interface (invasive or noninvasive) and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering—to develop neurotechniques for enhancing the understanding of whole-brain function and dysfunction, and the management of neurological and mental disorders.
Since its inception, endoscopy has aimed to establish an immediate diagnosis that is virtually consistent with a histologic diagnosis. In the past decade, confocal laser scanning microscopy has been brought into endoscopy, thus enabling in vivo microscopic tissue visualization with a magnification and resolution comparable to that obtained with the ex vivo microscopy of histological specimens. The major challenge in the development of instrumentation lies in the miniaturization of a fiber-optic probe for microscopic imaging with micron-scale resolution. Here, we present the design and construction of a confocal endoscope based on a fiber bundle with 1.4-μm lateral resolution and 8-frames per second (fps) imaging speed. The fiber-optic probe has a diameter of 2.6 mm that is compatible with the biopsy channel of a conventional endoscope. The prototype of a confocal endoscope has been used to observe epithelial cells of the gastrointestinal tracts of mice and will be further demonstrated in clinical trials. In addition, the confocal endoscope can be used for translational studies of epithelial function in order to monitor how molecules work and how cells interact in their natural environment.
Materials-development projects for advanced ultra-supercritical (A-USC) power plants with steam temperatures of 700 °C and above have been performed in order to achieve high efficiency and low CO2 emissions in Europe, the US, Japan, and recently in China and India as well. These projects involve the replacement of martensitic 9%−12% Cr steels with nickel (Ni)-base alloys for the highest temperature boiler and turbine components in order to provide sufficient creep strength at 700°C and above. To minimize the requirement for expensive Ni-base alloys, martensitic 9%−12% Cr steels can be applied to the next highest temperature components of an A-USC power plant, up to a maximum of 650°C. This paper comprehensively describes the research and development of Ni-base alloys and martensitic 9%−12% Cr steels for thick section boiler and turbine components of A-USC power plants, mainly focusing on the long-term creep-rupture strength of base metal and welded joints, strength loss in welded joints, creep-fatigue properties, and microstructure evolution during exposure at elevated temperatures.
The configuration space is a fundamental concept that is widely used in algorithmic robotics. Many applications in robotics, computer-aided design, and related areas can be reduced to computational problems in terms of configuration spaces. In this paper, we survey some of our recent work on solving two important challenges related to configuration spaces: ① how to efficiently compute an approximate representation of high-dimensional configuration spaces; and ② how to efficiently perform geometric proximity and motion planning queries in high-dimensional configuration spaces. We present new configuration space construction algorithms based on machine learning and geometric approximation techniques. These algorithms perform collision queries on many configuration samples. The collision query results are used to compute an approximate representation for the configuration space, which quickly converges to the exact configuration space. We also present parallel GPU-based algorithms to accelerate the performance of optimization and search computations in configuration spaces. In particular, we design efficient GPU-based parallel k-nearest neighbor and parallel collision detection algorithms and use these algorithms to accelerate motion planning.
Cutting-edge technologies in optical molecular imaging have ushered in new frontiers in cancer research, clinical translation, and medical practice, as evidenced by recent advances in optical multimodality imaging, Cerenkov luminescence imaging (CLI), and optical image-guided surgeries. New abilities allow in vivo cancer imaging with sensitivity and accuracy that are unprecedented in conventional imaging approaches. The visualization of cellular and molecular behaviors and events within tumors in living subjects is improving our deeper understanding of tumors at a systems level. These advances are being rapidly used to acquire tumor-to-tumor molecular heterogeneity, both dynamically and quantitatively, as well as to achieve more effective therapeutic interventions with the assistance of real-time imaging. In the era of molecular imaging, optical technologies hold great promise to facilitate the development of highly sensitive cancer diagnoses as well as personalized patient treatment—one of the ultimate goals of precision medicine.
