A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network

In this paper, we employ Probabilistic Neural Network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition algorithm. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.Comment: 6 pages, 3 figures, 2 table

Fast Generation of High-Fidelity Mechanical Non-Gaussian States via Additional Amplifier and Photon Subtraction

Non-Gaussian states (NGSs) with higher-order correlation properties have wide-range applications in quantum information processing. However, the preparation of such states with high quality still faces practical challenges. Here, we propose a protocol to rapidly generate two types of mechanical NGSs, Schr\"{o}dinger cat states and Fock states, in dissipative optomechanical systems, even when the cooperativity is smaller than one ($g^2/\kappa\gamma<1$). In contrast to the usual scheme of directly applying non-Gaussian operations on the entangled optical mode, we show that an additional phase-sensitive amplifier can accelerate the generation and also precisely control the type of NGSs. Then, a principally deterministic multi-photon subtraction induced by the Rydberg-blockade effect is adopted to produce large-sized NGSs. The protocol can be implemented with state-of-the-art experimental systems with close to unit fidelity. Moreover, it can also be extended to generate a four-component cat state and provide new possibilities for future quantum applications of NGSs.Comment: 7 pages, 4 figure

Open channel-based microchip electrophoresis interfaced with mass spectrometry via electrostatic spray ionization

The coupling between open channel-based microchip electrophoresis and mass spectrometry via electrostatic spray ionization is proposed for in situ detection of fractionated analytes. Electrophoretic separation is performed in an open channel fabricated in a plastic substrate. The solvent of background electrolyte is evaporated from the open channel because of Joule heating during electrophoresis, leaving the dried electrophoretic bands to be directly analyzed by mass spectrometry via scanning electrostatic spray ionization. Proof-of-concept results are obtained with fluorescent dyes and antibiotics as the test samples, demonstrating an efficient on-chip detection platform based on the electrophoresis and electrostatic spray ionization mass spectrometry

Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection

BACKGROUND: Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. RESULTS: In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. CONCLUSIONS: Our result demonstrates that metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture. Comparing with other existing methods, LPFS shows better performance to select a small set of key molecules. In addition, LPFS is a general methodology and can be applied to other high-dimensional data analysis, for example cancer genomics

Improved efficacy and reduced toxicity of doxorubicin encapsulated in sulfatide-containing nanoliposome in a glioma model

As a glycosphingolipid that can bind to several extracellular matrix proteins, sulfatide has the potential to become an&nbsp;effective targeting agent for tumors overexpressing tenasin-C in their microenvironment. To overcome the dose-limiting&nbsp;toxicity of doxorubicin (DOX), a sulfatide-containing nanoliposome (SCN) encapsulation approach was employed to&nbsp;improve treatment efficacy and reduce side effects of free DOX. This study analysed in vitro characteristics of sulfatidecontaining&nbsp;nanoliposomal DOX (SCN-DOX) and assessed its cytotoxicity in vitro, as well as biodistribution, therapeutic&nbsp;efficacy, and systemic toxicity in a human glioblastoma U-118MG xenograft model. SCN-DOX was shown to achieve highest&nbsp;drug to lipid ratio (0.5:1) and a remarkable in vitro stability. Moreover, DOX encapsulated in SCN was shown to be delivered&nbsp;into the nuclei and displayed prolonged retention over free DOX in U-118MG cells. This simple two-lipid SCN- DOX nanodrug has favourable pharmacokinetic attributes in terms of prolonged circulation time, reduced volume of distribution and&nbsp;enhanced bioavailability in healthy rats. As a result of the improved biodistribution, an enhanced treatment efficacy of SCNDOX&nbsp;was found in glioma-bearing mice compared to the free drug. Finally, a reduction in the accumulation of DOX in the&nbsp;drug&rsquo;s principal toxicity organs achieved by SCN-DOX led to the diminished systemic toxicity as evident from the plasma&nbsp;biochemical analyses. Thus, SCN has the potential to be an effective and safer nano-carrier for targeted delivery of&nbsp;therapeutic agents to tumors with elevated expression of tenascin-C in their microenvironment

