Improved Limits on Spin-Mass Interactions

Very light particles with CP-violating couplings to ordinary matter, such as axions or axion-like particles, can mediate long-range forces between polarized and unpolarized fermions. We describe a new experimental search for such forces between unpolarized nucleons in two 250 kg Pb weights and polarized neutrons and electrons in a $^3$He-K co-magnetometer located about 15 cm away. We place improved constrains on the products of scalar and pseudoscalar coupling constants, $g^n_p g^N_s < 4.2\times10^{-30}$ and $g^e_p g^N_s < 1.7\times10^{-30}$ (95% CL) for axion-like particle masses less than $10^{-6}$ eV, which represents an order of magnitude improvement over the best previous neutron laboratory limit

New limits on Anomalous Spin-Spin Interactions

We report the results of a new search for long range spin-dependent interactions using a Rb -$^{21}$Ne atomic comagnetometer and a rotatable electron spin source based on a SmCo$_{5}$ magnet with an iron flux return. By looking for signal correlations with the orientation of the spin source we set new constrains on the product of the pseudoscalar electron and neutron couplings $g^e_p g^n_p/\hbar c<1.7\times10^{-14}$ and on the product of their axial couplings $g^e_A g^n_A/\hbar c<5\times10^{-42}$ to a new particle with a mass of less than about $1~\mu$eV. Our measurements improve by about 2 orders of magnitude previous constraints on such spin-dependent interactions.Comment: 4 pages, 4 figure

Laboratory Constraints on the Neutron-Spin Coupling of feV-scale Axions

Ultralight axion-like particles can contribute to the dark matter near the Sun, leading to a distinct, stochastic signature in terrestrial experiments. We search for such particles through their neutron-spin coupling by re-analyzing approximately 40 days of data from a K-$^3$He co-magnetometer with a new frequency-domain likelihood-based formalism that properly accounts for stochastic effects over all axion coherence times relative to the experimental time span. Assuming that axions make up all of the dark matter in the Sun's vicinity, we find a median 95% upper limit on the neutron-spin coupling of $2.4 \times 10^{-10}$ GeV$^{{-1}}$ for axion masses from 0.4 to 4 feV, which is about five orders of magnitude more stringent than previous laboratory bounds in that mass range. Although several peaks in the experiment's magnetic power spectrum suggest the rejection of a white-noise null hypothesis, further analysis of their lineshapes yields no positive evidence for a dark matter axion.Comment: 23 pages, 15 figure

On the modelling of powder flow, material addition and thermal behaviours in LENS process

Application of 3D printing technologies for fabricating various metal products are receiving ever-increasing attention in the advanced manufacturing fields, e.g. aerospace, automobile and biomedical engineering. Laser engineering net shaping (LENS) is one of the promising 3D printing techniques that suitable for depositing fully-densed critical metal components of complex geometry layer-by-layer. Based on directed energy deposition, LENS process sprays metal powders into a moving molten pool generated by an energy-intensive laser and consequently deposits solid tracks on the substrate surface with the movement of the laser spot. Accurate numerical modelling of this additive manufacturing process is really a challenge due to involving in multiple physical-mechanical interactions along with the mass and heat flows. This research first reviews the existing metal powders technologies using and especially focusing on the LENS process. Then, powder dynamics for the metal powders being conveyed by carrier gas within the internal passages of laser deposition head and after being ejected from the nozzles are modelled and analysed to give a better understanding of the key physical stage during the LENS process. Material addition on the deposition layer is modelled by using finite element addition; thermal behaviours of substrate and temperature distribution caused by the moving laser beam during the LENS process are also studied by using FEM analysis. An in-depth study of the powder flow and its dynamics in LENS process via numerical simulation will facilitate subsequent research on mass addition on the deposited layers. An accurate thermal-mechanical model could be applied to further investigate the interactions between laser, molten pool and deposited track and finally predict the residual stress and possible cracks on the deposited layers. This research will be particularly useful for investigating the production of key complex components which are made by LENS process due to difficult-to-machine materials properties and have more demanding requirement on their functional performance

