Evaluation of the levofloxacin release characters from a rabbit foldable capsular vitreous body

The authors have manufactured a novel rabbit foldable capsular vitreous body (FCVB). The aim of this study was to determine whether this rabbit FCVB can release levofloxacin in vitro and in vivo, and to evaluate the release characteristics. In vitro, the rabbit FCVB with levofloxacin 500 μg/mL was immersed in cups of modified Franz diffusion cells. Following this, 200 μL of liquid was aspirated at intervals from 10 minutes to 24 hours. In vivo, the FCVB with levofloxacin was implanted into the right eyes of five rabbits. After implantation, the aqueous humor was aspirated on days 1, 7, 14, 28, and 56. The levofloxacin concentrations in the cups and aqueous humor samples were detected by high-performance liquid chromatography–tandem mass spectrometry. The FCVB was observed under a scanning electron microscope. The results showed that the released levofloxacin was stabilized at 20 ng/mL at time points from 10 minutes to 24 hours in vitro. In vivo, levofloxacin concentrations in the aqueous humor were 132, 50, 39, 11, and 15 ng/mL on days 1, 7, 14, 28, and 56, respectively. In the FCVB capsules, 300 nm apertures were observed. These results suggest the rabbit FCVB released levofloxacin stably in vitro and sustainably in vivo. This study provides a novel combined approach, with the FCVB as a vitreous substitute and drug delivery system for the treatment of bacterial endophthalmitis

Tunable plasmonic reflection by bound 1D electron states in a 2D Dirac metal

We show that surface plasmons of a two-dimensional Dirac metal such as graphene can be reflected by line-like perturbations hosting one-dimensional electron states. The reflection originates from a strong enhancement of the local optical conductivity caused by optical transitions involving these bound states. We propose that the bound states can be systematically created, controlled, and liquidated by an ultranarrow electrostatic gate. Using infrared nanoimaging, we obtain experimental evidence for the locally enhanced conductivity of graphene induced by a carbon nanotube gate, which supports this theoretical concept.Comment: 14 pages, 12 figures, submitted to PR

Study of double-potential-well leaf spring system’s chaotic vibration

Chaotic vibration has become increasingly popular in the study of acoustic and vibration engineering. Many engineering designs have taken advantage of the special characteristics of chaos, and deliberately introduced it into the system to improve efficiency. As an important component, leaf springs have long been used in the suspension system of wheeled vehicles. Recent development is considering chaotic vibration in the design of leaf springs to improve the system’s reliability. However, little experimental research has been carried out to investigate the chaos characteristics of leaf springs. Meanwhile, a preliminary study showed that some of the conventional signal processing methods may not be able to successfully identify the chaos features from a leaf spring test rig due to the complexity of the practical signal. Therefore, in this paper, a leaf spring system’s chaotic vibration and relevant signal processing strategy were investigated in theory and experiment. Firstly, the relationship between the amplitude and frequency of the double potential well system is derived with averaging method. The stability is analyzed on the Vander pol plane and the global bifurcation diagram and Lyapunov exponent spectrum are applied to determine the chaotic regime accurately. Numerical simulation was conducted using a finite element method to give an idea of the leaf spring’s natural frequencies where chaotic vibration can be potentially generated. The experimental rig was then designed based on double potential well theory to generate stable and repeatable chaotic vibration, and an experimental study was carried out to investigate the system’s response characteristics under different excitation strengths and frequencies. An improved signal processing method, Wavelet-SG-EEMD (Wavelet, Savitzky-Golay (SG) and Ensemble Empirical Mode Decomposition (EEMD)), was used to reduce noise and beneficial to identify chaotic features of the vibration signal generated by the system. The nonlinear vibration response features of the system were carefully analyzed. Sub-harmonic phenomena, periodic modes and chaotic behavior were discovered during the experiment

Determinant Role of Aerosols From Industrial Sources in Hurricane Harvey's Catastrophe

The destructive power of tropical cyclones is driven by latent heat released from water condensation and is inevitably linked to the abundance of aerosols as cloud condensation nuclei. However, the aerosol effects are unaccounted for in most operational hurricane forecast models. We combined multisource measurements and cloud‐resolving model simulations to show fundamentally altered cloud microphysical and thermodynamic processes by anthropogenic aerosols during Hurricane Harvey. Our observational analyses reveal intense lightning and precipitation in the proximity of Houston industrial areas, and these hot spots exhibit a striking geographic similarity to a climatological maximum of lightning flash density in the south‐central United States. Our ensemble cloud‐resolving simulations of Hurricane Harvey indicate that aerosols increase precipitation and lightning by a factor of 2 in the Houston urban area, unraveling the key anthropogenic factor in regulating flooding during this weather extreme

