Optimization of peak area precision of a GC–MS drug screening method using a nonparametric sign test

Objective: The aim of this paper is to show the application of the Non-Parametric Sign Test in problems involving the testing of central tendency values. Theoretical framework: Non-parametric methods are widely used in the study of populations that are taken in rank order (such as a movie that receives one to four star ratings). The use of non-parametric methods may also be necessary when the data has a ranking but no clear numerical interpretation, such as when accessing preferences. In terms of scale, non-parametric methods result in data that is "in order" (Thatcher et al., 2005) Method: Data was taken from a company in the South of Rio de Janeiro and a case study was carried out using the Non-Parametric Sign Test. Final Considerations: Initially it proved unfeasible to use a Parametric Test because the Anderson-Darling Test showed that the Assumption of Normality was not confirmed and finally the Non-Parametric Sign Test showed that the hypothetical Median really is the correct measure of Central Tendency. Implications of the research: The use of Non-Parametric Tests is widespread in scientific literature and has proven to be highly effective in dealing with data where the assumptions of Normality are not confirmed. Originality/value: Despite being well-known statistical tools, Non-Parametric Tests are widely used and can bring innovations to their application, as in the case of the company in question.

The objectives of this study were to compare nonparametric stability measures, and to identify promising high-yield and stable bread wheat (Triticum aestivum L.) genotypes in 7 environments during 2003-2005 in the central Black Sea region of Turkey. The bread wheat genotypes (20 advanced lines and 5 cultivars) were grown in a randomized complete block design with 4 replications in 7 different environments. Three nonparametric statistical tests of significance for genotype × environment (GE) interaction and 10 nonparametric measures of stability were used to identify stable genotypes in 7 environments. Combined ANOVA and nonparametric tests (Kubinger, Hildebrand, and De Kroon/Van der Laan) of genotype × environment interaction indicated the presence of significant crossover and non-crossover interactions, as well as significant differences between genotypes. In this study high TOP values (proportion of environments in which a genotype ranked in the top third) and low rank-sum values (sum of ranks of mean yield and Shukla’s stability variance) were associated with high mean yield. Nonetheless, results of the other nonparametric tests were negatively correlated with mean yield. In the simultaneous selection for high yield and stability, only the rank-sum and TOP methods were useful in terms of the principal component analysis (PCA) results, and correlation analysis of nonparametric stability statistics and yield. According to these stability parameters (TOP and rank-sum) G7 (VONA//KS75210/TAM101), G9 (JUP/4/CLLF/3/II14.53/ODIN//CI13431/WA 00477), G20 (Sakin), and G21 (VORONA/KAUZ//1D13.1/MLT) were the most stable genotypes for grain yield. The results also revealed that based on nonparametric test results stability could be classified into 3 groups, according to agronomic and biological concepts of stability.

To solve a fuzzy optimization problem, we need to compare fuzzy numbers. Here, we make use of our recently proposed modified Kerre’s method as an effective approach for comparison of LR fuzzy numbers. Using our new results on LR fuzzy numbers, we show that to compare two LR fuzzy numbers, we do not need to compute the fuzzy maximum of two numbers directly. We propose a new variable neighborhood search approach for solving fuzzy number quadratic programming problems by using the modified Kerre’s method. In our algorithm, a local search is performed using descent directions, found by solving five crisp mathematical programming problems. In several available methods, a fuzzy optimization problem is converted to a crisp problem, but in our proposed approach, using our modified Kerre’s method, the fuzzy optimization problem is solved directly, without changing it to a crisp program. We give some examples to compare the performance of our proposed algorithm with some available methods and show the effectiveness of our proposed algorithm by using the nonparametric statistical sign test.

The aim of this study was to compare the accuracy and the reproducibility of scotopic pupil measurements using 2 different methods. Scotopic pupil diameter was measured in 56 eyes of 28 volunteers and the results were compared between the green light test at the slit lamp (Haag-Streit, Switzerland) and the automatic measurements of the wave-front analyser WASCA (Carl-Zeiss-Meditec) by 2 independent examiners. Non-parametric sign test as well as All Pairwise Multiple Comparison Procedures (Student-Newman-Keuls method) were performed for the comparison of means for each individual eye as well as the results of both eyes tested by both examiners. Mean age of the subjects was 34.9 years. The colour of iris was green or blue in 22 cases and brown in 6 cases. REPRODUCIBILITY: For the green light test we found for the first investigator in the right eye a mean pupil diameter of 6.58 mm (SD 0.68). The measurement of the second investigator for the same eye was 6.64 mm (SD 0.61). The left eye values were as follows: 6.36 mm (SD 0.68) and 6.75 mm (SD 0.68). For WASCA we found for the first investigator in the right eye 6.33 mm (SD 0.64) vs. 6.30 mm (SD 0.64) for the second investigator, in the left eye 6.39 mm (SD 0.69) vs. 6.36 mm (SD 0.60). There was a statistically significant difference between the two investigators when the green light test was used (6.47 mm vs. 6.69 mm for both eyes). No difference was found using the WASCA integrated pupillometer (6.35 mm vs. 6.33 mm). There was a significant difference between the means of combined data for both measurement methods: 6.58 mm for the green light test (SD 0.57) vs. 6.34 mm for WASCA (SD 0.62). The integrated pupillometry of the WASCA analyser showed better reproducibility of measurements than the green light test. The green light test measures a slightly larger diameter (in the mean by 0.25 mm) than WASCA. Because of the fair and clinically sufficient reproducibility as well as virtually non-existing additional costs the green light test can be strongly recommended to referring ophthalmologists and low-volume refractive surgeons.

