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The homogeneous cooling process of binary mixtures of large aspherical particles and small spheres is modeled using DEM. The dissipation rate increases with the increasing total solid volume fraction of the mixture. For a specified total solid volume fraction of the mixture, the dissipation rate increases with the increasing fraction ratio of small spheres in the mixture. Energy equipartition analysis shows that the translational and rotational components of the granular temperature for the large aspherical particles are generally equivalent. Energy equipartition is also present between the translational granular temperature for the large and small particles. Both particle aspect ratio and shape irregularity affect the collisional dissipation rate. The collisional dissipation rate increases with the aspect ratio (AR) for the same particle shape. For the same AR, the collisional dissipation rate of more-irregular oval-like particles are larger than less-irregular rod-like particles. The collisional dissipation rate decreases with the increasing particle sphericity.

Evidence accumulated over the past decade has verified that long non-coding RNAs (lncRNAs) exert important functions in multiple cell programs. As a novel class of cellular regulatory molecules, lncRNAs interact with different molecules, such as DNA, RNA or proteins, depending on their subcellular distribution, to modulate gene transcription and kinase cascades. It has been widely clarified that lncRNAs play important roles in modulating metabolic reprogramming and reshaping the immune landscape and serve as hinges bridging tumor metabolism and anti-tumor immunity. Given these facts, lncRNAs, as putative regulators of tumor initiation and progression, have attracted extensive attention in recent years. In this review, we summarized the current research progress on the role of lncRNAs in tumor metabolic reprogramming and tumor-immune microenvironment remodeling, and conclude with our laboratory's contributions in advancing the clinical applications of lncRNAs.

Cholesterol contributes to the structural basis of biological membranes and functions as a signaling molecule, whose dysregulation has been associated with various human diseases. Here, we report that the long non-coding RNA (lncRNA) SNHG6 increases progression from non-alcoholic fatty liver disease (NAFLD) to hepatocellular carcinoma (HCC) by modulating cholesterol-induced mTORC1 activation. Mechanistically, cholesterol binds ER-anchored FAF2 protein to promote the formation of a SNHG6-FAF2-mTOR complex. As a putative cholesterol effector, SNHG6 enhances cholesterol-dependent mTORC1 lysosomal recruitment and activation via enhancing FAF2-mTOR interaction at ER-lysosome contacts, thereby coordinating mTORC1 kinase cascade activation with cellular cholesterol biosynthesis in a self-amplified cycle to accelerate cholesterol-driven NAFLD-HCC development. Notably, loss of SNHG6 inhibits mTORC1 signaling and impairs growth of patient-derived xenograft liver cancer tumors, identifyifng SNHG6 as a potential target for liver cancer treatment. Together, our findings illustrate the crucial role of organelle-associated lncRNA in organelle communication, nutrient sensing, and kinase cascades.

The purpose of this study is to evaluate and compare the quantitative material decomposition performance of the dual-energy CT (DECT) and differential phase contrast CT (DPCT) via numerical observer studies.The electron density (The model observer results show that the DECT is superior to DPCT at 0.3 mm spatial resolution (300 mm object size); the DECT and DPCT show similar quantitative imaging performance at 0.1 mm spatial resolution (100 mm object size); and the DPCT outperforms the DECT by approximately 1.5 times for the 0.3 mm sized imaging target at 0.03 mm spatial resolution (30 mm object size).In conclusion, the DECT would be recommended to obtain

The purpose of this paper is to present an end-to-end deep convolutional neural network to improve the dual-energy CT (DECT) material decomposition performance.In this study, we proposes a unified mutual-domain (sinogram domain and CT domain) material decomposition network (DIRECT-Net) for DECT imaging. By design, the DIRECT-Net has immediate access to mutual-domain data, and utilizes stacked convolution neural network layers for noise reduction and material decomposition. The training data are numerically generated following the fundamental DECT imaging physics. Numerical simulation of the XCAT digital phantom, experiments of a biological specimen, a calcium chloride phantom and an iodine solution phantom are carried out to evaluate the performance of DIRECT-Net. Comparisons are performed with different DECT decomposition algorithms.Results demonstrate that the proposed DIRECT-Net can generate water and bone basis images with less artifacts compared to the other decomposition methods. Additionally, the quantification errors of the calcium chloride (75-375 mg/cmAn end-to-end material decomposition network is proposed for quantitative DECT imaging. The qualitative and quantitative results demonstrate that this new DIRECT-Net has promising benefits in improving the DECT image quality.

