1D Experiments Research Articles

Visual Comparison of Networks in VR.

Networks are an important means for the representation and analysis of data in a variety of research and application areas. While there are many efficient methods to create layouts for networks to support their visual analysis, approaches for the comparison of networks are still underexplored. Especially when it comes to the comparison of weighted networks, which is an important task in several areas, such as biology and biomedicine, there is a lack of efficient visualization approaches. With the availability of affordable high-quality virtual reality (VR) devices, such as head-mounted displays (HMDs), the research field of immersive analytics emerged and showed great potential for using the new technology for visual data exploration. However, the use of immersive technology for the comparison of networks is still underexplored. With this work, we explore how weighted networks can be visually compared in an immersive VR environment and investigate how visual representations can benefit from the extended 3D design space. For this purpose, we develop different encodings for 3D node-link diagrams supporting the visualization of two networks within a single representation and evaluate them in a pilot user study. We incorporate the results into a more extensive user study comparing node-link representations with matrix representations encoding two networks simultaneously. The data and tasks designed for our experiments are similar to those occurring in real-world scenarios. Our evaluation shows significantly better results for the node-link representations, which is contrary to comparable 2D experiments and indicates a high potential for using VR for the visual comparison of networks.

A Second-Order Crank-Nicolson Leap-Frog Scheme for the Modified Phase Field Crystal Model with Long-Range Interaction.

In this paper, we construct a fully discrete and decoupled Crank-Nicolson Leap-Frog (CNLF) scheme for solving the modified phase field crystal model (MPFC) with long-range interaction. The idea of CNLF is to treat stiff terms implicity with Crank-Nicolson and to treat non-stiff terms explicitly with Leap-Frog. In addition, the scalar auxiliary variable (SAV) method is used to allow explicit treatment of the nonlinear potential, then, these technique combines with CNLF can lead to the highly efficient, fully decoupled and linear numerical scheme with constant coefficients at each time step. Furthermore, the Fourier spectral method is used for the spatial discretization. Finally, we show that the CNLF scheme is fully discrete, second-order decoupled and unconditionally stable. Ample numerical experiments in 2D and 3D are provided to demonstrate the accuracy, efficiency, and stability of the proposed method.

An unconditionally energy stable algorithm for copolymer–homopolymer mixtures

The homopolymer and copolymer mixtures have attracted extensive research in various scientific and engineering fields. A highly efficient, temporally second-order accurate, and unconditionally energy stable scheme for the coupled Cahn–Hilliard system simulating the phase separation in the homopolymer and copolymer mixtures is proposed. To appropriately treat the nonlinear and coupling terms in the coupled Cahn–Hilliard system, an efficient variant of the scalar auxiliary variable (SAV) approach is considered. However, the time-discretized modified energy resulting from the SAV method is usually no longer consistent with the original continuous energy because of the truncation errors during numerical implementations. Therefore, a simple and practical energy relaxation technique is adopted to overcome this shortcoming, and then the time-discretized corrected energy is obtained. The present method has the following merits: (i) In each iteration, all variables are decoupled, and we can solve them step-by-step. Thus, the numerical implementation is efficient; (ii) The time-discretized corrected energy and the original energy are highly consistent; (iii) The unique solvability and energy stability are strictly proved; (iv) Various morphologies of pattern formations of the copolymer–homopolymer mixtures can be well simulated. The accuracy, stability, and consistency of developed scheme are demonstrated by various 2D and 3D numerical experiments.

Chemical constituents from Melodinus axillaris W. T. Wang and their chemotaxonomic significance

A phytochemical investigation on the aerial parts of Melodinus axillaris resulted in the isolation and identification of 14 indole alkaloids and 2 other compounds. The 14 alkaloids were readily classified as an unusual aspidosperma (1), aspidosperma (2–9), quinolone (10 and 11), eburnamine (12 and 13) and condylocarpan (14) types. Melaxillarine (1) was an unusual aspidosperma-type alkaloid with a contracted E ring, and was identified by means of spectroscopic analysis, including HRESIMS, and 1D and 2D NMR experiments. Compounds 1, 4, 7–9, 11 and 15–16 were isolated from this plant for the first time, while the 1, 9 and 15–16 were reported from Melodinus species for the first time. Compounds 1 and 9 could be considered as chemotaxonomic markers for M. axillaris. The chemotaxonomic significance and distribution of these compounds in Melodinus genus were discussed.

