The information about a system's dynamics represented by measurement data sets are often confined to regions of restricted operations where the system is not sufficiently excited for model identification purposes. Experiments performed in closed-loop with safety constraints allow only for reduced order modeling. In the paper, a set of low order models are identified from real experimental data of the lateral dynamics of an electric passenger car. Low order models are advantageous for on-line computation in model-based control, though uncertainty due to neglected dynamics may deteriorate control performance and constraint satisfaction. The effect of uncertainty is analyzed by controller cross-validation where a controller designed based on one model is evaluated on other models playing the role of the true system. This method allows us to qualify not only model-controller pairs, but to determine the properties of input data and model uncertainty, which lead to more useful data sets, more robust and better performing controllers than the others.

When optimizing multi-dimensional non-linear problems the optimal solution in technical terms can be found by heuristic methods. It seems that human thinking does not work properlywith the mathematical processing: human decisionmakers tend to reject options that represent extreme values in the set of parameters and are not able to handle many system parameters at the same time. The paper investigates the best possible way for modeling the human thinking, comparing bacterial memetic algorithm and particle swarm optimization in fuzzy environment. © Springer-Verlag Berlin Heidelberg 2012.

Economic security can be considered as an economic aspect of the life of an individual or household that provides the opportunity to achieve financial stability and improve living standards. In this context, understanding the impact of economic affordability of food on the economic security of the country is of great importance. The authors propose to use the indicator of economic affordability of food for in-depth analysis of the economic security of the country. Indicators that determine the level of economic affordability of food products in Ukraine for 2000-2018 are calculated. The regression analysis made it possible to establish a close relationship between the indicators of food expenditures and the level of GDP per capita, between the level of income and expenditure of food of decile groups. Correlation coefficients between the consumption of six basic foodstuffs and the level of per capita income in Ukraine are determined. The obtained indicators, which determine the economic affordability of food, allow us to conclude that there is a lack of economic protection at the level of individual low-income households. Overcoming economic instability and minimizing the possible consequences of the low level of economic affordability of food should become one of the main tasks of Ukraine's economic security.

Background: Chronic respiratory diseases are an important global issue, particularly in Asia, where burden patterns vary widely across countries. With more than half the world's population living in Asia, understanding the national and regional burden of chronic respiratory diseases is essential; however, research on this area remains inadequate. We aimed to investigate the burden of chronic respiratory diseases in Asia at national and regional levels, and to identify key risk factors. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study 2023 provides estimates for assessing the burden of chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease (ILD), and pulmonary sarcoidosis. We focused on 34 countries in Asia, encompassing the high-income Asia Pacific region and central, east, south, and southeast Asia. Estimates for age-standardised prevalence and disability-adjusted life-year (DALY) rates per 100 000 population, including 95% uncertainty intervals (UIs), were extracted by location, sex, year, and Socio-demographic Index (SDI). The average annual percentage change was calculated and presented as a percentage with 95% CIs. Estimates of modifiable attributable risk factors for DALYs and mortality were also included. Findings: In Asia, the age-standardised prevalence and DALY rates for chronic respiratory diseases generally declined from 1990 to 2023; however, the trend varied substantially by disease and country. In 2023, the age-standardised prevalence rate of COPD was highest in south Asia (3044·18 [95% UI 2748·67–3303·04] per 100 000 population), while the age-standardised asthma prevalence rate was highest in the high-income Asia Pacific region (4870·24 [4046·70–5962·78] per 100 000 population) and southeast Asia (4778·18 [3970·25–5735·61] per 100 000 population). Despite southeast Asia and the high-income Asia Pacific region having a similar age-standardised asthma prevalence rate, southeast Asia had a higher age-standardised DALY rate (508·67 [95% UI 394·89–669·92] per 100 000 population) compared with the high-income Asia Pacific region (204·40 [129·23–290·41] per 100 000 population). A decrease in the age-standardised DALY rate for chronic respiratory diseases was observed with increasing SDI, contrasting with its prevalence patterns. Age-standardised DALY rates of COPD decreased in all Asian countries except for Georgia (average annual percentage change 1·37 [95% CI 1·26–1·48]) and Kazakhstan (0·73 [0·55–0·93]), and age-standardised DALY rates of asthma decreased in all countries. Smoking and ambient particulate matter pollution were identified as leading attributable risk factors for chronic respiratory diseases across Asia. Household air pollution from solid fuels was a regionally pronounced risk factor for chronic respiratory diseases, particularly in south Asia (age-standardised DALY rate 657·58 [95% UI 485·04–880·45] per 100 000 population). Although smoking was a major risk factor in males, ambient particulate matter pollution and secondhand smoke emerged as important attributable risk factors for chronic respiratory diseases in females. Interpretation: Countries with lower SDI had markedly higher DALY rates, highlighting the need to address socioeconomic and health-care inequities. Household air pollution from solid fuels continues to impose a substantial but preventable burden in south Asia, calling for clean energy adoption and improved ventilation. Funding: Gates Foundation.

This paper focuses on auditory sensory substitution for providing visually impaired users with suitable information in both static scene recognition and dynamic obstacle avoidance. We introduce three different sonification models together with three temporal presentation schemes, i.e. ways of temporally organizing the sonic events in order to provide suitable information. Following an overview of the motivation and challenges behind each of the solutions, we describe their implementation and an evaluation of their relative strengths and weaknesses based on a set of experiments conducted in a virtual environment.

