The main objective of this paper, based upon the extensive empirical research of free flow in local conditions, is to quantify the unfavourable impact of the flow structure on the road capacity using PCE (Passenger Car Equivalent) values as a function of longitudinal grade. Based on literature reviews and empirical research, it has been proved that the PCE value for all vehicle classes is directly correlated with the road gradient. The PCE values in free flow conditions have been determined for the approved vehicle classes. Based on the measured values, models for determining the average PCE value depending on the upward grade on two-lane roads have been developed. Comparison of the developed models in conditions of free traffic flow with the Highway Capacity Manual (HCM) models has shown lower PCE values in this research. Models for the percentage of PCE values PCE15%, PCE50% and PCE85% have also been established.

Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT'nDRIVE aims to solve the “random walk facility location” (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: “multihitting time,” the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene. When applied to 2200 tumors from four major cancer types, HIT'nDRIVE revealed many potentially clinically actionable driver genes. We also demonstrated that it is possible to perform accurate phenotype prediction for tumor samples by only using HIT'nDRIVE-seeded driver gene modules from gene interaction networks. In addition, we identified a number of breast cancer subtype-specific driver modules that are associated with patients’ survival outcome. Furthermore, HIT'nDRIVE, when applied to a large panel of pan-cancer cell lines, accurately predicted drug efficacy using the driver genes and their seeded gene modules. Overall, HIT'nDRIVE may help clinicians contextualize massive multiomics data in therapeutic decision making, enabling widespread implementation of precision oncology.

Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT'nDRIVE aims to solve the "random walk facility location" (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: "multi-hitting time", the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene. When applied to 2200 tumors from four major cancer types, HIT'nDRIVE revealed many potentially clinically actionable driver genes. We also demonstrated that it is possible to perform accurate phenotype prediction for tumor samples by only using HIT'nDRIVE seeded driver gene modules from gene interaction networks. In addition, we identified a number of breast cancer subtype-specific driver modules that are associated with patients' survival outcome. Furthermore, HIT'nDRIVE, when applied to a large panel of pan-cancer cell-lines, accurately predicted drug efficacy using the driver genes and their seeded gene modules. Overall, HIT'nDRIVE may help clinicians contextualize massive multi-omics data in therapeutic decision making, enabling widespread implementation of precision oncology.

Objective: The aim of this study was to examine whether there is a correlation between self-evaluated quality of life, anxiety, depression, motivation, subjective-rated financial status, education, age and autonomous movements in patients with chronic conditions. Respondents and Methods: The study consecutively included 68 chronically ill patients, the average chronological age of 56.21 years. The Hospital Anxiety and Depression Scale for self-evaluation of the quality of life of respondents was used to evaluate the presence of anxiety and depression, the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form was used for self-evaluation of the quality of life, and the Visual analogue scale of motivation was used for self-evaluation of the level of motivation. Results: It was found that anxiety, depression, education, financial status, chronological age and mobility have a significant impact on the sense of satisfaction with the quality of life of patients with chronic diseases. Conclusions: These results are important for clinical practice, planning and delivery of health services, evaluation of the implemented public health measures.

The aim of this paper is to determine the differences in life skills of young people with and without disability in chronological age from 18-35 year-old in Tuzla Canton. The respondents sample consists of two sub-samples. First sub-sample contains 50 young people with disability, chronological age from 18-35 of both genders. Second sub-sample contained 50 young people without disability, chronological age from 18- 35 of both genders. Research data were analysed using method of parametric and non-parametric statistics. Frequencies, percentages and measures of central tendency have been calculated (arithmetic mean and standard deviation). P-values have been used for examining the difference between variables and variance analysis has been used for examining the importance of differences. The results show that there is a significant statistical difference between young people with and without disabilities in the of life skills assessed: job retention skills, skills to cope in danger. Based on the results obtained, it is recommended to start the program and training in early age which will make life easier to disabled persons and their families.