In this paper, a novel flexible robot system with a constrained tendon-driven serpentine manipulator (CTSM) is presented. The CTSM gives the robot a larger workspace, more dexterous manipulation, and controllable stiffness compared with the da Vinci surgical robot and traditional flexible robots. The robot is tele-operated using the Novint Falcon haptic device. Two control modes are implemented, direct mapping and incremental mode. In each mode, the robot can be manipulated using either the highest stiffness scheme or the minimal movement scheme. The advantages of the CTSM are shown by simulation and experimental results.
In order to build a ceramic component by inkjet printing, the object must be fabricated through the interaction and solidification of drops, typically in the range of 10−100 pL. In order to achieve this goal, stable ceramic inks must be developed. These inks should satisfy specific rheological conditions that can be illustrated within a parameter space defined by the Reynolds and Weber numbers. Printed drops initially deform on impact with a surface by dynamic dissipative processes, but then spread to an equilibrium shape defined by capillarity. We can identify the processes by which these drops interact to form linear features during printing, but there is a poorer level of understanding as to how 2D and 3D structures form. The stability of 2D sheets of ink appears to be possible over a more limited range of process conditions that is seen with the formation of lines. In most cases, the ink solidifies through evaporation and there is a need to control the drying process to eliminate the: “coffee ring” defect. Despite these uncertainties, there have been a large number of reports on the successful use of inkjet printing for the manufacture of small ceramic components from a number of different ceramics. This technique offers good prospects as a future manufacturing technique. This review identifies potential areas for future research to improve our understanding of this manufacturing method.
Viral load measurements are an essential tool for the long-term clinical care of human immunodeficiency virus (HIV)-positive individuals. The gold standards in viral load instrumentation, however, are still too limited by their size, cost, and sophisticated operation for these measurements to be ubiquitous in remote settings with poor healthcare infrastructure, including parts of the world that are disproportionately affected by HIV infection. The challenge of developing a point-of-care platform capable of making viral load more accessible has been frequently approached but no solution has yet emerged that meets the practical requirements of low cost, portability, and ease-of-use. In this paper, we perform reverse-transcription loop-mediated isothermal amplification (RT-LAMP) on minimally processed HIV-spiked whole blood samples with a microfluidic and silicon microchip platform, and perform fluorescence measurements with a consumer smartphone. Our integrated assay shows amplification from as few as three viruses in a ~ 60 nL RT-LAMP droplet, corresponding to a whole blood concentration of 670 viruses per μL of whole blood. The technology contains greater power in a digital RT-LAMP approach that could be scaled up for the determination of viral load from a finger prick of blood in the clinical care of HIV-positive individuals. We demonstrate that all aspects of this viral load approach, from a drop of blood to imaging the RT-LAMP reaction, are compatible with lab-on-a-chip components and mobile instrumentation.
Metamaterials are composite materials whose material properties (acoustic, electrical, magnetic, or optical, etc.) are determined by their constitutive structural materials, especially the unit cells. The development of metamaterials continues to redefine the boundaries of materials science. In the field of electromagnetic research and beyond, these materials offer excellent design flexibility with their customized properties and their tunability under external stimuli. In this paper, we first provide a literature review of metamaterials with a focus on the technology and its evolution. We then discuss steps in the industrialization process and share our own experience.