In this work, a general theoretical framework is presented to explain the formation of the phase signal in an X-ray microscope integrated with a grating interferometer, which simultaneously enables the high spatial resolution imaging and the improved image contrast. Using this theory, several key parameters of phase contrast imaging can be predicted, for instance, the fringe visibility and period, the conversion condition from the differential phase imaging (DPI) to the phase difference imaging (PDI). Additionally, numerical simulations are performed with certain X-ray optical components and imaging geometry. Results demonstrate the accuracy of this developed quantitative analysis method of X-ray phase-sensitive microscope imaging., 8 pages, 3 figures

Perovskite materials in different dimensions show great potential in direct X‐ray detection, but each with limitations stemming from its own intrinsic properties. Particularly, the sensitivity of two‐dimensional (2D) perovskites is limited by poor carrier transport while ion migration in three‐dimensional (3D) perovskites causes the baseline drifting problem. To circumvent these limitations, herein a double‐layer perovskite film is developed with properly aligned energy level, where 2D (PEA)2MA3Pb4I13 (PEA=2‐phenylethylammonium, MA=methylammonium) is cascaded with vertically crystallized 3D MAPbI3. In this new design paradigm, the 3D layer ensures fast carrier transport while the 2D layer mitigates ion migration, thus offering a high sensitivity and a greatly stabilized baseline. Besides, the 2D layer increases the film resistivity and enlarges the energy barrier for hole injection without compromising carrier extraction. Consequently, the double‐layer perovskite detector delivers a high sensitivity (1.95 × 104 μC Gyair −1 cm−2) and a low detection limit (480 nGyair s−1). Also demonstrated is the X‐ray imaging capacity using a circuit board as the object. This work opens up a new avenue for enhancing X‐ray detection performance via cascade assembly of various perovskites with complementary properties., By integrating a layered 2D perovskite with a vertically crystallized MAPbI3, a double‐layer perovskite is constructed for direct X‐ray detection, showing stable baseline, a high sensitivity of 19 503 μC Gyair −1 cm−2, and a low detection limit of 480 nGyair s−1. This work provides a strategy to unlock the performance limitations stemming from the intrinsic properties of the perovskite.

Sparse-view CT is a promising approach for reducing the x-ray radiation dose in clinical CT imaging. However, the CT images reconstructed from the conventional filtered backprojection algorithm suffer from severe streaking artifacts. Iterative reconstruction algorithms have been widely adopted to mitigate these streaking artifacts, but they may prolong the CT imaging time due to the intense data-specific computations. Recently, a model-driven deep learning CT image reconstruction method, which unrolls the iterative optimization procedures into a deep neural network, has shown exciting prospects for improving image quality and shortening the reconstruction time. In this work, we explore a generalized unrolling scheme for such an iterative model to further enhance its performance on sparse-view CT imaging. By using it, the iteration parameters, regularizer term, data-fidelity term and even the mathematical operations are all assumed to be learned and optimized via network training. Results from the numerical and experimental sparse-view CT imaging demonstrate that the newly proposed network with the maximum generalization provides the best reconstruction performance.

Objective. In this work, a dedicated end-to-end deep convolutional neural network, named as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different material distribution volumes from the dual-energy CBCT projection data. Approach. In Triple-CBCT, the features of the sinogram and the CT image are independently extracted and cascaded via a customized domain transform network module. This Triple-CBCT network was trained by numerically synthesized dual-energy CBCT data, and was tested with experimental dual-energy CBCT data of the Iodine-CaCl2 solution and pig leg specimen scanned on an in-house benchtop system. Main results. Results show that the information stored in both the sinogram and CT image domains can be used together to improve the decomposition quality of multiple materials (water, iodine, CaCl2 or bone) from the dual-energy projections. In addition, both the numerical and experimental results demonstrate that the Triple-CBCT is able to generate high-fidelity dual-energy CBCT basis images. Significance. An innovative end-to-end network that joints the sinogram and CT image domain information is developed to facilitate high quality automatic decomposition from the dual-energy CBCT scans.

In this work, a novel, to the best of our knowledge, approach based on an x-ray thin lens imaging theory is proposed to predict the angular sensitivity responses of dual-phase-grating differential phase contrast (DPC) interferometers. Experimental validations have been performed to demonstrate the high accuracy of theoretical predictions using two different setups: one with real source images and the other with virtual source images. This new sensitivity calculation method is helpful to optimize the DPC imaging performance of a dual-phase-grating system.

Purpose The goal of this study is to develop a three-dimensional (3D) iterative reconstruction framework based on the deep learning (DL) technique to improve the digital breast tomosynthesis (DBT) imaging performance. Methods In this work, the DIR-DBTnet is developed for DBT image reconstruction by mapping the conventional iterative reconstruction (IR) algorithm to the deep neural network. By design, the DIR-DBTnet learns and optimizes the regularizer and the iteration parameters automatically during the network training with a large amount of simulated DBT data. Numerical, experimental, and clinical data are used to evaluate its performance. Quantitative metrics such as the artifact spread function (ASF), breast density, and the signal difference to noise ratio (SDNR) are measured to assess the image quality. Results Results show that the proposed DIR-DBTnet is able to reduce the in-plane shadow artifacts and the out-of-plane signal leaking artifacts compared to the filtered backprojection (FBP) and the total variation (TV)-based IR methods. Quantitatively, the full width half maximum (FWHM) of the measured ASF from the clinical data is 27.1% and 23.0% smaller than those obtained with the FBP and TV methods, while the SDNR is increased by 194.5% and 21.8%, respectively. In addition, the breast density obtained from the DIR-DBTnet network is more accurate and consistent with the ground truth. Conclusions In conclusion, a deep iterative reconstruction network, DIR-DBTnet, has been proposed for 3D DBT image reconstruction. Both qualitative and quantitative analyses of the numerical, experimental, and clinical results demonstrate that the DIR-DBTnet has superior DBT imaging performance than the conventional algorithms.

