| 1. |
- Zhang, Yanqing, et al.
(author)
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HflX is a ribosome-splitting factor rescuing stalled ribosomes under stress conditions
- 2015
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In: Nature Structural & Molecular Biology. - : Springer Science and Business Media LLC. - 1545-9993 .- 1545-9985. ; 22:11, s. 906-913
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Journal article (peer-reviewed)abstract
- Adverse cellular conditions often lead to nonproductive translational stalling and arrest of ribosomes on mRNAs. Here, we used fast kinetics and cryo-EM to characterize Escherichia coil HflX, a GTPase with unknown function. Our data reveal that HflX is a heat shock-induced ribosome-splitting factor capable of dissociating vacant as well as mRNA-associated ribosomes with deacylated tRNA in the peptidyl site. Structural data demonstrate that the N-terminal effector domain of HflX binds to the peptidyl transferase center in a strikingly similar manner as that of the class I release factors and induces dramatic conformational changes in central intersubunit bridges, thus promoting subunit dissociation. Accordingly, loss of HflX results in an increase in stalled ribosomes upon heat shock, These results suggest a primary role of HflX in rescuing translationally arrested ribosomes under stress conditions.
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| 2. |
- Chen, Zhang, et al.
(author)
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Making monolayer graphene photoluminescent by electron-beam-activated fluorination approach
- 2023
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In: Applied Surface Science. - : Elsevier. - 0169-4332 .- 1873-5584. ; 608
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Journal article (peer-reviewed)abstract
- The past one and half decades have witnessed a tremendous development of graphene electronics, and the key to the success of graphene is its exceptional properties. The lacking of an inherent bandgap endows graphene with excellent electrical properties but considerably limits its applications in light-emitting and high-performance graphene-based devices. Herein, an approach for the direct writing of semiconducting and photoluminescent fluorinated graphene (C4F) patterns on monolayer graphene by an optimized electron-beam-activated fluorination technique is reported. A series of characterization approaches, such as atomic force microscopy, X-ray photoelectron spectroscopy and Raman spectroscopy were used to demonstrate the successful preparation of C4F for maskless lithography. Specially, a sharp and strong photoluminescence located at the purple light range of ∼380 nm was observed in C4F, demonstrating a desirable semiconducting nature, and the bandgap was further confirmed by follow-up electrical measurements, where the C4F filed-effect transistor exhibited a p-type semiconductor behavior and significantly enhanced on/off ratio. Therefore, this work provides a novel technique for the fabrication of graphene devices for promising electronic and optoelectronic applications, but also opens a route towards the tailoring and engineering of electronic properties of graphene.
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| 3. |
- Mu, Cuicui, et al.
(author)
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Ecosystem CO2 Exchange and Its Economic Implications in Northern Permafrost Regions in the 21st Century
- 2023
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In: Global Biogeochemical Cycles. - 0886-6236. ; 37:11
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Journal article (peer-reviewed)abstract
- Climate warming increases carbon assimilation by plant growth and also accelerates permafrost CO2 emissions; however, the overall ecosystem CO2 balance in permafrost regions and its economic impacts remain largely unknown. Here we synthesize in situ measurements of net ecosystem CO2 exchange to assess current and future carbon budgets across the northern permafrost regions using the random forest model and calculate their economic implications under the Shared Socio-economic Pathways (SSPs) based on the PAGE-ICE model. We estimate a contemporary CO2 emission of 1,539 Tg C during the nongrowing season and CO2 uptake of 2,330 Tg C during the growing season, respectively. Air temperature and precipitation exert the most control over the net ecosystem exchange in the nongrowing season, while leaf area index plays a more important role in the growing season. This region will probably shift to a carbon source after 2,057 under SSP5-8.5, with a net emission of 17 Pg C during 2057–2100. The net economic benefits of CO2 budget will be $4.5, $5.0, and $2.9 trillion under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. Our results imply that a high-emission pathway will greatly reduce the economic benefit of carbon assimilation in northern permafrost regions.
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| 4. |
- Wang, Shiwei, et al.
