Preparation and Evaluation of a Self-Nanoemulsifying Drug Delivery System Loaded with Heparin Phospholipid Complex

A self-nanoemulsifying drug delivery system (SNEDDS) was developed to enhance the absorption of heparin after oral administration, in which heparin was compounded with phospholipids to achieve better fat solubility in the form of heparin-phospholipid (HEP-Pc) complex. HEP-Pc complex was prepared using the solvent evaporation method, which increased the solubility of heparin in n-octanol. The successful preparation of HEP-Pc complex was confirmed by differential scanning calorimetry (DSC), Fourier-transform infrared (FT-IR) spectroscopy, NMR, and SEM. A heparin lipid microemulsion (HEP-LM) was prepared by high-pressure homogenization and characterized. HEP-LM can enhance the absorption of heparin after oral administration, significantly prolong activated partial thromboplastin time (APTT) and thrombin time (TT) in mice, and reduce fibrinogen (FIB) content. All these outcomes indicate that HEP-LM has great potential as an oral heparin formulation.     

Non-Halogenated-Solvent Processed and Additive-Free Tandem Organic Solar Cell with Efficiency Reaching 16.67%

Organic solar cells (OSCs) have recently reached a remarkably high efficiency and become a promising technology for commercial application. However, OSCs with top efficiency are mostly processed by halogenated solvents and with additives that are not environmentally friendly, which hinders large-scale manufacture. In this study, high-performance tandem OSCs, based on polymer donors and two small-molecule acceptors with different bandgaps, are fabricated by solution processing with non-halogenated solvents without additive. Importantly, the two active layers developed from non-halogenated solvents show better phase segregation and charge transport properties, leading to superior performance than halogenated ones. As a result, a tandem OSC with high efficiency of up to 16.67% is obtained, showing unique advantages in future massive production.     

Effect of nitriding atmosphere on the morphology of AlN nanofibers from solution blow spinning

High purity AlN fiber is a promising thermal conductive material. In this work, AlN fibers were prepared using solution blow spinning followed by nitridation under N₂ or NH₃ atmosphere. Soluble polymer, such as polyaluminoxane, and allyl-functional novolac resin were adopted as raw materials to form homogeneous distribution of Al₂O₃ and C nanoparticles within the fibers, which could inhibit the growth of alumina crystal and promote their nitridation process. The effect of nitriding atmosphere on the fiber morphology was investigated. XRD results showed that complete nitridation was achieved at 1300 °C in the NH₃ or at 1500 °C in the N₂ atmosphere. Hollowed fiber structure was observed when fiber was nitrided in N₂ at high temperature, which was caused by gaseous Al gas diffusion, and this phenomenon was eliminated in NH₃ atmosphere. The nitridation mechanisms in different atmosphere were analyzed in detail. It was demonstrated that the nitridation of Al₂O₃ fibers in the NH₃ atmosphere offered the favored AlN morphology and chemical quality. Flexible AlN fiber with O content of 0.7 wt% was achieved after nitriding in NH₃ at 1400 °C. The high quality AlN can be used in thermal conductive composite materials.     

Embedding carbon dots in Eu3+-doped metal-organic framework for label-free ratiometric fluorescence detection of Fe3+ ions

Fluorescent detection is a new spectroscopic measurement for ions sensing due to the advantages of real-time determination with high selectivity, accuracy, and low cost. However, chemosensors based on fluorescent detection are usually determined by absolute intensity from a monochromatic emission signal, which is easy to be fluctuated by the external environment, especially for Fe³⁺ detection in complex fluids. Herein, we rationally design a dual-emission Eu³⁺: CDs@ZIF-8 to construct a ratiometric fluorescent sensor with self-calibrating ability for Fe³⁺ determination. High efficient carbon dots (CDs) are embedded in europium ions (Eu³⁺)-doped MOF by simple stirring preparation at room temperature. The label-free ratiometric fluorescent probe (I_CDs@ZIF-8/I_Eu) exhibits simultaneous blue and red emission under the same excitation at 365 nm. Remarkably, Eu³⁺: CDs@ZIF-8 displays the superiority of high selectivity to Fe³⁺, which shows ratiometric fluorescence characteristics (I₀/I) in a range of 0-6 μmol\L with a low limit of detection (LOD) of 0.897 μmol\L. Besides, the CDs-MOF nanocomposite holds good aqueous dispersibility and low cytotoxicity, which shows great potential applications in medical aid including biological detection and clinical diagnosis.     