7 pags., 5 figs., 2 tabs., The single-particle properties of Mg29 have been investigated via a measurement of the Mg28(d,p)Mg29 reaction, in inverse kinematics, using the ISOLDE Solenoidal Spectrometer. The negative-parity intruder states from the fp shell have been identified and used to benchmark modern shell-model calculations. The systematic data on the single-particle centroids along the N=17 isotones show good agreement with shell-model predictions in describing the observed trends from stability toward O25. However, there is also evidence that the effect of the finite geometry of the nuclear potential is playing a role on the behavior of the p orbitals near the particle-emission threshold., This work wassupported by the U.K. Science and Technology Facilities Council [Grants No. ST/P004598/1, No. ST/N002563/1, No. ST/M00161X/1 (Liverpool), No. ST/P004423/1 (Manchester), No. ST/P005314/1 (Surrey), the ISOL-SRS Grant (Daresbury), No. ST/R004056/1 (Ernest Rutherford Fellowship - Gaffney), and No. ST/T004797/1 (Ernest Rutherford Fellowship - Sharp)], the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, under Contracts No. DE-AC02-06CH11357 (ANL) and No. DE-SC-0014552 (UConn), the European Union’s Horizon 2020 Framework research and innovation program under Grant Agreement No. 654002 (ENSAR2), the Marie Skłodowska-Curie Grant Agreement No. 665779, the Research Foundation Flanders (FWO, Belgium), the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement No. 617156, and the Spanish Ministry of Science and Innovation under Grants No. PGC2018-095640- B-I00“ELEGANT” and No. PID2019-104390GB-I00. This research used targets provided by the Center for Accelerator Target Science at Argonne National Laboratory. The FSU shell-model calculations were performed using the computational facility of the nuclear physics theory group, Florida State University, supported by grants from the U.S. Department of Energy, Office of Science (DE-SC-0009883 (FSU).

Objective: The purpose of this work is to investigate the feasibility of using deep convolutional neural network (CNN) to improve the image quality of a grating-based X-ray differential phase contrast imaging (XPCI) system. Methods: In this work, a novel deep CNN based phase signal extraction and image noise suppression algorithm (named as XP-NET) is developed. The numerical phase phantom, the ex vivo biological specimen and the ACR breast phantom are evaluated via the numerical simulations and experimental studies, separately. Moreover, images are also evaluated under different low radiation levels to verify its dose reduction capability. Results: Compared with the conventional analytical method, the novel XP-NET algorithm is able to reduce the bias of large DPC signals and hence increasing the DPC signal accuracy by more than 15%. Additionally, the XP-NET is able to reduce DPC image noise by about 50% for low dose DPC imaging tasks. Conclusion: This proposed novel end-to-end supervised XP-NET has a great potential to improve the DPC signal accuracy, reduce image noise, and preserve object details. Significance: We demonstrate that the deep CNN technique provides a promising approach to improve the grating-based XPCI performance and its dose efficiency in future biomedical applications.

The nuclei below lead but with more than 126 neutrons are crucial to an understanding of the astrophysical r process in producing nuclei heavier than A∼190. Despite their importance, the structure and properties of these nuclei remain experimentally untested as they are difficult to produce in nuclear reactions with stable beams. In a first exploration of the shell structure of this region, neutron excitations in ^{207}Hg have been probed using the neutron-adding (d,p) reaction in inverse kinematics. The radioactive beam of ^{206}Hg was delivered to the new ISOLDE Solenoidal Spectrometer at an energy above the Coulomb barrier. The spectroscopy of ^{207}Hg marks a first step in improving our understanding of the relevant structural properties of nuclei involved in a key part of the path of the r process. ispartof: Physical Review Letters vol:124 issue:6 ispartof: location:United States status: published

Supplementary file to the manuscript

Export Date: 14 August 2020 ispartof: Acta Physica Polonica B vol:51 issue:3 pages:683-688 ispartof: location:POLAND, Piaski status: published

The design, realization and operation of a prototype or “demonstrator” version of an active target and time projection chamber (ACTAR TPC) for experiments in nuclear physics is presented in detail. The heart of the detection system features a micromegas gas amplifier coupled to a high-density pixelated pad plane with square pad sizes of 2 × 2 mm 2 . The detector has been thoroughly tested with several different gas mixtures over a wide range of pressures and using a variety of sources of ionizing radiation including laser light, an α -particle source and heavy-ion beams of 24Mg and 58Ni accelerated to energies of 4.0 MeV/u. Results from these tests and characterization of the detector response over a wide range of operating conditions will be described. These developments have served as the basis for the design of a larger detection system that is presently under construction.

