Biochemical and structural characterization of Cren7, a novel chromatin protein conserved among Crenarchaea

Archaea contain a variety of chromatin proteins consistent with the evolution of different genome packaging mechanisms. Among the two main kingdoms in the Archaea, Euryarchaeota synthesize histone homologs, whereas Crenarchaeota have not been shown to possess a chromatin protein conserved at the kingdom level. We report the identification of Cren7, a novel family of chromatin proteins highly conserved in the Crenarchaeota. A small, basic, methylated and abundant protein, Cren7 displays a higher affinity for double-stranded DNA than for single-stranded DNA, constrains negative DNA supercoils and is associated with genomic DNA in vivo. The solution structure and DNA-binding surface of Cren7 from the hyperthermophilic crenarchaeon Sulfolobus solfataricus were determined by NMR. The protein adopts an SH3-like fold. It interacts with duplex DNA through a β-sheet and a long flexible loop, presumably resulting in DNA distortions through intercalation of conserved hydrophobic residues into the DNA structure. These data suggest that the crenarchaeal kingdom in the Archaea shares a common strategy in chromatin organization

Sciences for The 2.5-meter Wide Field Survey Telescope (WFST)

The Wide Field Survey Telescope (WFST) is a dedicated photometric survey facility under construction jointly by the University of Science and Technology of China and Purple Mountain Observatory. It is equipped with a primary mirror of 2.5m in diameter, an active optical system, and a mosaic CCD camera of 0.73 Gpix on the main focus plane to achieve high-quality imaging over a field of view of 6.5 square degrees. The installation of WFST in the Lenghu observing site is planned to happen in the summer of 2023, and the operation is scheduled to commence within three months afterward. WFST will scan the northern sky in four optical bands (u, g, r, and i) at cadences from hourly/daily to semi-weekly in the deep high-cadence survey (DHS) and the wide field survey (WFS) programs, respectively. WFS reaches a depth of 22.27, 23.32, 22.84, and 22.31 in AB magnitudes in a nominal 30-second exposure in the four bands during a photometric night, respectively, enabling us to search tremendous amount of transients in the low-z universe and systematically investigate the variability of Galactic and extragalactic objects. Intranight 90s exposures as deep as 23 and 24 mag in u and g bands via DHS provide a unique opportunity to facilitate explorations of energetic transients in demand for high sensitivity, including the electromagnetic counterparts of gravitational-wave events detected by the second/third-generation GW detectors, supernovae within a few hours of their explosions, tidal disruption events and luminous fast optical transients even beyond a redshift of 1. Meanwhile, the final 6-year co-added images, anticipated to reach g about 25.5 mag in WFS or even deeper by 1.5 mag in DHS, will be of significant value to general Galactic and extragalactic sciences. The highly uniform legacy surveys of WFST will also serve as an indispensable complement to those of LSST which monitors the southern sky.Comment: 46 pages, submitted to SCMP

A USV-UAV Cooperative Trajectory Planning Algorithm with Hull Dynamic Constraints

Efficient trajectory generation in complex dynamic environments remains an open problem in the operation of an unmanned surface vehicle (USV). The perception of a USV is usually interfered by the swing of the hull and the ambient weather, making it challenging to plan optimal USV trajectories. In this paper, a cooperative trajectory planning algorithm for a coupled USV-UAV system is proposed to ensure that a USV can execute a safe and smooth path as it autonomously advances through multi-obstacle maps. Specifically, the unmanned aerial vehicle (UAV) plays the role of a flight sensor, providing real-time global map and obstacle information with a lightweight semantic segmentation network and 3D projection transformation. An initial obstacle avoidance trajectory is generated by a graph-based search method. Concerning the unique under-actuated kinematic characteristics of the USV, a numerical optimization method based on hull dynamic constraints is introduced to make the trajectory easier to be tracked for motion control. Finally, a motion control method based on NMPC with the lowest energy consumption constraint during execution is proposed. Experimental results verify the effectiveness of the whole system, and the generated trajectory is locally optimal for USV with considerable tracking accuracy

A USV-UAV Cooperative Trajectory Planning Algorithm with Hull Dynamic Constraints

Efficient trajectory generation in complex dynamic environments remains an open problem in the operation of an unmanned surface vehicle (USV). The perception of a USV is usually interfered by the swing of the hull and the ambient weather, making it challenging to plan optimal USV trajectories. In this paper, a cooperative trajectory planning algorithm for a coupled USV-UAV system is proposed to ensure that a USV can execute a safe and smooth path as it autonomously advances through multi-obstacle maps. Specifically, the unmanned aerial vehicle (UAV) plays the role of a flight sensor, providing real-time global map and obstacle information with a lightweight semantic segmentation network and 3D projection transformation. An initial obstacle avoidance trajectory is generated by a graph-based search method. Concerning the unique under-actuated kinematic characteristics of the USV, a numerical optimization method based on hull dynamic constraints is introduced to make the trajectory easier to be tracked for motion control. Finally, a motion control method based on NMPC with the lowest energy consumption constraint during execution is proposed. Experimental results verify the effectiveness of the whole system, and the generated trajectory is locally optimal for USV with considerable tracking accuracy