This paper presents findings from an investigation of the large-scale construction solid waste (CSW) landslide that occurred at a landfill at Shenzhen, Guangdong, China, on December 20, 2015, and which killed 77 people and destroyed 33 houses. The landslide involved 2.73×106 m3 of CSW and affected an area about 1100?m in length and 630?m in maximum width, making it the largest landfill landslide in the world. The investigation of this disaster used a combination of unmanned aerial vehicle surveillance and multistage remote-sensing images to reveal the increasing volume of waste in the landfill and the shifting shape of the landfill slope for nearly two years before the landslide took place, beginning with the creation of the CSW landfill in March, 2014, that resulted in the uncertain conditions of the landfill’s boundaries and the unstable state of the hydrologic performance. As a result, applying conventional stability analysis methods used for natural landslides to this case would be difficult. In order to analyze this disaster, we took a multistage modeling technique to analyze the varied characteristics of the landfill slope’s structure at various stages of CSW dumping and used the non-steady?flow?theory to explain the groundwater seepage problem. The investigation showed that the landfill could be divided into two units based on the moisture in the land: ① a front uint, consisted of the landfill slope, which had low water content; and ② a rear unit, consisted of fresh waste, which had a high water content. This structure caused two effects—surface-water infiltration and consolidation seepage that triggered the landslide in the landfill. Surface-water infiltration induced a gradual increase in pore water pressure head, or piezometric head, in the front slope because the infiltrating position rose as the volume of waste placement increased. Consolidation seepage led to higher excess pore water pressures as the loading of waste increased. We also investigated the post-failure soil dynamics parameters of the landslide deposit using cone penetration, triaxial, and ring-shear tests in order to simulate the characteristics of a flowing slide with a long run-out due to the liquefaction effect. Finally, we conclude the paper with lessons from the tens of catastrophic landslides of municipal solid waste around the world and discuss how to better manage the geotechnical risks of urbanization.
HPR1000 is an advanced nuclear power plant (NPP) with the significant feature of an active and passive safety design philosophy, developed by the China National Nuclear Corporation. On one hand, it is an evolutionary design based on proven technology of the existing pressurized water reactor NPP; on the other hand, it incorporates advanced design features including a 177-fuel-assembly core loaded with CF3 fuel assemblies, active and passive safety systems, comprehensive severe accident prevention and mitigation measures, enhanced protection against external events, and improved emergency response capability. Extensive verification experiments and tests have been performed for critical innovative improvements on passive systems, the reactor core, and the main equipment. The design of HPR1000 fulfills the international utility requirements for advanced light water reactors and the latest nuclear safety requirements, and addresses the safety issues relevant to the Fukushima accident. Along with its outstanding safety and economy, HPR1000 provides an excellent and practicable solution for both domestic and international nuclear power markets.
Building cyber-physical system (CPS) models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control (CNC) system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control (NC) processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.
We have developed a new form of intravascular optical coherence tomography (IV-OCT) that allows the extremely fast acquisition of high-resolution images of the coronary arteries. This process leads to much better image quality by eliminating cardiac motion artefacts and undersampling. It relies on a catheter that incorporates a synchronous micromotor with a diameter of 1.0 mm and a rotational speed of up to 5600 revolutions per second, enabling an IV-OCT frame rate of 5.6 kHz. This speed is matched by a wavelength-swept laser that generates up to 2.8 million image lines per second. With this setup, our team achieved IV-OCT imaging of up to 5600 frames per second (fps) in vitro and 4000 fps in vivo, deployed at a 100 mm·s−1 pullback velocity. The imaging session is triggered by the electrocardiogram of the subject, and can scan a coronary artery in the phase of the heartbeat where the heart is at rest, providing a name for this new technology: the “Heartbeat OCT.”
This paper reviews the development of current research in bulk glassy alloys by focusing on the trigger point for the synthesis of the first bulk glassy alloys by the conventional mold casting method. This review covers the background, discovery, characteristics, and applications of bulk glassy alloys, as well as recent topics regarding them. Applications of bulk glassy alloys have been expanding, particularly for Fe-based bulk glassy alloys, due to their unique properties, high glass-forming ability, and low cost. In the near future, the engineering importance of bulk glassy alloys is expected to increase steadily, and continuous interest in these novel metallic materials for basic science research is anticipated.