A stress-based criterion to identify and control intersections in 2D compliance minimization topology optimization

Topology optimization typically generates designs that exhibit significant geometrical complexity, which can pose difficulties for manufacturing and assembly. The number of occurrences of an important design feature, in particular intersections, increases with geometrical complexity. Intersections are essential for load transfer in many engineering structures. For certain upcoming manufacturing processes, such as direct metal deposition, the size of an intersection plays a role. During metal deposition, slim intersections are more prone to manufacturing defects than bulkier ones. In this study, a computationally tractable methodology is proposed to both control occurrence and size of intersections in topology optimization. To identify intersections, a stress-based quantity is proposed, denoted as Intersection Indicator. This quantity is based on the local degree of multi-axiality of the stress state, and identifies material points at intersections. The proposed intersection indicator can identify intersections in both single as well as multi-load case problems. To detect the relative size of intersections, the average density in the vicinity of an intersection is used to penalize or promote intersection sizes of interest. The corresponding sensitivity analysis involves solving a set of adjoint equations for each load case. Numerical 2D experiments demonstrate a controllable reduction of penalized slim intersections compared to the designs obtained from conventional compliance minimization. The overall geometrical complexity of the design is reduced due to the promotion of bulkier intersections which leads to an increase in compliance. The designs obtained are more suitable for manufacturing processes such as direct metal deposition.

Aquila: a spatial omics database and analysis platform.

Spatial omics is a rapidly evolving approach for exploring tissue microenvironment and cellular networks by integrating spatial knowledge with transcript or protein expression information. However, there is a lack of databases for users to access and analyze spatial omics data. To address this limitation, we developed Aquila, a comprehensive platform for managing and analyzing spatial omics data. Aquila contains 107 datasets from 30 diseases, including 6500+regions of interest, and 15.7 million cells. The database covers studies from spatial transcriptome and proteome analyses, 2D and 3D experiments, and different technologies. Aquila provides visualization of spatial omics data in multiple formats such as spatial cell distribution, spatial expression and co-localization of markers. Aquila also lets users perform many basic and advanced spatial analyses on any dataset. In addition, users can submit their own spatial omics data for visualization and analysis in a safe and secure environment. Finally, Aquila can be installed as an individual app on a desktop and offers the RESTful API service for power users to access the database. Overall, Aquila provides a detailed insight into transcript and protein expression in tissues from a spatial perspective. Aquila is available at https://aquila.cheunglab.org.

Microstructural Analysis of Poly(ethylene-co-propylene-co-1-butene) terpolymers by Multidimensional NMR Spectroscopy

Physical, rheological and optical properties of polymer depend on its molecular microstructure. Specifically, the monomer content and sequence distribution of polymer significantly affect the mechanical performance of the final product. To this base, Nuclear Magnetic Resonance Spectroscopy (NMR) has been introduced as a very powerful technique to study the microstructure of polymer. The purpose of this study was to develop a methodology to investigate the microstructure of poly(ethylene-co-propylene-co-butene) terpolymer by using multidimensional NMR spectroscopy, including pulsed-field-gradient (PFG) 1H-13C heteronuclear single quantum coherence (GHSQC), heteronuclear multiple bond coherence (gHMBC), and heteronuclear single quantum coherence-total correlation spectroscopy (GHSQC-TOCSY). The combination of 1D and 2D NMR experiments, permit the characterization of the complex structure of poly(ethylene-co-propylene-co-butene) terpolymer. The completed 13C NMR assignments provided in this work allow more accurate quantitative determination of the microstructure in these polymers.

Fast meshfree methods for nonlinear radiation diffusion equation

Radiation diffusion is a phenomenon of interest in the field of astrophysics, inertial confinement fusion and so on. Since it is modeled by nonlinear equations that are usually solved in complex domains, it is difficult to solve by means of finite element method and finite difference method and so on. In the paper, we will provide a kind of new fast meshfree methods based on radial basis functions. At first, the part of diffusion terms for 1D and 2D radiation diffusion equations are linearized directly on time to form the new implicit schemes, and Kansa’s non-symmetric collocation method with the compactly supported radial basis function is used to solve the radiation diffusion problem. Second, the successive permutation iterative algorithms for full-implicit discretization on time are constructed furtherly, which are more efficient than the former algorithm. In the end, the accuracy and efficiency of the presented algorithms are verified by 1D and 2D numerical experiments. The new meshfree methods not only avoid the complexity of mesh generation, but also solve the radiation diffusion problem with high accuracy.

