Artful determination : "state of the art" and PCME Ltd v. Goyen COntrols Co. UK Ltd

In a recent decision by Mr Justice Laddie, a patent was held anticipated by, inter alia, prior use of a device which fell within the claims of the patent in suit, even though its circuitry was enclosed in resin. The anticipating invention had been "made available to the public" within the terms of section 2 (2) of the Patents Act 1977 because its essential integers would have been revealed by an interesting character, the "skilled forensic engineer".

Simultaneous kinetic spectrophotometric determination of norfloxacin and rifampicin in pharmaceutical formulation and human urine samples by use of chemometrics approaches

A kinetic spectrophotometric method with aid of chemometrics is proposed for the simultaneous determination of norfloxacin and rifampicin in mixtures. The proposed method was applied for the simultaneous determination of these two compounds in pharmaceutical formulation and human urine samples, and the results obtained are similar to those obtained by high performance liquid chromatography.

The development of a new method for the determination of concentrations of carbonaceous gases using a non-dispersive infrared sensor

An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.

Simultaneous determination by UPLC-ESI-MS of scoparone, capillarisin, rhein, and emodin in rat urine after oral administration of Yin Chen Hao Tang preparation

A simple, sensitive, and validated method was developed for simultaneous determination of scoparone, capillarisin, rhein, and emodin in rat urine by ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC-MS). The urinary samples were analyzed on an Acquity UPLC BEH C18 1.7 microm 2.1x50 mm column. Scoparone, capillarisin, rhein, and emodin in rat urine were simultaneously analyzed with good separation. The lower limits of detection were 6.0, 9.0, 7.0, and 3.0 ng/mL, and the lower limits of quantification were 20.0, 33.0, 24.0, and 12.0 ng/mL for scoparone, capillarisin, rhein, and emodin, respectively. The intra- and inter-day precisions (RSD) were less than 9%. The intra- and inter-accuracies were found to be in the range of 94.14-104.54% for scoparone, 101.72-107.34% for capillarisin, 95.24-103.59% for rhein, and 101.32-107.82% for emodin at three concentration levels. The absolute recoveries for scoparone, capillarisin, rhein, and emodin were not less than 77.0%. The developed method has been applied to determine scoparone, capillarisin, rhein, and emodin in rat urine after oral administration of Yin Chen Hao Tang preparation, a traditional Chinese medicine formulation widely used in China for treatment of jaundice and liver disorders.

Quality evaluation of Yin Chen Hao Tang extract based on fingerprint chromatogram and simultaneous determination of five bioactive constituents

A completely validated method based on HPLC coupled with photodiode array detector (HPLC-UV) was described for evaluating and controlling quality of Yin Chen Hao Tang extract (YCHTE). First, HPLC-UV fingerprint chromatogram of YCHTE was established for preliminarily elucidating amount and chromatographic trajectory of chemical constituents in YCHTE. Second, for the first time, five mainly bioactive constituents in YCHTE were simultaneously determined based on fingerprint chromatogram for furthermore controlling the quality of YCHTE quantitatively. The developed method was applied to analyze 12 batches of YCHTE samples which consisted of herbal drugs from different places of production, showed acceptable linearity, intraday (RSD <5%), interday precision (RSD <4.80%), and accuracy (RSD <2.80%). As a result, fingerprint chromatogram determined 15 representative general fingerprint peaks, and the fingerprint chromatogram resemblances are all better than 0.9996. The contents of five analytes in different batches of YCHTE samples do not indicate significant difference. So, it is concluded that the developed HPLC-UV method is a more fully validated and complete method for evaluating and controlling the quality of YCHTE.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Salt in the desert: A comparison of clinical versus serum-calculated osmolality determination of dehydration

Background: Clinicians frequently use their own judgement to assess patient’s hydration status although there is limited evidence for the diagnostic utility of any individual clinical symptom. Hence, the aim of this study was to compare the diagnostic accuracy of clinically assessed dehydration in older hospital patients (using multiple symptoms), versus dehydration measured using serum-calculated osmolality (CO) as the reference standard. Method: Participants were 44 hospital patients aged ≥ 60 years. Dehydration was assessed clinically and pathologically (CO) within 24 hours of admission and at study exit. Indicators of diagnostic accuracy were calculated. Results: Clinicians identified 27% of patients as dehydrated at admission, and 19% at exit, compared to 19% and 16% using CO. Agreement between the measures was fair at admission and poor at exit. Clinical assessment showed poor sensitivity for predicting dehydration with reasonable specificity. Conclusions: Compared to the use of CO, clinical assessment of dehydration in older patients was poor. Given that failure to identify dehydration in this population may have serious consequences, we recommend that clinicians do not rely upon their own assessments without also using the reference standard.

Determination of preventive maintenance lead time using hybrid analysis

The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.