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According to the International Maritime Organization (IMO) (2010), more than one million metric tons of oil are spilled into oceans annually, resulting in severe and far-reaching consequences for marine ecosystems. Therefore, the aim of this paper is to offer insights into enhancing environmental protection and preparedness for more efficient responses. This is achieved by studying simulations of oil spill trajectories presented in 18 different scenarios within the semi-enclosed coastal basin of Kaštela Bay in the Adriatic Sea. Given the sensitivity of this area, incident simulations were generated using the Potential Incident Simulation, Control, and Evaluation System (PISCES II) simulator. Three worst-case scenarios are introduced in order to give an insight into the potential incident impact on the marine environment. Furthermore, observing through forward stepwise generated multiple regression model (F=2.734; R=0.517; p=0.097) variable height of wave was identified as a statistically significant predictor of speed at which oils spread in (b=1.965; p=0.047). In addition, the non-parametric Mann–Whitney U test was applied for the validity of the calculated regression model assessment. The paper provides insights into linear relations between the most appropriate predictor (height of wave) and criterion (speed at which oil spreads), and it can be used as a starting point for risk assessment analyses of the incidents. Furthermore, the results of this research provide a possibility to ensure that safe and effective preparedness measures are set in place. Last but not least, results are implicitly pointing to the benefits and sufficiency of equipment for responding to real-life oil pollution incidents. [ABSTRACT FROM AUTHOR]

The physical condition of an occupant's home represents a significant factor in determining the dweller's overall quality of life. This paper provides a statistical framework for measuring housing quality in an urban area through a standardized index. This index is constructed using principal component analysis, incorporating demographic, geographic, and economic factors from the New York City Housing and Vacancy Survey. This metric allows for investigating differences in housing quality based upon ownership status. Analysis of the index demonstrates that renters face more housing quality issues than owners. Several of the index's input variables driving these differences were found to exhibit varying effects on housing quality over time, possibly due to events such as the 2008 financial crisis. Implementing this novel statistical framework, housing quality indices can be constructed for other cities to examine housing disparities and inform policies aimed at improving quality of life for urban residents. [ABSTRACT FROM AUTHOR]

The article deals with assessing and analyzing the standard of living of the population of a particular region. The objective of the article is to assess changes in the standard of living of the population of the Republic of Buryatia that occurred in 2012–2018 compared to 2005–2011. Assuming a relationship between the standard of living and structure of household expenditures, the authors analyze structural shifts in six components of the population's monetary expenditures. The article provides point and interval estimates of structural shifts obtained by the bootstrap method; statistical significance is checked by the Mann–Whitney and permutation test. Based on the calculation results, it is concluded that the standard of living in the Republic of Buryatia has decreased, which is reflected in characteristic changes in the structure of consumer spending, an increase in the share of mandatory payments and contributions, as well as a negative difference in household income and expenses. The estimates of structural shifts given in the article can be used as benchmarks or target indicators by the authorities in developing measures to improve the standard of living the republic's population. The methodology described in the study can also be used to analyze the standard of living at the federal district and national levels, as well as in interregional comparisons. [ABSTRACT FROM AUTHOR]

Due to the spatial-temporal inadequacy of large-scale general circulation models (GCMs), linking large-scale GCM data with small-scale local climatic data has found great interest. In this paper, in order to downscale minimum and maximum temperatures and precipitation predictands, the performance of three statistical downscaling techniques including Long Ashton Research Station-Weather Generator (LARS-WG), statistical downscaling model (SDSM), and artificial neural network (ANN) was compared based on Intergovernmental Panel on Climate Change-Fifth Assessment Report (IPCC-AR5) in northwest Iran. For this purpose, a nonparametric test named Mann-Whitney test, Spearman correlation coefficient, and the root mean square error (RMSE) were utilized to assess the efficiency of downscaling models. To scrutinize the climate change impacts, periods of 1961–1990 and 1991–2005 were considered as the baseline and verification periods, respectively. The findings revealed the superior performance of the ANN model for minimum and maximum temperatures, while for precipitation predictand, the SDSM represented the best performance among the models. Simulation results for future temperature indicated an ascending trend as 0.1–1.3 °C, 0.3–1.7 °C, and 0.5–2.1 °C for LARS-WG, SDSM, and ANN techniques, respectively. On the other hand, simulation outputs for the precipitation indicated a descending trend of 10–30% in future precipitation of the region according to downscaling models under Representative Concentration Pathway 8.5 (RCP8.5) pessimistic scenario of Hadley Center Coupled Model version 3 (HadCM3) GCM model. [ABSTRACT FROM AUTHOR]