Background: Aside from being a one-neutron halo nucleus, $^{15}\mathrm{C}$ is interesting because it is involved in reactions of relevance for several nucleosynthesis scenarios.Purpose: The aim of this work is to analyze various reactions involving $^{15}\mathrm{C}$, using a single structure model based on halo effective field theory (halo EFT) following the excellent results obtained in [P. Capel et al., Phys. Rev. C 98, 034610 (2018)].Method: To develop a halo-EFT model of $^{15}\mathrm{C}$ at next to leading order (NLO), we first extract the asymptotic normalization coefficient (ANC) of its ground state by analyzing $^{14}\mathrm{C}(d,p)^{15}\mathrm{C}$ transfer data at low energy using the method developed in [J. Yang and P. Capel, Phys. Rev. C 98, 054602 (2018)]. Using the halo-EFT description of $^{15}\mathrm{C}$ constrained with this ANC, we study the $^{15}\mathrm{C}$ Coulomb breakup at high (605 MeV/nucleon) and intermediate (68 MeV/nucleon) energies using eikonal-based models with a consistent treatment of nuclear and Coulomb interactions at all orders, and which take into account proper relativistic corrections. Finally, we study the $^{14}\mathrm{C}(n,\ensuremath{\gamma})^{15}\mathrm{C}$ radiative capture.Results: Our theoretical cross sections are in good agreement with experimental data for all reactions, thereby assessing the robustness of the halo-EFT model of this nucleus. Since a simple NLO description is enough to reproduce all data, the only nuclear-structure observables that matter are the $^{15}\mathrm{C}$ binding energy and its ANC, showing that all the reactions considered are purely peripheral. In particular, it confirms the value we have obtained for the ANC of the $^{15}\mathrm{C}$ ground state: ${\mathcal{C}}_{1/{2}^{+}}^{2}=1.59\ifmmode\pm\else\textpm\fi{}0.06\phantom{\rule{4pt}{0ex}}{\mathrm{fm}}^{\ensuremath{-}1}$. Our model of $^{15}\mathrm{C}$ provides also a new estimate of the radiative-capture cross section at astrophysical energy: ${\ensuremath{\sigma}}_{n,\ensuremath{\gamma}}(23.3\phantom{\rule{0.16em}{0ex}}\mathrm{keV})=4.66\ifmmode\pm\else\textpm\fi{}0.14\phantom{\rule{0.16em}{0ex}}\ensuremath{\mu}\mathrm{b}$.Conclusions: Including a halo-EFT description of $^{15}\mathrm{C}$ within precise models of reactions is confirmed to be an excellent way to relate the reaction cross sections and the structure of the nucleus. Its systematic expansion enables us to establish how the reaction process is affected by that structure and deduce which nuclear-structure observables are actually probed in the collision. From this, we can infer valuable information on both the structure of $^{15}\mathrm{C}$ and its synthesis through the $^{14}\mathrm{C}(n,\ensuremath{\gamma})^{15}\mathrm{C}$ radiative capture at astrophysical energies.

SpecMAT is a magnetic active target (AT) for transfer reaction studies with low-intensity radioactive ion beams at the ISOLDE facility (CERN). SpecMAT combines two types of detectors: a gas-filled time projection chamber (TPC), the core detector for tracking charged particles emitted in nuclear reactions, and an array of auxiliary scintillation detectors for in-flight γ -ray spectroscopy . All active target components are optimised for operation in a strong background magnetic field. The TPC has a cylindrical shape. Its electron detector is a bulk Micromegas segmented into 2916 triangular pads for sampling charged particle tracks . The scintillation array is composed of 45 detectors with cubic 48 × 48 × 48 mm 3 CeBr3 crystals. The General Electronics for TPC (GET) is used in SpecMAT to read out both detector types allowing correlation of the detected γ -rays with the TPC events. This article describes the SpecMAT active target and its characterisation with the α -decay of 241Am. A γ -ray spectrum obtained in correlation with 3D tracks left by charged particles in an active target is reported for the first time for such detectors.

The precise calibration of angular distribution of heavy-ion elastic scattering induced by Radioactive Ion Beams (RIBs) at energies around Coulomb barrier on the Radioactive Ion Beam Line in Lanzhou (RIBLL) at the Heavy-Ion Research Facility in Lanzhou (HIRFL) is presented. The beam profile and the scattering angles on the target are deduced by a measurement with two Multi Wire Proportional Chambers (MWPC), and four sets of detector telescopes (including Double-sided Silicon Strip Detectors (DSSD) placed systematically along the beam line, incorporating with Monte Carlo simulation. The MWPCs were used to determine the beam trajectory before the target, and the energies and the positions of scattered particles on the detectors were measured by the DSSDs. Minor corrections on the beam spot and the detector position are performed by assuming the pure Rutherford scattering at angles which are smaller than the related grazing angle. This method is applied for the elastic scattering of 17 F on 89 Y target at E lab =59 MeV and 50 MeV.