Waveguide external cavity narrow linewidth semiconductor lasers

Narrow linewidth light source is a prerequisite for high-performance coherent optical communication and sensing.Waveguide-based external cavity narrow linewidth semiconductor lasers(WEC-NLSLs)have become a competitive and attractive candidate for many coherent applications due to their small size,volume,low energy consumption,low cost and the ability to integrate with other optical components.In this paper,we present an overview of WEC-NLSLs from their required technologies to the state-of-the-art progress.Moreover,we highlight the common problems occurring to current WEC-NLSLs and show the possible approaches to resolving the issues.Finally,we present the possible development directions for the next phase and hope this review will be beneficial to the advancements of WEC-NLSLs.     

Er3+-Yb3+ ions doped fluoro-aluminosilicate glass-ceramics as a temperature-sensing material

The transparent Er³⁺-Yb³⁺-doped fluoro-aluminosilicate glass-ceramic (GC) was prepared by melt-quenching. The crystal phase, morphology, and up-conversion (UC) luminescence of as-produced GC were characterized by X-ray diffraction, scanning electron microscopy, and fluorescence spectrophotometry, respectively. The results show that BaYF₅ nanocrystals were uniformly distributed in the glass matrix of the as-produced GC. When the as-produced GC was subjected to heat treatment, the crystallinity was increased, but the crystal identity remains unchanged. Such heat-treatment doubled the intensity of the UC luminescence, and this enhancement was ascribed to the increased incorporation of both Er³⁺ and Yb³⁺ ions into the lower phonon energy environment of BaYF₅ nanocrystals. Furthermore, the heat-treated GC was stable against further crystallization, and consequently its UC luminescence was stable at the application temperature. The heat-treated GC was found to possess an outstanding temperature-sensing capability.     

A two-step shapelets based framework for interactional activities recognition

Multimedia Tools and Applications - Human-human interactions recognition has high potential to have a big impact on enabling robots being able to interact with people. Recently, body sensor...     

Optimized decomposition and two-step nonlinear integration model with error correction strategy coupled interval prediction for digital currency price forecast

Digital currency price prediction is vital to both sellers and purchasers. Over these years, decomposition and integration models have been applied more and more to realize the goal of precise prediction, however, many of them tend to neglect the reconstruction of features or the residual series. Altogether, one of the biggest drawbacks of the decomposition and integration framework is the method applied requires manual parameter setting whether it is for decomposition or integration. Still, for the results, they are merely satisfied with the point prediction which brings high uncertainty. In this paper, an optimized feature reconstruction decomposition and two-step nonlinear integration method is proposed which gives consideration to feature reconstruction, nonlinear integration, optimization and interval prediction. The original data series is decomposed through improved variational mode decomposition based approximate entropy feature reconstruction system. Then, improved particle swarm optimization-gated recurrent unit (iPSO-GRU) is utilized in the first and second nonlinear integration part separately. Meanwhile, the residual series is given attention, if it is not a white noise series, the residual will be the input of iPSO-GRU whose result will be added back to the second integration result to form the point prediction result. Based on the point prediction result, interval prediction estimate will be generated as well via maximum likelihood function. This study chooses three kinds of digital currency as cases and the results show that the MAPE values of point prediction are all below 3.5%, and CP values of interval prediction are all 1 with suitable MWP. In addition, compared with other benchmark models, the proposed model shows better performance.