An algorithm for assessing the possibility of joining two datasets obtained by different operators for attestation of standard samples of biological medicinal substances (SS BMS) is proposed. These studies tested the uniformity of the results obtained by different operators during attestation of industrial standard samples of the specific activity of an oral poliomyelitis vaccine, i.e., divalent live attenuated types 1 and 3 "BiVak polio" vaccine, using the Mann-Whitney and Z statistics for independent sets run manually using a formula, with subsequent interpretation of the results. Results from calculation of the Mann-Whitney test in Statistica software (version 10) are presented. [ABSTRACT FROM AUTHOR]

The addition of runs-rules has been recommended to improve the performance of classical, normal theory Shewhart-type control charts, for detecting small to moderate size shifts. In this paper, we consider adding both standard and improved runs-rules to enhance the performance of the distribution-free Phase II Shewhart-type chart based on the well-known Mann-Whitney statistic proposed by Chakraborti and Van de Wiel [1]. Standard runs-rules are typically of the form w- of-( w + v) with w > 1 and v ≥ 0, and the improved runs-rules scheme is a combination of the classical 1-of-1 runs-rule and the w- of-( w + v) runs-rules. The improved scheme improves the performance of the charts in detecting larger shifts while maintaining its performance in detecting small to moderate shifts. The in-control and out-of-control performance of the proposed runs-rules enhanced distribution-free charts are examined through extensive simulations. It is seen that the proposed charts have attractive performance compared to some competing charts and are better in many cases. An illustrative example is provided, along with a summary and conclusions. [ABSTRACT FROM AUTHOR]

Experience with real data indicates that psychometric measures often have heavy-tailed distributions. This is known to be a serious problem when comparing the means of two independent groups because heavy-tailed distributions can have a serious effect on power. Another problem that is common in some areas is outliers. This paper suggests an approach to these problems based on the one-step M-estimator of location. Simulations indicate that the new procedure provides very good control over the probability of a Type I error even when distributions are skewed, have different shapes, and the variances are unequal. Moreover, the new procedure has considerably more power than Welch's method when distributions have heavy tails, and it compares well to Yuen's method for comparing trimmed means. Wilcox's median procedure has about the same power as the proposed procedure, but Wilcox's method is based on a statistic that has a finite sample breakdown point of only 1/ n, where n is the sample size. Comments on other methods for comparing groups are also included. [ABSTRACT FROM AUTHOR]

For six proteins involved in transcriptional regulation of the early embryonic development of Drosophila melanogaster, DNA regions with significant binding as determined by chromatin immunoprecipitation with subsequent hybridization on a biochip (the ChIP-chip method) were considered. At the same time, binding site clusters of these proteins were predicted computationally. The theoretical and experimental data were compared for all pairwise combinations of factors studied. For chromosome 2R, it was shown that the intensity of the ChIP-chip signal differed significantly between the regions within and outside the predicted binding site clusters. In spite of the difficulties caused by the ChIP-chip signal noise, comparison of the experimental data in various pairwise combinations indicated that certain factors tend to bind in the same DNA regions, which supports the evidence of their functional association. Therefore, comparison of ChIP-chip data with the results of sequence analysis can reveal functionally interconnected regulatory subsystems even in systems studied less comprehensively than the system of regulation of the early embryonic development of D. melanogaster. [ABSTRACT FROM AUTHOR]

This research focuses on the factors of survival and growth of new enterprises in Tunisia. Based on previous research, we hypothesize that three factors influence the survival and growth of these firms: factors related to the entrepreneur, factors related to organizational characteristics and characteristics of the environment from start-up. We test these assumptions on a sample of 60 companies. The results show that human capital and the experience of the entrepreneur have a relatively small impact on the survival of newly created firms. Similarly, the intensity of preparation for creation by accompanying structures is not generally a key factor for survival. On the other hand, organizational characteristics (the amount of capital invested at start-up or customer structure) are strongly linked to the survival of the latter. [ABSTRACT FROM AUTHOR]