(author)
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26.8-m THz wireless transmission of probabilistic shaping 16-QAM-OFDM signals
- 2020
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In: APL Photonics.. - : AIP Publishing. - 2378-0967. ; 5:5
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Journal article (peer-reviewed)abstract
- Recently, remarkable efforts have been made in developing wireless communication systems at ultrahigh data rates, with radio frequency (RF) carriers in the millimeter wave (30-300 GHz) and/or in the terahertz (THz, >300 GHz) bands. Converged technologies combining both the electronics and the photonics show great potential to provide feasible solutions with superior performance compared to conventional RF technologies. However, technical challenges remain to be overcome in order to support high data rates with considerably feasible wireless distances for practical applications, particularly in the THz region. In this work, we present an experimental demonstration of a single-channel THz radio-over-fiber (RoF) system operating at 350 GHz, achieving beyond 100 Gbit/s data rate over a 10-km fiber plus a >20-m wireless link, without using any THz amplifiers. This achievement is enabled by using an orthogonal frequency division multiplexing signal with a probabilistic-shaped 16-ary quadrature amplitude modulation format, a pair of highly directive Cassegrain antennas, and advanced digital signal processing techniques. This work pushes the THz RoF technology one step closer to ultrahigh-speed indoor wireless applications and serves as an essential segment of the converged fiber-wireless access networks in the beyond 5G era.
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| 5. |
- Zhang, Zhuangzhuang, et al.
(author)
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Digital twin-enabled grasp outcomes assessment for unknown objects using visual-tactile fusion perception
- 2023
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In: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 84
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Journal article (peer-reviewed)abstract
- Humans can instinctively predict whether a given grasp will be successful through visual and rich haptic feedback. Towards the next generation of smart robotic manufacturing, robots must be equipped with similar capabilities to cope with grasping unknown objects in unstructured environments. However, most existing data-driven methods take global visual images and tactile readings from the real-world system as input, making them incapable of predicting the grasp outcomes for cluttered objects or generating large-scale datasets. First, this paper proposes a visual-tactile fusion method to predict the results of grasping cluttered objects, which is the most common scenario for grasping applications. Concretely, the multimodal fusion network (MMFN) uses the local point cloud within the gripper as the visual signal input, while the tactile signal input is the images provided by two high-resolution tactile sensors. Second, collecting data in the real world is high-cost and time-consuming. Therefore, this paper proposes a digital twin-enabled robotic grasping system to collect large-scale multimodal datasets and investigates how to apply domain randomization and domain adaptation to bridge the sim-to-real transfer gap. Finally, extensive validation experiments are conducted in physical and virtual environments. The experimental results demonstrate the effectiveness of the proposed method in assessing grasp stability for cluttered objects and performing zero-shot sim-to-real policy transfer on the real robot with the aid of the proposed migration strategy.
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| 6. |
- Zheng, Xiaoxiao, et al.
(author)
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Graphene-Oxide-Based Fluoro- and Chromo-Genic Materials and Their Applications
- 2022
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In: Molecules. - : MDPI AG. - 1431-5157 .- 1420-3049. ; 27:6
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Journal article (peer-reviewed)abstract
- Composite materials and their applications constitute a hot field of research nowadays due to the fact that they comprise a combination of the unique properties of each component of which they consist. Very often, they exhibit better performance and properties compared to their combined building blocks. Graphene oxide (GO), as the most widely used derivative of graphene, has attracted widespread attention because of its excellent properties. Abundant oxygen-containing functional groups on GO can provide various reactive sites for chemical modification or functionalization of GO, which in turn can be used to develop novel GO-based composites. This review outlines the most recent advances in the field of novel dyes and pigments encompassing GO as a key ingredient or as an important cofactor. The interactions of graphene with other materials/compounds are highlighted. The special structure and unique properties of GO have a great effect on the performance of fabricated hybrid dyes and pigments by enhancing the color performance of dyes, the anticorrosion properties of pigments, the viscosity and rheology of inks, etc., which further expands the applications of dyes and pigments in dyeing, optical elements, solar-thermal energy storage, sensing, coatings, and microelectronics devices. Finally, challenges in the current development as well as the future prospects of GO-based dyes and pigments are also discussed. This review provides a reference for the further exploration of novel dyes and pigments.
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| 7. |
- Bolmsjö, Gunnar, et al.
(author)
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Safety System for Industrial Robots to Support Collaboration
- 2016
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In: Advances in Ergonomics of Manufacturing. - Cham : Springer International Publishing. - 9783319416960 - 9783319416977 ; , s. 253-265
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Book chapter (peer-reviewed)abstract
- The ongoing trend towards manufacturing of customized products generates an increased demand on highly efficient work methods to manage product variants through flexible automation. Adopting robots for automation is not always feasible in low batch production. However, the combination of humans together with robots performing tasks in collaboration provides a complementary mix of skill and creativity of humans, and precision and strength of robots which support flexible production in small series down to one-off production. Through this, collaboration can be used with implications on reconfiguration and production. In this paper, the focus and study is on designing safety for efficient collaboration operator—robot in selected work task scenarios. The recently published ISO/TS 15066:2016 describing collaboration between operator and robot is in this context an important document for development and implementation of robotic systems designed for collaboration between operator and robot.