19F fast MAS (60–111 kHz) dipolar and scalar based correlation spectroscopy of organic molecules and pharmaceutical formulations

19F magic angle spinning (MAS) NMR spectroscopy is a powerful tool for characterization of fluorinated solids. The recent development of 19F MAS NMR probes, operating at spinning frequencies of 60–111 kHz, enabled analysis of systems spanning from organic molecules to pharmaceutical formulations to biological assemblies, with unprecedented resolution. Herein, we systematically evaluate the benefits of high MAS frequencies (60–111 kHz) for 1D and 2D 19F-detected experiments in two pharmaceuticals, the antimalarial drug mefloquine and a formulation of the cholesterol-lowering drug atorvastatin calcium. We demonstrate that 1H decoupling is essential and that scalar-based, heteronuclear single quantum coherence (HSQC) and heteronuclear multiple quantum coherence (HMQC) correlation experiments become feasible and efficient at the MAS frequency of 100 kHz. This study opens doors for the applications of high frequency 19F MAS NMR to a wide range of problems in chemistry and biology.

An error bound for the time-sliced thawed Gaussian propagation method

We study the time-sliced thawed Gaussian propagation method, which was recently proposed for solving the time-dependent Schrödinger equation. We introduce a triplet of quadrature-based analysis, synthesis and re-initialization operators to give a rigorous mathematical formulation of the method. Further, we derive combined error bounds for the discretization of the wave packet transform and the time-propagation of the thawed Gaussian basis functions. Numerical experiments in 1D illustrate the theoretical results.

Fate of Sulfonamides and Tetracyclines in Meat during Pan Cooking: Focus on the Thermodegradation of Sulfamethoxazole.

Although antimicrobials are generally found in trace amounts in meat, the human health risk they bear cannot be ignored. With the ultimate aim of making a better assessment of consumer exposure, this study explored the effects of pan cooking on sulfonamides and tetracyclines in meat. Screening of these antimicrobials in cooked meat was first performed by the European Union Reference Laboratory on the basis of HPLC-MS/MS analyses. A proof of concept approach using radiolabeling was then carried out on the most cooking-sensitive antimicrobial—sulfamethoxazole—to assess if a thermal degradation could explain the observed cooking losses. Degradation products were detected thanks to separation by HPLC and monitoring by online radioactivity detection. HPLC-Orbitrap HRMS analyses completed by 1D and 2D NMR experiments allowed the structural characterization of these degradation compounds. This study revealed that cooking could induce significant antimicrobial losses of up to 45% for sulfamethoxazole. Six potential degradation products of 14C-sulfamethoxazole were detected in cooked meat, and a thermal degradation pattern was proposed. This study highlights the importance of considering the cooking step in chemical risk assessment procedures and its impact on the level of chemical contaminants in meat and on the formation of potentially toxic breakdown compounds.

New Development in Understanding Drug-Polymer Interactions in Pharmaceutical Amorphous Solid Dispersions from Solid-State Nuclear Magnetic Resonance.

Pharmaceutical amorphous solid dispersions (ASDs) represent a widely used technology to increase the bioavailability of active pharmaceutical ingredients (APIs). ASDs are based on an amorphous API dispersed in a polymer, and their stability is driven by the presence of strong intermolecular interactions between these two species (e.g., hydrogen bond, electrostatic interactions, etc.). The understanding of these interactions at the atomic level is therefore crucial, and solid-state nuclear magnetic resonance (NMR) has demonstrated itself as a very powerful technique for probing API-polymer interactions. Other reviews have also reported exciting approaches to study the structures and dynamic properties of ASDs and largely focused on the study of API-polymer miscibility and on the identification of API-polymer interactions. Considering the increased use of NMR in the field, the aim of this Review is to specifically highlight recent experimental strategies used to identify API-polymer interactions and report promising recent examples using one-dimensional (1D) and two-dimensional (2D) experiments by exploiting the following emerging approaches of very-high magnetic field and ultrafast magic angle spinning (MAS). A range of different ASDs spanning APIs and polymers with varied structural motifs is targeted to illustrate new ways to understand the mechanism of stability of ASDs to enable the design of new dispersions.

Ingol, ent-atisane, and stachane-type diterpenoids from Euphorbia deightonii with multidrug resistance reversing activity

Nine previously undescribed ingol-type diterpenoid polyesters with eighteen known ingol esters, two ent-atisane, and one stachane diterpenoid were isolated from the methanol extract of Euphorbia deightonii Croizat. The structures were established by extensive spectroscopic analysis involving 1D (1H, 13C J-modulation) and 2D NMR experiments, HRESIMS measurements, and the comparison of the spectroscopic data with reported literature values. The cytotoxic concentrations of 13 isolated compounds were determined, and the compounds were investigated for multidrug resistance modulating activity on an L5178 mouse lymphoma cell line using a rhodamin 123 accumulation assay. Six ingol esters demonstrated the significant inhibition of P-glycoprotein, while the two ent-atisane diterpenoids were found to be inactive. The measured activities allowed to establish some structure–activity relationships. Notably, lower and higher-type diterpenoids simultaneously occurred in E. deightonii.