Recently, a loss of function variant (rs72613567) in 17-beta-hydroxysteroid dehydrogenase 13 (HSD17B13) has been identified as protective of nonalcoholic (NAFLD) and alcoholic liver disease (ALD). However, the role of this single-nucleotide polymorphism (SNP) in the development of hepatocellular carcinoma (HCC) is currently unknown. A total of 3,315 European patients with HCC (n = 1,109) or without HCC, but with chronic liver disease (CLD; n = 2,206), from four centers were analyzed either by whole-exome sequencing (WES; exploratory cohort, 285 HCC) or genotyped for HSD17B13 rs72613567 (validation cohort, 824 HCC and all CLD). We included a control group of 33,337 healthy European individuals from the Exome Aggregation Consortium. We compared distribution of genotype using the chi-square test and logistic regression. In the exploratory cohort analyzed by WES, frequency of the TA allele of HSD17B13 rs72613567 was significantly decreased in HCC patients compared to healthy controls (P = 1.52 × 10-06 ). In the validation cohort, frequency of TA allele carriers was also decreased in patients with CLD and without HCC (39%) compared to healthy individuals (47%; P < 0.0001). The protective effect of the TA allele of HSD17B13 rs72613567 was identified in patients with ALD (odds ratio [OR] = 0.73; 95% confidence interval [CI], 0.65-0.82; P < 0.0001), NAFLD (OR = 0.64; 95% CI, 0.49-0.83; P = 0.0007), and hepatitis C (OR = 0.71; 95% CI, 0.60-0.85; P = 0.0002). In patients with ALD, the proportion of TA allele carriers with HCC was significantly lower (32%) than in CLD patients without HCC (40%), even after adjustment for age, sex, and fibrosis (OR = 0.64; 95% CI, 0.46-0.87; P = 0.005). Conclusion: The HSD17B13 rs72613567 loss of function variant is protective of HCC development in patients with ALD.

The ACtive TARget and Time Projection Chamber (ACTAR TPC) is a novel gas-filled detector that has recently been constructed at GANIL. This versatile detector is a gaseous thick target that allows the tracking of charged particles in three dimensions and provides a precise reaction energy reconstruction from the vertex position. A commissioning experiment using resonant scattering of a 3.2MeV/nucleon 18O beam on an isobutane gas (proton) target was performed. The beam and the heavy scattered ions were stopped in the gas volume, while the light recoil left the active volume and were stopped in auxiliary silicon detectors. A dedicated tracking algorithm was applied to determine the angle of emission and the length of the trajectory of the ions, to reconstruct the reaction kinematics used to built the excitation functions of the 1H(18O, 18O)1H and 1H(18O, 15N)4He reactions. In this article, we describe the design of the detector and the data analysis, that resulted in center of mass reaction energy resolutions of 38(4)keV FWHM and 54(9)keV FWHM for the proton and alpha channels, respectively. The ACtive TARget and Time Projection Chamber (ACTAR TPC) is a novel gas-filled detector that has recently been constructed at GANIL. This versatile detector is a gaseous thick target that allows the tracking of charged particles in three dimensions and provides a precise reaction energy reconstruction from the vertex position. A commissioning experiment using resonant scattering of a 3.2MeV/nucleon 18O beam on an isobutane gas (proton) target was performed. The beam and the heavy scattered ions were stopped in the gas volume, while the light recoil left the active volume and were stopped in auxiliary silicon detectors. A dedicated tracking algorithm was applied to determine the angle of emission and the length of the trajectory of the ions, to reconstruct the reaction kinematics used to built the excitation functions of the 1H(18O, 18O)1H and 1H(18O, 15N)4He reactions. In this article, we describe the design of the detector and the data analysis, that resulted in center of mass reaction energy resolutions of 38(4)keV FWHM and 54(9)keV FWHM for the proton and alpha channels, respectively. ispartof: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment vol:940 pages:498-504 status: published

Through this study we propose to use sub-Coulomb transfer to investigate the one-neutron halo phenomenon within nuclear excited states since this method could naturally guarantee the peripherality of the transfer. Zero-range ADWA calculations are performed with the final nucleus bound under different conditions. It can be observed that there is a clear enhancement of the interaction cross sections when the nucleus is loosely bound within an s orbital.

Direct injection of retinal cells into the eyes of patients is a new and better therapeutic method for cataract, but the challenge is that the survival rate of cells during injection is very low. In order to solve this problem, in this study, the force distribution of retinal cells in the injectors with two needle shapes was analysed using coupled discrete element method with computational fluid dynamics (DEM-CFD), in which an immersed boundary method was implemented. Two injectors were considered: one with a straight needle and the other with a curved needle. It was found that the velocities of retinal cells in the injector with a straight needle were slightly higher than that with a curved needle. In addition, the injection speed greatly affected the force distribution of retinal cells, and the retinal cells near the piston were subjected to the highest forces during injection. It was also found that the forces on retinal cells increased as the concentration of the cells increase, and the forces of retinal cells increased evidently with the increasing of piston displacement.