Rotational symmetry breaking in superconducting nickelate Nd0.8Sr0.2NiO2 films

The infinite-layer nickelates, isostructural to the high-Tc superconductor cuprates, have risen as a promising platform to host unconventional superconductivity and stimulated growing interests in the condensed matter community. Despite numerous researches, the superconducting pairing symmetry of the nickelate superconductors, the fundamental characteristic of a superconducting state, is still under debate. Moreover, the strong electronic correlation in the nickelates may give rise to a rich phase diagram, where the underlying interplay between the superconductivity and other emerging quantum states with broken symmetry is awaiting exploration. Here, we study the angular dependence of the transport properties on the infinite-layer nickelate Nd0.8Sr0.2NiO2 superconducting films with Corbino-disk configuration. The azimuthal angular dependence of the magnetoresistance (R({\phi})) manifests the rotational symmetry breaking from isotropy to four-fold (C4) anisotropy with increasing magnetic field, revealing a symmetry breaking phase transition. Approaching the low temperature and large magnetic field regime, an additional two-fold (C2) symmetric component in the R({\phi}) curves and an anomalous upturn of the temperature-dependent critical field are observed simultaneously, suggesting the emergence of an exotic electronic phase. Our work uncovers the evolution of the quantum states with different rotational symmetries and provides deep insight into the global phase diagram of the nickelate superconductors

Compatible Buffer for Capillary Electrophoresis and Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

A compatible buffer system for the coupling of capillary electrophoresis (CE) with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) was developed. The employed interface consists of a robot to drive a sliver-covered separation capillary and an AnchorChip MALDI-MS target. The outlet of the capillary is grounded and connected to the pre-deposited buffer droplet on the MALDI target to make the electric connection and allow sample crystallization for MALDI-MS. The possibility of using only one buffer already containing the matrix for MALDI-MS for the separation and the ionization was investigated and tested on protein and peptide samples. The results show that the proposed buffer system is suitable for CE-MALDI-MS coupling, simplifies the traditional buffer mixing steps in off-line CE-MALDI-MS protocols, and is therefore highly promising for on-line analysis

Highly sensitive detection of five typical fluoroquinolones in low-fat milk by field-enhanced sample injection based CE in bubble cell capillary

Fluoroquinolones are a group of synthetic antibiotics with a broad activity spectrum against mycoplasma, gram-positive and gram-negative bacteria. Due to the extensive use of fluoroquinolones in farming and veterinary science, there is a constant need in the analytical methods able to efficiently monitor their residues in food products of animal origin, regulated by Commission Regulation (European Union) no. 37/2010. Herein, field-enhanced sample injection for sample stacking prior the CZE separation was developed inside a bubble cell capillary for highly sensitive detection of five typical fluoroquinolones in bovine milk. Ethylenediamine was proposed as the main component of BGE for the antibiotics separation. The effect of BGE composition, injection parameters and water plug length on the field-enhanced sample injection based CE with UV detection was investigated. Under the optimized conditions, described field-enhanced sample injection based CE-UV analysis of fluoroquinolones provides LODs varying from 0.4 to 1.3 ng/mL. These LOD values are much lower (from 460 to 1500 times) than those obtained by a conventional CE in a standard capillary without bubble cell. The developed method was finally applied for the analysis of fluoroquinolones in low-fat milk from a Swiss supermarket. Sample recovery values from 93.6% to 106.0% for different fluoroquinolones, and LODs from 0.7 to 2.5 μg/Kg, were achieved. Moreover, the proposed ethylenediamine-based BGE as volatile and compatible with MS system, enabled the coupling of the field-enhanced sample injection-based CE with a recently introduced electrostatic spray ionization MS via an iontophoretic fraction collection interface for qualitative fluoroquinolones identification