Triterpenes from Momordica balsamina (African pumpkin): ABCB1 inhibition and synergistic interaction with doxorubicin in resistant cancer cells

Aiming at overcoming multidrug resistance (MDR) in cancer, we have been studying Momordica balsamina, a vegetable known as African pumpkin. Five undescribed cucurbitane-type triterpenoids (balsaminaepoxide, balsaminatriol, balsaminoic acid, balsaminal, and balsaminol G) along with five known cucurbitacins were isolated from the methanol extract of Momordica balsamina aerial parts, whose structures were elucidated by spectroscopic data, mainly 1D and 2D NMR experiments. Compounds were evaluated for their ability as P-glycoprotein (P-gp/ABCB1) inhibitors in multidrug resistant human ABCB1-transfected mouse lymphoma cells (L5178Y, MDR) and resistant human colon adenocarcinoma cells (COLO 320), using the rhodamine-123 exclusion test, by flow cytometry. Several compounds, which were found to be non-cytotoxic, strongly inhibited P-gp efflux activity in a dose-dependent manner in both cell models. In MRD mouse lymphoma cells, balsaminol G and karavilagenin B were the most active, while in resistant colon adenocarcinoma cells, the strongest inhibitory activity was found for balsaminaepoxide, balsaminatriol and karavilagenin C, being several-fold more active than the positive control verapamil. In chemosensitivity assays, in a model of combination chemotherapy, selected compounds showed to interact synergistically with doxorubicin, thus substantiating their potential as MDR reversers. The strongest synergistic interaction was found for balsaminal and balsaminol G.

Oleanane-type glycosides from Weigela x Styriaca and two cultivars of W. florida: “Minor black” and “Brigela”

Sixteen oleanane-type glycosides were extracted from three Weigela hybrids and cultivars: W. x Styriaca, W. florida “Minor black” and W. florida “Brigela”, and four of them were previously undescribed ones: 3- O -β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→3)-α- L -rhamnopyranosyl-(1→2)-β- D -xylopyranosyloleanolic acid, 3- O -β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→3)-α- L -rhamnopyranosyl-(1→2)-α- L -arabinopyranosyloleanolic acid, 3- O -β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→3)-α- L -rhamnopyranosyl-(1→2)-α- L -arabinopyranosyloleanolic acid, and 3- O -β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→4)-β- D -xylopyranosyl-(1→3)-α- L -rhamnopyranosyl-(1→2)-α- L -arabinopyranosyloleanolic acid. Their full structural elucidation required extensive 1D and 2D NMR experiments, as well as mass spectrometry analysis. Six compounds among the known ones were in sufficient amount to be tested for their antifungal activity against Candida albicans, and their antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa . • Sixteen saponins were isolated, among which four new. • Their structures were elucidated by extensive spectroscopic analyses. • The chemotaxonomy of the Weigela genus was discussed, based on the structure of the isolated glycosides. • Five of the isolated compounds were tested against Candida albicans , Staphylococcus aureus and Pseudomonas aeruginosa .

Laboratory Evaluation of the Plugging Performance of an Inorganic Profile Control Agent for Thermal Oil Recovery

During the process of steam thermal recovery of heavy oil, steam channeling seriously affects the production and ultimate recovery. In this study, fly ash was used as the plugging agent, and then a series of plugging experiments based on the results of two-dimensional (2D) experiments were conducted to study the effect of plugging the steam breakthrough channels. The experimental results show that the inorganic particle plugging agent made from the fly ash had a good suspension stability, consolidation strength, and injection performance. Because of these characteristics, it was migrated farther in the formation with a high permeability than in the formation with a low permeability, and the plugging rate was greater than 99%. After steam injection, it had a good anti-flush ability and stable plugging performance in the formation. In terms of the oil displacement effect, oil recovery in the formation with a low permeability was effectively improved because of plugging. The results show that the inorganic particle plugging agent could effectively control the steam channeling and it improved the development effect of the heavy oil reservoir.