Selective discrimination and classification of G-quadruplex structures with a host–guest sensing array

The secondary structures of nucleic acids have an important influence on their cellular functions but can be difficult to identify and classify quickly. Here, we show that an arrayed suite of synthetic hosts and dyes is capable of fluorescence detection of oligonucleotide secondary structures. Multivariate analysis of different fluorescence enhancements—generated using cationic dyes that show affinity for both DNA G-quadruplexes and the synthetic hosts—enables discrimination between G-quadruplex structures of identical length and highly similar topological types. Different G-quadruplexes that display the same folding topology can also be easily differentiated by the number of G-quartets and sequence differences at the 3′ or 5′ ends. The array is capable of both differentiation and classification of the G-quadruplex structures at the same time. This simple non-invasive sensing method does not require the discovery and synthesis of specific G-quadruplex binding ligands, but employs a simple multicomponent approach to ensure wide applicability

An NgAgo tool for genome editing: did CRISPR/Cas9 just find a competitor?

AbstractWhile CRISPR/Cas9-mediated genome editing technology has been experiencing a rapid transformation during the past few years, a recent report on NgAgo-mediated single-stranded DNA-guided genome editing may offer an attractive alternative for genome manipulation. While it's too early to predict whether NgAgo will be able to compete with or be superior to CRISPR/Cas9, the scientific community is anxiously waiting for further optimization and broader applications of the NgAgo genome editing technology

Characterization of Terrestrial Water Dynamics in the Congo Basin Using GRACE and Satellite Radar Altimetry

The Congo Basin is the world's third largest in size (approx.3.7 million sq km), and second only to the Amazon River in discharge (approx.40,200 cu m/s annual average). However, the hydrological dynamics of seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3deg 3deg regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111 cu km, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain

Validation of the Chinese version 10-item Perceived Efficacy in Patient-Physician Interactions scale in patients with osteoarthritis

OBJECTIVES: This study aimed to assess the reliability and validity of the Chinese version of the 10-item Perceived Efficacy in Patient–Physician Interaction (PEPPI-10) scale in hospitalized patients with severe knee osteoarthritis in the People’s Republic of China. METHODS: Between January and March 2015, the Chinese versions of PEPPI, self-efficacy for exercise scale, osteoporosis self-efficacy scale, and modified fall efficacy scale were applied to assess 110 severe knee osteoarthritis patients who were hospitalized in the second ward of the department of arthroplasty surgery of Tianjin Hospital. RESULTS: The Chinese version of the PEPPI-10 scale had a high coefficient of internal consistency (Cronbach’s α coefficient, 0.907). The score of the Chinese version of PEPPI was weakly correlated with the scores of the Chinese versions of self-efficacy for exercise scale, osteoporosis self-efficacy scale, and modified fall efficacy scale. CONCLUSION: The Chinese version of the PEPPI-10 scale exhibits sufficient internal consistency and convergent validity in hospitalized patients with severe knee osteoarthritis in the People’s Republic of China

Optimizing Fresh Agricultural Product Distribution Paths Under Demand Uncertainty

Consumers' demand for fresh agricultural products (FAPs) and their quality requirements are increasing in the current agricultural-product consumption market. FAPs' unique perishability and short shelf-life features mean a high level of delivery efficiency is required to ensure their freshness and quality. However, consumers' demand for FAPs is contingent and geographically dispersed. Therefore, the conflicting relationship between the costs associated with the logistics distribution and the level of delivery quality is important to consider. In this paper, the authors consider a fresh agricultural-product distribution path planning problem with time windows (FAPDPPPTW). To address the FAPDPPPTW under demand uncertainty, a mixed-integer linear programming model based on robust optimization is proposed. Moreover, a particle swarm optimization algorithm combined with a variable neighborhood search is designed to solve the proposed mathematical model. The numerical experiment results show the robustness and fast convergence of the algorithm.</p