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| 8. |
- Chen, Lan, et al.
(author)
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A modified ionization difference UV-vis method for fast quantitation of guaiacyl-type phenolic hydroxyl groups in lignin
- 2022
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In: International Journal of Biological Macromolecules. - : Elsevier BV. - 0141-8130 .- 1879-0003. ; 201, s. 330-337
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Journal article (peer-reviewed)abstract
- An ionization difference UV-Vis method (Delta epsilon-spectrum method) is the most potentially simple method for fast quantitation of phenolic hydroxyl groups (ph-OH) in lignin. However, the underestimated results were calculated from the conventional Delta epsilon-spectrum method using one- or two-point wavelengths measurement. In this study, a modified Delta epsilon-spectrum method using multi-point wavelengths measurement was developed and the negative absorbance was also considered. Four main typical lignin models, e.g. vanilla alcohol, 5-5 biphenyl, stilbenoid and vanillin, were applied as the guaiacyl-type (G-type) phenolic models for the determination of ph-OH by the modified Delta epsilon-spectrum method. The 2-methoxyethanol/water/acetic acid = 8/2/0.2 (V/V/V) was used as the acidic solvent system and the 2-methoxyethanol/0.2 M NaOH solution = 1/9 (V/V) was used as the alkaline solvent system. The ph-OH contents in the spruce milled wood lignin (SMWL) and the spruce Kraft lignin (SKL) were respectively quantified by the modified Delta epsilon-spectrum method as 1.078 and 4.348 mmol/g, which were comparable to the counterparts determined by P-31 Nuclear Magnetic Resonance Spectroscopy (P-31 NMR). The results revealed that the modified Delta epsilon-spectrum method can provide more accurate and reliable results compared to the conventional method.
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| 9. |
- Ericsson, Mikael, 1975-, et al.
(author)
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Virtual Commissioning of Machine Vision Applications in Aero Engine Manufacturing
- 2018
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In: Proceedings of The 15th International Conference on Control,Automation, Robotics and Vision, November 18-21, 2018. - 9781538695814 ; , s. 1947-1952
-
Conference paper (peer-reviewed)abstract
- New aero engine design puts new demands on the manufacturing methods with increased automation level. Therefore, the use of vision sensors for control and guiding of industrial robots is being increasingly used. In such system, it is need to customise the machine vision system with real components in the real environment which is normally done close to the start-up of the production. This paper addresses a new concept for designing, programming, analysing, testing and verifying a machine vision application early in the design phase, called Virtual Machine Vision. It is based on a robot simulation software where the real machine vision application is simulated before the implementation in the production line. To verify the Virtual Machine Vision concept an advanced stereo vision application was used. Using two captured images from the robot simulated environment, camera calibration, image analysis and stereo vision algorithms are applied to determine a desired welding joint. The information of the weld joint, i.e. robot position and orientation for the weld path, are sent from the machine vision system to the robot control system in the simulation environment and the weld path is updated. The validation of the Virtual Machine Vision concept using the stereo vision application is promising for industrial use, and it is emphasised that the same programs are used in the virtual and real word.
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| 10. |
- Eriksson, Kristina M., 1976-, et al.
(author)
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Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning
- 2022
-
In: Procedia CIRP. - : Elsevier BV. - 2212-8271 .- 2212-8271. ; 107, s. 955-960
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Journal article (peer-reviewed)abstract
- Increased environmental awareness is driving the manufacturing industry towards novel ways of energy reduction to become sustainable yet stay competitive. Climate and enviromental challenges put high priority on incorporating aspects of sustainability into both strategic and operational levels, such as production scheduling, in the manufacturing industry. Considering energy as a parameter when planning makes an already existing highly complex task of production scheduling even more multifaceted. The focus in this study is on inverse scheduling, defined as the problem of finding the number of jobs and duration times to meet a fixed input capacity. The purpose of this study was to investigate how scheduling can be formulated, within the environment of discrete event simulation coupled with reinforcement learning, to meet production demands while simultaneously minimize makespan and reduce energy. The study applied the method of modeling a production robot cell with its uncertainties, using discrete event simulation combined with deep reinforcement learning and trained agents. The researched scheduling approach derived solutions that take into consideration the performance measures of energy use. The method was applied and tested in a simulation environment with data from a real robot production cell. The study revealed opportunities for novel approaches of studying and reducing energy in the manufacturing industry. Results demonstrated a move towards a more holistic approach for production scheduling, which includes energy usage, that can aid decision-making and facilitate increased sustainability in production. We propose a conceptual framework for scheduling for minimizing energy use applying discrete event simulation as an environment for deep reinforcement learning.
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