Oral Supplementation with a High-Fat, High-Energy Product Improves Nutritional Status and Alters Serum Lipids in Patients with Cystic Fibrosis

Turnout gear provides protection against dermal exposure to contaminants during firefighting; however, the level of protection is unknown. We explored the dermal contribution to the systemic dose of polycyclic aromatic hydrocarbons (PAHs) and other aromatic hydrocarbons in firefighters during suppression and overhaul of controlled structure burns. The study was organized into two rounds, three controlled burns per round, and five firefighters per burn. The firefighters wore new or laundered turnout gear tested before each burn to ensure lack of PAH contamination. To ensure that any increase in systemic PAH levels after the burn was the result of dermal rather than inhalation exposure, the firefighters did not remove their self-contained breathing apparatus until overhaul was completed and they were >30 m upwind from the burn structure. Specimens were collected before and at intervals after the burn for biomarker analysis. Urine was analyzed for phenanthrene equivalents using enzyme-linked immunosorbent assay and a benzene metabolite (s-phenylmercapturic acid) using liquid chromatography/tandem mass spectrometry; both were adjusted by creatinine. Exhaled breath collected on thermal desorption tubes was analyzed for PAHs and other aromatic hydrocarbons using gas chromatography/mass spectrometry. We collected personal air samples during the burn and skin wipe samples (corn oil medium) on several body sites before and after the burn. The air and wipe samples were analyzed for PAHs using a liquid chromatography with photodiode array detection. We explored possible changes in external exposures or biomarkers over time and the relationships between these variables using non-parametric sign tests and Spearman tests, respectively. We found significantly elevated (P < 0.05) post-exposure breath concentrations of benzene compared with pre-exposure concentrations for both rounds. We also found significantly elevated post-exposure levels of PAHs on the neck compared with pre-exposure levels for round 1. We found statistically significant positive correlations between external exposures (i.e. personal air concentrations of PAHs) and biomarkers (i.e. change in urinary PAH metabolite levels in round 1 and change in breath concentrations of benzene in round 2). The results suggest that firefighters wearing full protective ensembles absorbed combustion products into their bodies. The PAHs most likely entered firefighters’ bodies through their skin, with the neck being the primary site of exposure and absorption due to the lower level of dermal protection afforded by hoods. Aromatic hydrocarbons could have been absorbed dermally during firefighting or inhaled during the doffing of gear that was off-gassing contaminants.

Dolichonychia refers to nails that are elongated and slender. This nail morphology has been described in single case reports of patients with Ehlers-Danlos syndrome, hypohidrotic ectodermal dysplasia, and Marfan syndrome. The length and width of fingernails were measured in patients with Marfan syndrome and in individuals without the syndrome. A fingernail index was calculated for each person. A non-parametric sign test was used to compare the mean fingernail index of patients with Marfan syndrome and control subjects. The fingernail index ranged from 0.92 to 1.52 in patients with Marfan syndrome and from 0.77 to 1.30 in control individuals. The median fingernail index in women with Marfan syndrome (1.455) was significantly greater than the median fingernail index in women control subjects (1.080) (P = 0.035). Dolichonychia, defined as a fingernail index greater than or equal to 1.30, was present in six of eight (75%) of women with Marfan syndrome as compared with only one of 40 (2.5%) of women control subjects. Dolichonychia is a physical finding present in some patients with Marfan syndrome. The detection of long narrow fingernails in women should suggest the possibility of Marfan syndrome.

State of the Union Addresses (SOUA) by two recent US Presidents, President Obama (2016) and President Trump (2018), and a series of recent of tweets by President Trump, are analysed by means of the data mining technique, sentiment analysis. The intention is to explore the contents and sentiments of the messages contained, the degree to which they differ, and their potential implications for the national mood and state of the economy. President Trump's 2018 SOUA and his sample tweets are identified as being more positive in sentiment than President Obama's 2016 SOUA. This is confirmed by bootstrapped t tests and non-parametric sign tests on components of the respective sentiment scores. The issue of whether overly positive pronouncements amount to self-promotion, rather than intrinsic merit or sentiment, is a topic for future research.