We reanalyze the experiment of Schmitt et al. on the $^{10}\mathrm{Be}(d,p)^{11}\mathrm{Be}$ transfer reaction [Phys. Rev. Lett. 108, 192701 (2012)] by exploring the beam-energy and angular ranges at which the reaction is strictly peripheral. We consider the adiabatic distorted wave approximation (ADWA) to model the reaction and use a Halo-EFT description of $^{11}\mathrm{Be}$ to systematically explore the sensitivity of our calculations to the short-range physics of the $^{10}\mathrm{Be}\ensuremath{-}n$ wave function. We find that by selecting the data at low beam energy and forward scattering angle the calculated cross sections scale nearly perfectly with the asymptotic normalization coefficient (ANC) of the $^{11}\mathrm{Be}$ bound states. Following these results, a comparison of our calculations with the experimental data gives a value of ${C}_{1s1/2}=0.785\ifmmode\pm\else\textpm\fi{}0.03\phantom{\rule{0.16em}{0ex}}{\mathrm{fm}}^{\ensuremath{-}1/2}$ for the ${\frac{1}{2}}^{+}$ ground-state ANC and ${C}_{0p1/2}=0.135\ifmmode\pm\else\textpm\fi{}0.005\phantom{\rule{0.16em}{0ex}}{\mathrm{fm}}^{\ensuremath{-}1/2}$ for the ${\frac{1}{2}}^{\ensuremath{-}}$ excited state, which are in perfect agreement with the ab initio calculations of Calci et al., who obtain ${C}_{1/{2}^{+}}^{\mathit{ab}\phantom{\rule{0.28em}{0ex}}\mathit{initio}}=0.786\phantom{\rule{0.16em}{0ex}}{\mathrm{fm}}^{\ensuremath{-}1/2}$ and ${C}_{1/{2}^{\ensuremath{-}}}^{\mathit{ab}\phantom{\rule{0.28em}{0ex}}\mathit{initio}}=0.129\phantom{\rule{0.16em}{0ex}}{\mathrm{fm}}^{\ensuremath{-}1/2}$ [Phys. Rev. Lett. 117, 242501 (2016)].

Measurements have been performed with scintillation crystals of LaBr3:Ce coupled to an array of Silicon Photomultipliers (SiPMs) in a 3 T magnetic field. The SiPMs were read out by digital data acquisition systems, including the GET electronics system. Inside of the B-field, energy resolution values of 3.82% FWHM at 661.7 keV are reported for a 1.5′′ cubic LaBr3:Ce crystal coupled to a 6 × 6 array of 6 × 6 mm2 SiPMs. No measurable degradation in energy resolution due to the presence of the strong magnetic field was observed.

The single-shot x-ray Talbot–Lau interferometer-based differential phase contrast (DPC) imaging is able to accelerate time-consuming data acquisition; however, the extracted phase image suffers from severe image artifacts. Here, we propose to estimate the DPC image via a deep convolutional neural network (CNN) incorporated with the physical imaging model. Instead of training the CNN with thousands of labeled data beforehand, both phantom and biological specimen validation experiments show that high-quality DPC images can be automatically generated from only one single-shot projection image with a certain periodic moiré pattern. This work provides a new, to the best of our knowledge, paradigm for single-shot x-ray DPC imaging.

Both inhibitor of growth 4 (ING4) and phosphatase and tensin homolog deleted on chromosome 10 (PTEN) are well known as tumor suppressors that are closely related to tumor occurrence and progression. It was reported that ING4 and PTEN showed synergistic antitumor activities in nasopharyngeal carcinoma cells. The two tumor suppressors demonstrated synergistic effect on growth inhibition and apoptosis activation. In this study, we investigated their therapeutic potential in hepatocellular carcinoma (HCC) cells. Recombinant adenoviruses co-expressing ING4 and PTEN (Ad-ING4-PTEN) were constructed, and the antitumor effect on SMMC-7721 and HepG2 HCC cells was evaluated. Ad-ING4-PTEN cooperatively inhibited cell growth, stimulated apoptosis, and suppressed invasion in both HCC cells, and regulated cell cycle in SMMC-7721. Further studies showed that the combination of ING4 and PTEN by Ad-ING4-PTEN cooperatively enhanced the alteration of the expression of cell cycle-related proteins (p53, p21, and cyclin D1) and apoptotic factors (Bad, Bcl-2, Bcl-XL, and Bax), which are involved in the regulation of cell cycle and the activation of apoptotic pathways, leading to the synergistic antitumor effect. These results indicate that the combination of ING4 and PTEN may provide an effective therapeutic strategy for HCC.