Deep Learning-Based Intelligent Forklift Cargo Accurate Transfer System

In this research, we present an intelligent forklift cargo precision transfer system to address the issue of poor pallet docking accuracy and low recognition rate when using current techniques. The technology is primarily used to automatically check if there is any pallet that need to be transported. The intelligent forklift is then sent to the area of the target pallet after being recognized. Images of the pallets are then collected using the forklift’s camera, and a deep learning-based recognition algorithm is used to calculate the precise position of the pallets. Finally, the forklift is controlled by a high-precision control algorithm to insert the pallet in the exact location. This system creatively introduces the small target detection into the pallet target recognition system, which greatly improves the recognition rate of the system. The application of Yolov5 into the pallet positional calculation makes the coverage and recognition accuracy of the algorithm improved. In comparison with the prior approach, this system’s identification rate and accuracy are substantially higher, and it requires fewer sensors and indications to help with deployment. We have collected a significant amount of real data in order to confirm the system’s viability and stability. Among them, the accuracy of pallet docking is evaluated 1000 times, and the inaccuracy is kept to a maximum of 6 mm. The recognition rate of pallet recognition is above 99.5% in 7 days of continuous trials

some improvements on model checking coreasm models of security protocols

University of Buffalo (UB); The State University of New YorkThis paper presents a tool called ASM-SPV (Abstract State Machines-Security Protocols Verifier) for verifying security protocols by model checking. In ASM-SPV, a security protocol is modeled by CoreASM language which is an executable ASM (Abstract State Machines) language. Then a modified CoreASM engine takes the CoreASM model of the protocol to build state space on-demand. Furthermore, security properties of the protocol are described as CTL (Computation Tree Logic) formulas and an adapted model checking algorithm is introduced to check whether the CoreASM model satisfies a given CTL formula or not. In this paper, we show the effectiveness of ASM-SPV with regard to memory consumption and speed of generating states compared with another CoreASM based model checker [mc]square. © 2010 IEEE

Green and Short Preparation of CeO2 Nanoparticles with Large Specific Surface Area by Spray Pyrolysis

Green and short preparation of CeO2 nanoparticles with large specific surface area from rare earth extraction (CeCl3) was successfully achieved by spray pyrolysis (SP). In this method, a precursor solution is first prepared by mixing CeCl3, C6H8O, and H2O in the requisite quantities. Subsequently, the precursor consisting of a mixture of CeO2 and C was obtained by SP method by using the precursor solution. Finally, the calcination at 500 °C~800 °C in air for two hours to transform the precursor to CeO2 nanoparticles. Thermodynamic analysis and experimental studies were performed to determine the optimal SP temperature and citric acid amount. The results indicated that the maximum specific surface area (59.72 m2/g) of CeO2 nanoparticles were obtained when the SP temperature was 650 °C and the molar ratio of citric acid to CeCl3 was 1.5

Data_Sheet_1_Plant-soil-enzyme C-N-P stoichiometry and microbial nutrient limitation responses to plant-soil feedbacks during community succession: A 3-year pot experiment in China.docx

Studying plant-soil feedback (PSF) can improve the understanding of the plant community composition and structure; however, changes in plant-soil-enzyme stoichiometry in response to PSF are unclear. The present study aimed to analyze the changes in plant-soil-enzyme stoichiometry and microbial nutrient limitation to PSF, and identify the roles of nutrient limitation in PSF. Setaria viridis, Stipa bungeana, and Bothriochloa ischaemum were selected as representative grass species in early-, mid-, and late-succession; furthermore, three soil types were collected from grass species communities in early-, mid-, and late-succession to treat the three successional species. A 3-year (represents three growth periods) PSF experiment was performed with the three grasses in the soil in the three succession stages. We analyzed plant biomass and plant-soil-enzyme C-N-P stoichiometry for each plant growth period. The plant growth period mainly affected the plant C:N in the early- and late- species but showed a less pronounced effect on the soil C:N. During the three growth periods, the plants changed from N-limited to P-limited; the three successional species soils were mainly limited by N, whereas the microbes were limited by both C and N. The plant-soil-enzyme stoichiometry and plant biomass were not significantly correlated. In conclusion, during PSF, the plant growth period significantly influences the plant–soil–microbial nutrient limitations. Plant-soil-enzyme stoichiometry and microbial nutrient limitation cannot effectively explain PSF during succession on the Loess Plateau.</p

Multiscale agent-based modelling of ovarian cancer progression under the stimulation of the STAT 3 pathway

This research is developed to simulate ovarian cancer progression with signal transducers and activators of the transcription 3 (STAT 3) pathway. The main focus is on studying how the STAT 3 pathway affects the cancer cells\u27 biomechanical phenotype under the stimulation of the interleukin-6 (IL- 6) cytokine and various well-known microscopic factors. The simulated results agreed with recent experimental evidence that ovarian cancer cells with a stimulated STAT 3 pathway have high survival rates and drug resistance. And we discussed how the IL6 and these well-known microscopic factors impacted the cancer progression. Copyright © 2014 Inderscience Enterprises Ltd

Cortical Bone under an Ultrahigh Magnetic Field: Relaxation, Spectroscopy and Micron-resolution Imaging

Compact, mineralized cortical bone tissues are often concealed on magnetic resonance (MR) images. Recent development of MR instruments and pulse techniques has yielded significant advances in acquiring anatomical and physiological information from cortical bone despite its poor 1H signals. This work demonstrates the first MR research on cortical bones under an ultrahigh magnetic field of 14 T. The 1H signals of different mammalian species exhibit multi-exponential decays of three characteristic T2 or T2* values: 0.1–0.5 ms, 1–4 ms, and 4–8 ms. Systematic sample comparisons attribute these T2/T2* value ranges to collagen-bound water, pore water, and lipids, respectively. Ultrashort echo time (UTE) imaging under 14 T yielded spatial resolutions of 20–80 microns, which resolves the three-dimensional anatomy of the Haversian canals. The T2* relaxation characteristics further allow spatial classifications of collagen, pore water and lipids in human specimens. Our study achieves a record of the spatial resolution for MR imaging in bone and shows that ultrahigh-field MR has the unique ability to differentiate the soft and organic compartments in bone tissues