The availability of a sensitive and rapid analytical method for the determination of opiates, and other substances of forensic interest, in a variety of biological specimens is of utmost importance to forensic laboratories. Solid-phase extraction is very popular in the pre-treatment of forensic samples. Nevertheless, a new approach, disposable pipette extraction (DPX), is gaining increasing interest in sample preparation. DPX has already been applied to the analysis of drugs of abuse in common biological matrices, such as urine and blood, but has not yet been evaluated on alternative biological samples, such as vitreous humor. The objective of this study was to evaluate the applicability of DPX on the analysis of opiates in vitreous humor. The currently developed method is fast, reliable, and easy to perform. The sensitivity, precision, and accuracy are satisfactory. Recoveries obtained are within the range of 72-91%, whereas the sample volume of vitreous humor required is only 100 μL. 相似文献
Herein a quantitative method for the determination of seven penicillins in bovine plasma and veterinary drugs has been developed. Amoxicillin (AMO), ampicillin (AMP), penicillin G (PENG), penicillin V (PENV), oxacillin (OXA), cloxacillin (CLO) and dicloxacillin (DICLO) were separated on a Perfectsil ODS‐2 (250×4 mm, 5 μm) column, using gradient elution, with a mobile phase of 0.1% v/v TFA and ACN–methanol (90:10 v/v). PDA detection was used at 240 nm. Penicillins were isolated from bovine plasma by SPE on Lichrolut RP‐18 cartridges with mean recoveries from 85.7 to 113.5%. Colchicine (3 ng/μL) was used as an internal standard. The developed method was validated in terms of selectivity, linearity, accuracy, precision, stability and sensitivity. Repeatability (n = 5) and between‐day precision (n = 5) revealed RSD < 12%. The detection limits in the bovine plasma were estimated as 18 ng for AMO and AMP, 25 for PENG, PENV and OXA, 3 ng for CLO and 12 ng for DICLO. Spiked plasma samples were stable for 1 wk, except for AMP and CLO, which were stable for 3 wk and OXA for 4 wk. AMO, PENG and PENV were stable for two freeze–thaw cycles, OXA, CLO and DICLO for four, while AMP only for one. 相似文献
Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms.
Journal of Nonlinear Science - The original version of this article unfortunately contained an error in Acknowledgement section. The authors would like to correct the error with this erratum. The... 相似文献
To account for variations in the frequency, time, and space dimensions, dynamic re-use of licensed bands under the cognitive radio (CR) paradigm calls for innovative network-level sensing algorithms for multi-dimensional spectrum opportunity awareness. Toward this direction, the present paper develops a collaborative scheme whereby CRs cooperate to localize active primary user (PU) transmitters and reconstruct a power spectral density (PSD) map portraying the spatial distribution of power across the monitored area per frequency band and channel coherence interval. The sensing scheme is based on a parsimonious model that accounts for two forms of sparsity: one due to the narrow-band nature of transmit-PSDs compared to the large portion of spectrum that a CR can sense, and another one emerging when adopting a spatial grid of candidate PU locations. Capitalizing on this dual sparsity, an estimator of the model coefficients is obtained based on the group sparse least-absolute-shrinkage-and-selection operator (GS-Lasso). A novel reduced-complexity GS-Lasso solver is developed by resorting to the alternating direction method of multipliers (ADMoM). Robust versions of this GS-Lasso estimator are also introduced using a GS total least-squares (TLS) approach to cope with both uncertainty in the regression matrices, arising due to inaccurate channel estimation and grid-mismatch effects, and unexpected model outliers. In spite of the non-convexity of the GS-TLS criterion, the novel robust algorithm has guaranteed convergence to (at least) a local optimum. The analytical findings are corroborated by numerical tests. 相似文献