Some Thoughts About Data Type, Distribution, and Statistical Significance

This study describes naturalistic 3-month follow-up after discharge from a 5-day partial hospitalization dialectical behavior therapy (DBT) program for women diagnosed with borderline personality disorder (BPD). We also examined individual BPD criteria as predictors of treatment response. Fifty women diagnosed with BPD were consecutively recruited from a partial hospital DBT program, 47 of whom (94%) completed all assessments including baseline (prior to discharge) and 3-months post-discharge assessments. Most continued with some combination of individual psychotherapy and pharmacotherapy, and all had the option of continuing with weekly DBT skills classes. Baseline scores were compared to 3-month scores using paired two-tailed non-parametric (sign) tests. Regression analyses were conducted to identify predictors of outcome. Depression, hopelessness, anger expression, dissociation, and general psychopathology scores significantly decreased over the 3-month follow-up interval, although scores on several measures remained in the clinical range. Those who endorsed emptiness, impulsivity, and relationship disturbance demonstrated improvement on a number of outcomes, while those who endorsed identity disturbance and fear of abandonment had less improvement on some outcomes. These findings illustrate (1) that improvement occurred over a 3-month interval on a number of measures in patients receiving treatment as usual following discharge from a partial hospitalization program, and (2) that BPD is a complex, heterogeneous disorder for which there is no single pathognomonic criterion, so that each criterion should be considered individually in determining its potential effect on treatment outcomes.

We present a novel action recognition method based on space-time locally adaptive regression kernels and the matrix cosine similarity measure. The proposed method uses a single example of an action as a query to find similar matches. It does not require prior knowledge about actions, foreground/background segmentation, or any motion estimation or tracking. Our method is based on the computation of novel space-time descriptors from the query video which measure the likeness of a voxel to its surroundings. Salient features are extracted from said descriptors and compared against analogous features from the target video. This comparison is done using a matrix generalization of the cosine similarity measure. The algorithm yields a scalar resemblance volume, with each voxel indicating the likelihood of similarity between the query video and all cubes in the target video. Using nonparametric significance tests by controlling the false discovery rate, we detect the presence and location of actions similar to the query video. High performance is demonstrated on challenging sets of action data containing fast motions, varied contexts, and complicated background. Further experiments on the Weizmann and KTH data sets demonstrate state-of-the-art performance in action categorization.

An investigation of nursing students' knowledge of dementia: A questionnaire study

Sludge from water treatment plants (WTPs) is usually processed by physicochemical clarification followed by thickening, which results in the production of an effluent from dewatering/drying sludge processes that can potentially impact the environment. This paper assessed the viability of employing sludge dewatering water from a water treatment sludge plant (WTSP) in São Paulo State, Brazil, for reuse purposes. Water quality variables were monitored in the effluent and receiving stream. The data were analyzed by paired samples Student t-test (parametric significance test), paired samples Wilcoxon signed rank test (non-parametric significance test), and principal component analysis (multivariate analysis). Despite the distribution of data, typically not Gaussian, both Student and Wilcoxon methods agreed in 9 out of 10 studied parameters regarding the influence of WTSP discharge on waterbody; only for total manganese the Wilcoxon approach provided better fit than Student. Principal component analysis helped to evince correlations among all variables. Results provided useful information for understanding the vocation of WTSP effluent for reuse. For direct non-potable reuse, recirculating the final effluent back to the WTP for two months saved 92,000 m3 of water, the volume of drinking water demanded by the city (n = 292,000 inhabitants) in approximately 30h.

Recently introduced in analyzing data from functional MRI (fMRI) and other neuroimaging techniques, Bayesian networks (BN) is a method to characterize effective connectivity patterns among multiple brain regions. So far, interests of using BN have been primarily on learning the connectivity pattern for each single group with well investigated computational algorithms. Examination of the connectivity pattern differences between groups, on the other hand, lacks rigorous statistical inference procedure. In this study, we propose using random permutation, a type of non-parametric statistical significance test in which a reference distribution is obtained by calculating all possible values of the test statistic under re-arrangements of the group labels on the observed data points, to infer whether the difference is significant. Two different approaches to perform the permutation test are introduced, compared to each other and both compared to the routinely used parametric t-test. Permutation approach 1 permutes the group labels first followed by learning BN pattern for each of the newly formed groups. Approach 2 learns BN pattern for each individual and connection parameters are then subjected to the group label permutations. Synthetic data generated under varying signal-to-noise ratios are used to investigate the performances of the proposed methods. Our results demonstrated that permutation approach 1 in detecting the effective connectivity pattern difference between two groups is superior to permutation approach 2 and to the common-sense two sample t-test.

This study aims to determine differences in the performance of the profitability ratio (ROA), sales growth ratio (SG), liquidity ratio (CR) and leverage ratio (DER) to bankruptcy prediction (Altman Z-score) before and during the Covid 19 pandemic. Descriptive statistical method with secondary data collection, namely quarterly financial reports from 2019-2020. Samples were taken by purposive sampling method and obtained 62 samples of the construction industry and consumer goods in 2019-2020. Normality testing using the Kolmogorov-Smirnov test results in data not normally distributed with a significance value below 0.05. Different tests using the non-parametric Wilcoxon sign test resulted in differences in ROA (0.000 &lt;0.05), SG (0.004 &lt;0.05) and CR (0.005 &lt;0.05) on the decreased bankruptcy predictions during the pandemic. Meanwhile, DER (0.803 &lt;0.05) did not differ from the prediction of bankruptcy before and during the COVID-19 pandemic