Cellular spheroids serving as three-dimensional (3D) in vitro tissue models have attracted increasing interest for pathological study and drug-screening applications. Various methods, including microwells in particular, have been developed for engineering cellular spheroids. However, these methods usually suffer from either destructive molding operations or cell loss and non-uniform cell distribution among the wells due to two-step molding and cell seeding. We have developed a facile method that utilizes cell-embedded hydrogel arrays as templates for concave well fabrication and in situ MCF-7 cellular spheroid formation on a chip. A custom-built bioprinting system was applied for the fabrication of sacrificial gelatin arrays and sequentially concave wells in a high-throughput, flexible, and controlled manner. The ability to achieve in situ cell seeding for cellular spheroid construction was demonstrated with the advantage of uniform cell seeding and the potential for programmed fabrication of tissue models on chips. The developed method holds great potential for applications in tissue engineering, regenerative medicine, and drug screening.
This article focuses on the potential impact of big data analysis to improve health, prevent and detect disease at an earlier stage, and personalize interventions. The role that big data analytics may have in interrogating the patient electronic health record toward improved clinical decision support is discussed. We examine developments in pharmacogenetics that have increased our appreciation of the reasons why patients respond differently to chemotherapy. We also assess the expansion of online health communications and the way in which this data may be capitalized on in order to detect public health threats and control or contain epidemics. Finally, we describe how a new generation of wearable and implantable body sensors may improve wellbeing, streamline management of chronic diseases, and improve the quality of surgical implants.
Conventionally, an experimentally determined phase diagram requires studies of phase formation at a range of temperatures for each composition, which takes years of effort from multiple research groups. Combinatorial materials chip technology, featuring high-throughput synthesis and characterization, is able to determine the phase diagram of an entire composition spread of a binary or ternary system at a single temperature on one materials library, which, though significantly increasing efficiency, still requires many libraries processed at a series of temperatures in order to complete a phase diagram. In this paper, we propose a “one-chip method” to construct a complete phase diagram by individually synthesizing each pixel step by step with a progressive pulse of energy to heat at different temperatures while monitoring the phase evolution on the pixel in situ in real time. Repeating this process pixel by pixel throughout the whole chip allows the entire binary or ternary phase diagram to be mapped on one chip in a single experiment. The feasibility of this methodology is demonstrated in a study of a Ge-Sb-Te ternary alloy system, on which the amorphous-crystalline phase boundary is determined.
The issues of reducing CO2 levels in the atmosphere, sustainably utilizing natural mineral resources, and dealing with industrial waste offer challenging opportunities for sustainable development in energy and the environment. The latest advances in CO2 mineralization technology involving natural minerals and industrial waste are summarized in this paper, with great emphasis on the advancement of fundamental science, economic evaluation, and engineering applications. We discuss several leading large-scale CO2 mineralization methodologies from a technical and engineering-science perspective. For each technology option, we give an overview of the technical parameters, reaction pathway, reactivity, procedural scheme, and laboratorial and pilot devices. Furthermore, we present a discussion of each technology based on experimental results and the literature. Finally, current gaps in knowledge are identified in the conclusion, and an overview of the challenges and opportunities for future research in this field is provided.
Electron beam selective melting (EBSM) is an additive manufacturing technique that directly fabricates three-dimensional parts in a layerwise fashion by using an electron beam to scan and melt metal powder. In recent years, EBSM has been successfully used in the additive manufacturing of a variety of materials. Previous research focused on the EBSM process of a single material. In this study, a novel EBSM process capable of building a gradient structure with dual metal materials was developed, and a powder-supplying method based on vibration was put forward. Two different powders can be supplied individually and then mixed. Two materials were used in this study: Ti6Al4V powder and Ti47Al2Cr2Nb powder. Ti6Al4V has excellent strength and plasticity at room temperature, while Ti47Al2Cr2Nb has excellent performance at high temperature, but is very brittle. A Ti6Al4V/Ti47Al2Cr2Nb gradient material was successfully fabricated by the developed system. The microstructures and chemical compositions were characterized by optical microscopy, scanning microscopy, and electron microprobe analysis. Results showed that the interface thickness was about 300 μm. The interface was free of cracks, and the chemical compositions exhibited a staircase-like change within the interface.