Particle interactions play a significant role in controlling the performance of dry powder inhalers (DPIs), which mainly arise through van der Waals potentials, electrostatic interactions, and capillary forces. Our aim is to investigate the influence of electrostatic charge on the performance of DPIs as a basis for improving the formulation of the particle ingredients. The mixing process of carrier and active pharmaceutical ingredient (API) particles in a vibrating container is investigated using a discrete element method (DEM). The number of API particles attaching to the carrier particle (i.e., contact number) increases with increasing charge and decreases with increasing container size. The contact number decreases with increasing vibrational velocity amplitude and frequency. Moreover, a mechanism governed by the electrostatic force is proposed for the mixing process. This mechanism is different from that previously proposed for the mixing process governed by van der Waals forces, indicating that long-range and short-range adhesive forces can result in different mixing behaviours.

Numerical modelling using computational fluid mechanics (CFD) and discrete element method (DEM) becomes increasingly prevalent for the exploration of agglomeration and deagglomeration in dry powder inhalers (DPIs). These techniques provide detailed information on air flow and particle-particle/wall interaction, respectively. Coupling of CFD and DEM enables an in-depth investigation of the mechanisms at the microscopic level. This paper reviews the applications of CFD and DEM in DPI development and optimisation. The recent progress in modelling of two key processes in DPIs, i.e. agglomeration and deagglomeration, is presented. It has been demonstrated that DEM-CFD is a promising numerical approach to investigate the underlying agglomeration and deagglomeration mechanisms for DPIs. With further advances in computing capacity, it is expected that DEM-CFD will be capable of addressing more realistic and complicated issues in DPI improvement.

The effects of particle shape differences on binary mixture shear flows are investigated using the Discrete Element Method (DEM). The binary mixtures consist of frictionless rods and disks, which have the same volume but significantly different shapes. In the shear flows, stacking structures of rods and disks are formed. The effects of the composition of the mixture on the stacking are examined. It is found that the number fraction of stacking particles is smaller for the mixtures than for the monodisperse rods and disks. For binary mixtures with small particle shape differences, the mixture stresses are bounded by the stresses of the two corresponding monodisperse systems. However, for binary mixtures with large particle shape differences, the stresses of the mixtures can be larger than the stresses of the monodisperse systems at large solid volume fractions because larger differences in particle shape cause geometrical interference in packing, leading to stronger particle–particle interactions in the flow. The stresses in dense binary mixtures are found to be exponential functions of the order parameter, which is a measure of particle alignment. Based on the simulation results, an empirical expression for the bulk friction coefficient (ratio of the shear stress to normal stress) for dense binary flows is proposed by accounting for the effects of particle alignment and solid volume fraction.

Few single nucleotide polymorphisms (SNPs) have been reproducibly associated with hepatocellular carcinoma (HCC). Our aim was to test the association between nine SNPs and HCC occurrence. SNPs in genes linked to HCC (DEPDC5, GRIK1, KIF1B, STAT4, MICA, DLC1, DDX18) or to liver damage (PNPLA3-rs738409, TM6SF2-rs58542926) in GWAS were genotyped in discovery cohorts including 1,020 HCC, 2,021 controls with chronic liver disease and 2,484 healthy individuals and replication was performed in prospective cohorts of cirrhotic patients with alcoholic liver disease (ALD, n=249) and hepatitis C (n=268). In the discovery cohort, PNPLA3 and TM6SF2 SNPs were associated with HCC (OR=1.67 [CI95%:1.16-2.40], p=0.005; OR=1.45 [CI95%:1.08-1.94], p=0.01) after adjustment for fibrosis, age, gender and etiology. In contrast, STAT4-rs7574865 was associated with HCC only in HBV infected patients (p=0.03) and the other tested SNP were not linked with HCC risk. PNPLA3 and TM6SF2 variants were independently associated with HCC in patients with ALD (OR=3.91 [CI95%:2.52-6.06], p=1.14E-09; OR=1.79 [CI95%:1.25-2.56], p=0.001) but not with other etiologies. PNPLA3 SNP was also significantly associated with HCC developed on a non-fibrotic liver (OR=2.19 [CI95%:1.22-3.92], p=0.007). The association of PNPLA3 and TM6SF2 with HCC risk was confirmed in the prospective cohort with ALD. A genetic score including PNPLA3 and TM6SF2 minor alleles showed a progressive significant increased risk of HCC in ALD patients. In conclusion, PNPLA3-rs738409 and TM6SF2-rs58542926 are inherited risk variants of HCC development in patients with ALD in a dose dependent manner. The link between PNPLA3 and HCC on non-fibrotic liver suggests a direct role in liver carcinogenesis. This article is protected by copyright. All rights reserved.

