The reaction of H-phosphinates and secondary phosphine oxides with amines and alcohols proceeds highly stereospecifically to give the corresponding coupling products with inversion of configuration at the phosphorus center under the Atherton-Todd reaction conditions. This finding leads to the establishment of a general and efficient method for the synthesis of a variety of optically active organophosphorus acid derivatives from the easily available chiral H-phosphinates and secondary phosphine oxides.

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Matching people across multiple camera views known as person reidentification is a challenging problem due to the change in visual appearance caused by varying lighting conditions. The perceived color of the subject appears to be different under different illuminations. Previous works use color as it is or address these challenges by designing color spaces focusing on a specific cue. In this paper, we propose an approach for learning color patterns from pixels sampled from images across two camera views. The intuition behind this work is that, even though varying lighting conditions across views affect the pixel values of the same color, the final representation of a particular color should be stable and invariant to these variations, i.e., they should be encoded with the same values. We model color feature generation as a learning problem by jointly learning a linear transformation and a dictionary to encode pixel values. We also analyze different photometric invariant color spaces as well as popular color constancy algorithm for person reidentification. Using color as the only cue, we compare our approach with all the photometric invariant color spaces and show superior performance over all of them. Combining with other learned low-level and high-level features, we obtain promising results in VIPeR, Person Re-ID 2011, and CAVIAR4REID data sets.

2,2-Diphenyl-1-picrylhydrazyl-ultra-high performance liquid chromatography-Q-time-of-flight mass spectrometry (DPPH-UPLC-Q-TOF/MS), as a rapid and efficient means, now was used for the first time to screen antioxidants from Selaginella doederleinii. The nine biflavone compounds were screened as potential antioxidants. The biflavones were structurally identified and divided into the three types, that is, amentoflavone-type, robustaflavone-type, and hinokiflavone-type biflavonoids. Among the compounds bilobetin (3) and putraflavone (8) were found from Selaginella doederleinii for the first time and others including amentoflavone (1), robustaflavone (2), 4′-methoxy robustaflavone (4), podocarpusflavone A (5), hinokiflavone (6), ginkgetin (7), and heveaflavone (9) were identified previously in the plant. Moreover, nine biflavones possessed a good antioxidant activity via their DPPH free radical scavenging. It demonstrates that DPPH-UPLC-Q-TOF/MS exhibits strong capacity in separation and identification for small molecule. The method is suitable for rapid screening of antioxidants without the need for complicated systems and additional instruments.

As new green solvents, ionic liquids (ILs) have been generally applied in the extraction and separation of natural product. In this study, microwave assisted extraction based on IL (IL-MAE) was firstly employed to extract total biflavonoids from Selaginella doederleinii. Based on single-factor experiment, microwave power (300–700 W), extract time (30–50 min) and extract temperature (40–60 °C) on total bioflavonoids and antioxidant activities of the extracts were further investigated by a Box-Behnken design of response surface methodology (RSM) selecting total bioflavonoids yields and IC50 of radical scavenging as index. Besides antioxidant activity of the extract was evaluated by a 2,2-diphenyl-1-picrylhydarzyl (DPPH) and 2,2′-azinobis-(3-ethylbenzthiazoline-6-sulphonate (ABTS) radical scavenging assay, ferric reducing power assay and chelation of ferrous ions assay, and then anticaner activity was also researched against A549 cell line and 7721 cell line. The results illustrated that three factors and their interactions could be well suited for second-order polynomial models (p < 0.05). Through process parameters, optimization of the extract (460 W, 40 min, and 45 °C) and detection of bioactivity, the yield of total bioflavonoids was 16.83 mg/g and IC50 value was 56.24 μg/mL, respectively, indicating the extract has better anti-oxidation effect and antitumor activity. Furthermore, IL-MAE was the most efficient extracting method compared with MAE and Soxhlet extraction, which could improve extraction efficiency in a shorter time and at a lower temperature. In general, ILs-MAE was first adopted to establish a novel and green extraction process on the yields of total biflavonoids from S. doederleinii. In addition, the extract of containing biflavones showed potent antioxidant and anticancer capacity as a utilized valuable bioactive source for natural medicine.

Mobile networking researchers have long searched for largescale, fine-grained traces of human movement, which have remained elusive for both privacy and logistical reasons. Recently, researchers have begun to focus on geosocial mobility traces, e.g. Foursquare checkin traces, because of their availability and scale. But are we conceding correctness in our zeal for data? In this paper, we take initial steps towards quantifying the value of geosocial datasets using a large ground truth dataset gathered from a user study. By comparing GPS traces against Foursquare checkins, we find that a large portion of visited locations is missing from checkins, and most checkin events are either forged or superfluous events. We characterize extraneous checkins, describe possible techniques for their detection, and show that both extraneous and missing checkins introduce significant errors into applications driven by these traces.

As a new and green solvent, ionic liquids (ILs) have received more attention during the green extraction and separation process for natural medicines. In this paper, IL-ultrasound-assisted extraction (IL-UAE) of total biflavonoids (TBFs) from Selaginella helvetica was firstly developed, and different ILs were employed and compared. Based on single-factor experiment, solid–liquid ratio (1:10–1:14 g/mL), IL concentration (0.6–1.0 mmol/mL), and extract temperature (40–60 °C) were further explored, according to response surface methodology (RSM), with TBF yields as the index. Moreover, antioxidant activity of TBF extract was analyzed by four methods, i.e., 2,2-di(4-tert-octylphenyl)-1-picrylhydrazyl (DPPH) and 2,2′-azinobis-(3-ethylbenzth-iazoline-6-sulphonate (ABTS) free radical scavenging assay, ferric ion reducing power assay, and chelation of ferrous ions assay. The results indicated that [C6mim]PF6 had a high selectivity and efficiency. Moreover, important parameters for the extraction process were investigated and optimized. Through parameter optimization (0.8 mmol/L, 250 W, 40 min, 1:12.7 g/mL, and 47 °C), a yield of 18.69 mg/g biflavonoids was obtained from the extract of S. helvetica. Compared with ethanol-UAE, heat-reflux extraction, Soxhlet extraction, and percolation extraction, IL-UAE could not only obtain higher yield in a shorter time, but also reduce the solvent consumption. In addition, TBF extract showed potential antioxidant activity based on the above four antioxidant methods. In short, IL-UAE was first employed to develop a novel and green extraction method for TBF content, and this experiment provides valuable references for further utilization of S. helvetica.

The random sample consensus (RANSAC) based algorithm is widely used in estimating the two-view geometry from image point correspondences. However, it often becomes extremely slow when the data is contaminated by a large percentage of incorrect matches. To address this problem, the paper proposes a new modification of RANSAC called LP-RANSAC that is robust to varying inlier ratios and achieves large computational savings without deterioration in accuracy. LP-RANSAC integrates the locality preserving constraint into the universal RANSAC framework, which prunes most of the unreliable correspondences before the hypothesize-and-verify loop and guides non-uniform sampling to generate and verify promising models earlier. Unlike other guided sampling strategies, the proposed method is simple to implement and does not require any prior information. Extensive experiments performed on the publicly available datasets reveal that LP-RANSAC can achieve more accurate and stable solutions at much lower computational cost (in milliseconds on standard CPU) than state-of-the-art methods, particularly when handling problems with low inlier ratios. INDEX TERMS Robust estimation, RANSAC, outlier removal, image matching, two-view geometry.