Numerical approximations of flow coupled binary phase field crystal system: Fully discrete finite element scheme with second-order temporal accuracy and decoupling structure

In this article, we first establish a new flow-coupled binary phase-field crystal model and prove its energy law. Then by using some newly introduced variables, we reformulate this three-phase model into an equivalent form, which makes it possible to construct a fully discrete linearized decoupling scheme with unconditional energy stability and second-order time accuracy to solve this model for the first time. The energy law of the reformulated model is also proved. Then we incorporate the explicit-IEQ (invariant energy quadratization) method for the nonlinear potentials, the projection method for the Navier-Stokes equations, the Crank-Nicolson method for time marching, and the finite element method for spatial discretization together to develop the fully discrete scheme for the reformulated and equivalent system. By using the nonlocal splitting technique, at each time step, only a few decoupled constant-coefficient elliptic equations are required to be solved, even though the original and reformulated models are much more complicated in the form. The developed algorithm is further proved to be unconditionally energy stable, and a detailed implementation process is also provided. Various numerical experiments in 2D and 3D are carried out to verify the effectiveness of the developed scheme, including the binary crystal growth under the action of shear flow and the sedimentation process of many binary particles.

Finding the Right Place: Sensor Placement for UWB Time Difference of Arrival Localization in Cluttered Indoor Environments

Ultra-wideband (UWB) time difference of arrival (TDOA)-based localization has recently emerged as a promising indoor positioning solution. However, in cluttered environments, both the UWB radio positions and the obstacle-induced non-line-of-sight (NLOS) measurement biases significantly impact the quality of the position estimate. Consequently, the placement of the UWB radios must be carefully designed to provide satisfactory localization accuracy for a region of interest. In this work, we propose a novel algorithm that optimizes the UWB radio positions for a pre-defined region of interest in the presence of obstacles. The mean-squared error (MSE) metric is used to formulate an optimization problem that balances the influence of the geometry of the radio positions and the NLOS effects. We further apply the proposed algorithm to compute a minimal number of UWB radios required for a desired localization accuracy and their corresponding positions. In a real-world cluttered environment, we show that the designed UWB radio placements provide 47% and 76% localization root-mean-squared error (RMSE) reduction in 2D and 3D experiments, respectively, when compared against trivial placements.

Cascade transformation of 4-hydroxymethyl-2-carene into novel cage methanopyrano[4,3-b]thieno[3,2-g]benzofuran derivative

Reaction of trans-4-hydroxymethyl-2-carene with thiophene- 2-carbaldehyde under heterogeneous catalysis by K10 clay affordsubstitutedmethanopyrano[4,3-b]thieno[3,2-g]- benzofuran, a complex 5-membered chiral cage heterocyclic compound containing two thiophene moieties. Its structure was determined by 1D and 2D NMR experiments (HSQC, HMBC, COSY, NOESY) and HRMS.

Stable Numerical Implementation of a Turbulence Scheme with Two Prognostic Turbulence Energies

Abstract In this paper, we present a new and more stable numerical implementation of the two-energy configuration of the Third Order Moments Unified Condensation and N-dependent Solver (TOUCANS) turbulence scheme. The original time-stepping scheme in TOUCANS tends to suffer from spurious oscillations in stably stratified turbulent flows. Because of their high frequency, the oscillations resemble the so-called fibrillations that are caused by the coupling between turbulent exchange coefficients and the stability parameter. However, our analysis and simulations show that the oscillations in the two-energy scheme are caused by the usage of a specific implicit–explicit temporal discretization for the relaxation terms. In TOUCANS, the relaxation technique is used on source and dissipation terms in prognostic turbulence energy equations to ensure numerical stability for relatively long time steps. We present both a detailed linear stability analysis and a bifurcation analysis, which indicate that the temporal discretization is oscillatory for time steps exceeding a critical time-step length. Based on these findings, we propose a new affordable time discretization of the involved terms that makes the scheme more implicit. This ensures stable solutions with enough accuracy for a wider range of time-step lengths. We confirm the analytical outcomes in both idealized 1D and full 3D model experiments. Significance Statement The vertical turbulent transport of momentum, heat, and moisture has to be parameterized in numerical weather prediction models. The parameterization typically employs nonlinear damping equations, whose numerical integration can lead to unphysical, time-oscillating solutions. In general, a presence of such numerical noise negatively affects the model performance. In our work, we address numerical issues of the recently developed scheme with two prognostic turbulence energies that have more realism and physical complexity. Specifically, we detect, explain, and design a numerical treatment for a new type of spurious oscillations that is connected to the temporal discretization. The treatment suppresses the oscillations and allows us to increase the model time step more than 4 times while keeping an essentially non-oscillatory solution.