A detector setup for the measurement of angular distribution of heavy-ion elastic scattering at energies around Coulomb barrier on the radioactive ion beam line in Lanzhou at the heavy-ion research facility in Lanzhou is designed. The beam profile and the scattering angles on the target are deduced by two parallel plate avalanche counters, and four sets of detector telescopes (including double-sided silicon strip detectors) are placed systematically with the beam line, incorporating with Monte Carlo simulations. The data of $$^{16}\hbox {O}$$ on $$^{89}\hbox {Y}$$ target were analyzed to compare with the simulation results. It is found that the simulated distribution is agreeable with the experimental data. By assuming the pure Rutherford scattering at small scattering angles, the angular distribution of elastic scattering of $${}^{16}\hbox {O} + {}^{89}\hbox {Y}$$ at low energies can be reasonably obtained. It indicates that this set of detector setup can be used for the measurement of angular distributions of heavy-ion elastic scattering at energies around Coulomb barrier.

Scour under a submarine pipeline can lead to structural failure; hence, a good understanding of the scour mechanism is paramount. Various numerical methods have been proposed to simulate scour, such as potential flow theory and single-phase and two-phase turbulent models. However, these numerical methods have limitations such as their reliance on calibrated empirical parameters and inability to provide detailed information. This paper investigates the use of a coupled computational fluid dynamics-discrete element method (CFD-DEM) model to simulate scour around a pipeline. The novelty of this work is to use CFD-DEM to extract detailed information, leading to new findings that enhance the current understanding of the underlying mechanisms of the scour process. The simulated scour evolution and bed profile are found to be in good agreement with published experimental results. Detailed results include the contours of the fluid velocity and fluid pressure, particle motion and velocity, fluid forces on the particles, and inter-particle forces. The sediment transport rate is calculated using the velocity of each single particle. The quantitative analysis of the bed load layer is also presented. The numerical results reveal three scour stages: onset of scour, tunnel erosion, and lee-wake erosion. Particle velocity and force distributions show that during the tunnel erosion stage, the particle motion and particle–particle interactive forces are particularly intense, suggesting that single-phase models, which are unable to account for inter-particle interactions, may be inadequate. The fluid pressure contours show a distinct pressure gradient. The pressure gradient force is calculated and found to be comparable with the drag force for the onset of scour and the tunnel erosion. However, for the lee-wake erosion, the drag force is shown to be the dominant mechanism for particle movements.

Air flow and particle–particle/wall impacts are considered as two primary dispersion mechanisms for dry powder inhalers (DPIs). Hence, an understanding of these mechanisms is critical for the development of DPIs. In this study, a coupled DEM–CFD (discrete element method–computational fluid dynamics) is employed to investigate the influence of air flow on the dispersion performance of the carrier-based DPI formulations. A carrier-based agglomerate is initially formed and then dispersed in a uniformed air flow. It is found that air flow can drag API particles away from the carrier and those in the downstream air flow regions are prone to be dispersed. Furthermore, the influence of the air velocity and work of adhesion are also examined. It is shown that the dispersion number (i.e., the number of API particles detached from the carrier) increases with increasing air velocity, and decreases with increasing the work of adhesion, indicating that the DPI performance is controlled by the balance of the removal and adhesive forces. It is also shown that the cumulative Weibull distribution function can be used to describe the DPI performance, which is governed by the ratio of the fluid drag force to the pull-off force., Graphical abstract In this study, a coupled DEM–CFD (discrete element method–computational fluid dynamics) is employed to investigate the influence of air flow on the dispersion performance of the carrier-based DPI formulations.

© 2019 Jagellonian University. All Rights Reserved. The breaking of isospin symmetry caused by the Coulomb interaction can be measured by the study of E1 γ decay. The Isovector Giant Dipole Resonance (IVGDR) was measured in 60 Zn and 62 Zn at two different excitation energies E ∗ = 47 MeV and E ∗ = 58 MeV with the goal of deducing the isospin mixing term. A fusion–evaporation reaction, with a beam of 32 S and a target of 28 Si, was used to produce 60 Zn. We also produced the compound nucleus 62 Zn using the reaction 32 S + 30 Si. This last reaction is required because, for the produced nucleus, the statistical model analysis is much less sensitive to the isospin mixing, and this allows to extract the GDR parameters and use them for isospin mixing sensitive reaction populating neighboring nucleus with N = Z. The experimental setup was composed of GALILEO array (germanium detectors) coupled to the large-volume LaBr 3 :Ce detectors for the γ-rays measuring and by two ancillary arrays, EUCLIDES and the Neutron Wall for the detection of particles and neutrons, respectively. An overview on the ongoing analysis and on preliminary results is presented. ispartof: ACTA PHYSICA POLONICA B vol:50 issue:3 pages:481-486 ispartof: location:POLAND, Zakopane status: published

The half-lives of cluster decays are calculated using proximity potential model with a new universal function, and compared to the experimentally measured values and the theoretical ones of liquid drop model. The results of the present calculations show reasonable agreement with the experimental data as well as the half-life calculations of liquid drop model. In the present work, it is certified that proximity potential model with the new universal function can be used successfully to calculate the half-lives of cluster decays for heavy nuclei.