Planar optical waveguides were fabricated in Pr:YLF crystals by ion implantation. In a further step, ridge waveguides were fabricated using precision diamond dicing. These enable strong light confinement and have propagation losses as low as 0.4 dB/cm. To study the influence of ion implantation on the spectroscopic properties, fluorescence and lifetime measurements were conducted in the ridge waveguides. Under blue pumping, small-signal optical gains of 6.5 dB/cm and 5 dB/cm were demonstrated at wavelengths of 607 nm and 639 nm, respectively. These results make ion-implanted ridge waveguides in Pr:YLF promising candidates for compact integrated lasers in the visible spectral region with high output powers in the watt range.

Optimization methods known from the literature include gradient techniques and evolutionary algorithms. The main idea of gradient methods is to calculate the gradient of the objective function at the actual point and then to step towards better values according to this value. Evolutionary algorithms imitate a simplified abstract model of evolution observed in nature. Memetic algorithms traditionally combine evolutionary and gradient techniques to exploit the advantages of both methods. Our current research aims to discover the properties, especially the efficiency (i.e. the speed of convergence) of particular evolutionary and memetic algorithms. For this purpose the techniques are compared by applying them on several numerical optimization benchmark functions and on fuzzy rule base identification.

Background Breast cancer is a leading cause of mortality and morbidity among females worldwide. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, we provided an updated comprehensive assessment of the epidemiological trends, disease burden, and risk factors associated with breast cancer globally, regionally, and nationally from 1990 to 2023. Methods Breast cancer incidence, mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) were estimated by age and sex for 204 countries and territories from 1990 to 2023. Mortality estimates were generated using GBD Cause of Death Ensemble models, leveraging data from population-based cancer registration systems, vital registration systems, and verbal autopsies. Mortality-to-incidence ratios were calculated to derive both mortality and incidence estimates. Prevalence was calculated by combining incidence and modelled survival estimates. YLLs were established by multiplying age-specific deaths with the GBD standard life expectancy at the age of death. YLDs were estimated by applying disability weights to prevalence estimates. The sum of YLLs and YLDs equalled the number of DALYs. Breast cancer burden attributable to seven risk factors was examined through the comparative risk assessment framework. The GBD forecasting framework was used to forecast breast cancer incidence and mortality from 2024 to 2050. Age-standardised rates were calculated for each metric using the GBD 2023 world standard population. Findings In 2023, there were an estimated 2·30 million (95% uncertainty interval [UI] 2·01 to 2·61) breast cancer incident cases, 764 000 deaths (672 000 to 854 000), and 24·1 million (21·3 to 27·5) DALYs among females globally. In the World Bank low-income group, where a low age-standardised incidence rate (ASIR) was estimated (44·2 per 100 000 person-years [31·2 to 58·4]), the age-standardised mortality rate (ASMR) was the highest (24·1 per 100 000 [16·8 to 31·9]). The highest ASIR was in the high-income group (75·7 per 100 000 [67·1 to 84·0]), and the lowest ASMR was in the upper-middle-income group (11·2 per 100 000 [10·2 to 12·3]). Between 1990 and 2023, the ASIR in the low-income group increased by 147·2% (38·1 to 271·7), compared with a 1·2% (–11·5 to 17·2) change in the high-income group. The ASMR decreased in the high-income group, changing by –29·9% (–33·6 to –25·9), but increased by 99·3% (12·5 to 202·9) in the low-income group. The increase in age-standardised DALY rates followed that of ASMRs. Risk factors such as dietary risks, tobacco use, and high fasting plasma glucose contributed to 28·3% (16·6 to 38·9) of breast cancer DALYs in 2023. The risk factors with a decrease in attributable DALYs between 1990 and 2023 were high alcohol use and tobacco. By 2050, the global incident cases of breast cancer among females were forecast to reach 3·56 million (2·29 to 4·83), with 1·37 million (0·841 to 2·02) deaths. Interpretation The stable incidence and declining mortality rates of female breast cancer in high-income nations reflect success in screening, diagnosis, and treatment. In contrast, the concurrent rise in incidence and mortality in other regions signals health system deficits. Without effective interventions, many countries will fall short of the WHO Global Breast Cancer Initiative's ambitious target of achieving an annual reduction of 2·5% in age-standardised mortality rates by 2040. The mounting breast cancer burden, disproportionately affecting some of the world's most vulnerable populations, will further exacerbate health inequalities across the globe without decisive immediate action. Funding Gates Foundation, St Jude Children's Research Hospital.

The continuous tribological development of engine lubricants is becoming more and more vital due to its fuel efficiency improvement and lifetime increasing potential. The antiwear additives play a high role in the lubricants to protect the contacting surfaces even in the presence of thinner oil film. Nanoscale spherical particles in the lubricant may increase the necessary protecting effect. This paper presents the results of the experimental tribological investigation of nanoscale spherical Y2O3 (yttria) ceramic particles as an engine lubricant additive. The ball-on-disc tribological measurements have revealed an optimum concentration at 0.5 wt% with about 45% wear scar diameter and 90% wear volume decrease, compared to the reference, neat Group III base oil. The high-magnitude SEM analysis revealed the working mechanisms of yttria: the particles collected in the roughness valleys resulted in a smoother contacting surface, they were tribo-sintered and they have also caused slight plastic deformation of the outer layer of the metallic surface.