LC/MS Guided Isolation of Alkaloids from Lotus Leaves by pH-Zone-Refining Counter-Current Chromatography

The traditional methods used in natural product separation primarily target the major components and the minor components may thus be lost during the separation procedure. Consequently, it’s necessary to develop efficient methods for the preparative separation and purification of relatively minor bioactive components. In this paper, a LC/MS method was applied to guide the separation of crude extract of lotus (Nelumbo nucifera Gaertn.) leaves whereby a minor component was identified in the LC/MS analysis. Afterwards, an optimized pH-zone-refining CCC method was performed to isolate this product, identified as N-demethylarmepavine. The separation procedure was carried out with a biphasic solvent system composed of hexane-ethyl acetate-methyl alcohol-water (1:6:1:6, v/v) with triethylamine (10 mM) added to the upper organic phase as a retainer and hydrochloric acid (5 mM) to the aqueous mobile phase eluent. Two structurally similar compounds – nuciferine and roemerine – were also obtained from the crude lotus leaves extract. In total 500 mg of crude extract furnished 7.4 mg of N-demethylarmepavine, 45.3 mg of nuciferine and 26.6 mg of roemerine with purities of 90%, 92% and 96%, respectively. Their structures were further identified by HPLC/ESI-MSn, FTICR/MS and the comparison with reference compounds

Quantum interface between frequency-uncorrelated down-converted entanglement and atomic-ensemble quantum memory

Photonic entanglement source and quantum memory are two basic building blocks of linear-optical quantum computation and long-distance quantum communication. In the past decades, intensive researches have been carried out, and remarkable progress, particularly based on the spontaneous parametric down-converted (SPDC) entanglement source and atomic ensembles, has been achieved. Currently, an important task towards scalable quantum information processing (QIP) is to efficiently write and read entanglement generated from a SPDC source into and out of an atomic quantum memory. Here we report the first experimental realization of a quantum interface by building a 5 MHz frequency-uncorrelated SPDC source and reversibly mapping the generated entangled photons into and out of a remote optically thick cold atomic memory using electromagnetically induced transparency. The frequency correlation between the entangled photons is almost fully eliminated with a suitable pump pulse. The storage of a triggered single photon with arbitrary polarization is shown to reach an average fidelity of 92% for 200 ns storage time. Moreover, polarization-entangled photon pairs are prepared, and one of photons is stored in the atomic memory while the other keeps flying. The CHSH Bell's inequality is measured and violation is clearly observed for storage time up to 1 microsecond. This demonstrates the entanglement is stored and survives during the storage. Our work establishes a crucial element to implement scalable all-optical QIP, and thus presents a substantial progress in quantum information science.Comment: 28 pages, 4 figures, 1 tabl

RLIPv2: Fast Scaling of Relational Language-Image Pre-training

Relational Language-Image Pre-training (RLIP) aims to align vision representations with relational texts, thereby advancing the capability of relational reasoning in computer vision tasks. However, hindered by the slow convergence of RLIPv1 architecture and the limited availability of existing scene graph data, scaling RLIPv1 is challenging. In this paper, we propose RLIPv2, a fast converging model that enables the scaling of relational pre-training to large-scale pseudo-labelled scene graph data. To enable fast scaling, RLIPv2 introduces Asymmetric Language-Image Fusion (ALIF), a mechanism that facilitates earlier and deeper gated cross-modal fusion with sparsified language encoding layers. ALIF leads to comparable or better performance than RLIPv1 in a fraction of the time for pre-training and fine-tuning. To obtain scene graph data at scale, we extend object detection datasets with free-form relation labels by introducing a captioner (e.g., BLIP) and a designed Relation Tagger. The Relation Tagger assigns BLIP-generated relation texts to region pairs, thus enabling larger-scale relational pre-training. Through extensive experiments conducted on Human-Object Interaction Detection and Scene Graph Generation, RLIPv2 shows state-of-the-art performance on three benchmarks under fully-finetuning, few-shot and zero-shot settings. Notably, the largest RLIPv2 achieves 23.29mAP on HICO-DET without any fine-tuning, yields 32.22mAP with just 1% data and yields 45.09mAP with 100% data. Code and models are publicly available at https://github.com/JacobYuan7/RLIPv2.Comment: Accepted to ICCV 2023. Code and models: https://github.com/JacobYuan7/RLIPv