It is widely known that virtual laboratories can improve and complete university lectures. This paper presents laboratories, that allow engineering students to design a pole placement based controller for typical control problems: inverted pendulum, Furuta pendulum, crane, ball and beam. The dynamics of the plants and instructions for controller design and test are provided on smartboards of the virtual laboratory. The controller can be designed by the help of Octave Online. Finally, the controller performance can be studied by the model of the real-life application. The mathematical models and controller design are presented as well as the experiences in the virtual laboratory of control engineering.

Our long-term goal is to implement autonomous vehicle control functions on a standard vehicle. At first we started with the investigation of the steering, which is a crucial area of the control of autonomous vehicles. As a part of the program, vehicle dynamical measurements were carried out on a Nissan Leaf electric vehicle equipped with a sensor system, furthermore we design a high-level trajectory-tracking controller.

Oil pumpkin is a major emerging alternative crop with several unresolved weed management questions in central-eastern Europe, one of the focal regions of oil pumpkin production worldwide. This study aims to assess the importance of three groups of factors: environment, non-chemical management (all management excluding herbicides), and chemical weed management, in determining the weed species composition of oil pumpkin crops in Hungary. We surveyed the weed flora of 180 oil pumpkin fields across the country, along with 32 background variables. Applying a minimal adequate model consisting of 18 terms with significant net effects, 30.8% of the total variation in weed species data could be explained. Most variation in species composition was determined by environmental factors, with climatic conditions (precipitation and temperature) being most influential. The net effects of seven non-chemical management variables (preceding crop, N and P fertilisers, seeding rate, crop cover, cultivating tillage, and manual weed control), and two herbicides (S-metolachlor and linuron) were also significant. Variation partitioning demonstrated the dominance of environmental factors, and it also showed that non-chemical management practices accounted for five times more variance than herbicides. Within non-chemical management, the relative impact of cultural variables was nearly five times larger than that of mechanical weed management. Among the abundant weeds, Chenopodium polyspermum and Ambrosia artemisiifolia were positively associated with precipitation, Datura stramonium and Hibiscus trionum correlated with higher temperature, and Chenopodium album favoured larger potassium content of the soil. High seeding rate and crop cover suppressed Amaranthus retroflexus, cultivating tillage reduced Ambrosia artemisiifolia and Setaria pumila, while conspicuous tall weeds like Abutilon theophrasti and Chenopodium album were most vulnerable to manual weed control. Although the short stature of pumpkin with its poor weed-suppressive ability could unfavourably influence the results of some cultural practices, our findings suggest that the weed vegetation of oil pumpkin fields can be efficiently managed also with environmentally benign methods.

Historical transportation infrastructures (HTIs) like railways and bridges are essential to our cultural heritage. However, the preservation and enhancement of these structures pose significant challenges due to their complex nature and the need for modern upgrades. Historic building information modeling (HBIM) has emerged as a solution, facilitating the documentation, restoration, and maintenance of historic transportation assets. The purpose of the proposed work is to provide a systematic review of research findings on the application of HBIM in historic transportation infrastructure, highlighting its role in capturing intricate architectural details and supporting decision making for preservation efforts. A series of case studies in which HBIM has been instrumental in preserving historic transportation infrastructure are investigated and analyzed using a comprehensive literature review method. Furthermore, future directions in HBIM research are proposed, identifying potential applications and recommending areas for further investigation. Additionally, this paper suggests HBIM’s potential to balance modernization demands with the conservation needs of historic transportation infrastructure, providing policymakers and stakeholders with insightful strategies for sustainable heritage management.

Metaheuristic algorithms are well-researched and popular techniques in the field of optimization, which can solve complex tasks with a large number of instances with acceptable quality. They are extremely problem- and parameter-sensitive methods, so the exact definition of the necessary data and the testing of the appropriate parameters fundamentally determine the efficiency and performance of an algorithm. This is a time-consuming and expensive task. In many cases, when applying a metaheuristic, it works properly with the variables of a given task and there is no specific interval where a given algorithm can still be effective. To increase efficiency and reduce costs, the authors defined a general parameter definition by applying the Ant Colony Optimization algorithm applicable to the simple Traveling Salesman Problem with the number of cities n=50, where for values of 30 ≤ n ≤ 50, the defined parameter setting structure can be properly applied based on the results. The proposed parameter setting structure can work effectively not only for the task presented in the paper, but also for any similar task within the defined interval. In the case of tasks of a similar size, it is not necessary to experiment with the parameters to achieve the appropriate result, thereby reducing the optimization time and improving efficiency. The presentation of the set parameter setting scenarios and the obtained results all contribute to reducing the optimization time in the field of logistics as well. All of this can also help facilitate the practical application of metaheuristics in solving NP-hard tasks.

Background The 2023 iteration of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) estimated prevalence, incidence, and health burden for 375 diseases and injuries, including 12 mental disorders. We assess past, current, and emerging trends in the prevalence and burden of mental disorders across sexes and age groups, for 21 regions, 204 countries and territories, and by Socio-demographic Index (SDI) quintile, from 1990 to 2023. Methods Mental disorders included in GBD 2023 were anxiety disorders, major depressive disorder, dysthymia, bipolar disorder, schizophrenia, autism spectrum disorders, conduct disorder, attention-deficit hyperactivity disorder, anorexia nervosa, bulimia nervosa, idiopathic developmental intellectual disability, and a residual category of other mental disorders. A literature review identified epidemiological data for each disorder. These were analysed via a Bayesian meta-regression to estimate prevalence by disorder, sex, age, location, and year. Disorder-specific prevalence was multiplied by disability weights representing the severity of health loss associated with each disorder to estimate years lived with disability (YLDs). Deaths due to anorexia nervosa were assessed with a Cause of Death Ensemble modelling strategy to estimate deaths by sex, age, location, and year, and then multiplied by the standard life expectancy at age of death to estimate years of life lost (YLLs). YLDs equalled disability-adjusted life-years (DALYs) for all mental disorders except anorexia nervosa (the only mental disorder considered as an underlying cause of death in GBD), for which DALYs represented the sum of YLDs and YLLs. We presented prevalence, deaths, YLDs, YLLs, and DALYs as counts, age-specific rates per 100 000 population, and age-standardised rates per 100 000 population. Findings We estimated 1·17 billion (95% uncertainty interval 1·06–1·31) prevalent cases of mental disorders globally in 2023, equivalent to an age-standardised prevalence rate of 14 210·7 cases (12 849·5–15 940·1) per 100 000 population. These estimates represented a 95·5% (75·0–121·2) increase in prevalent cases and 24·2% (11·4–41·4) increase in age-standardised prevalence rate between 1990 and 2023. All mental disorders showed increases in prevalent cases between 1990 and 2023, while notable increases were seen in age-standardised prevalence rates for anxiety disorders, major depressive disorder, dysthymia, anorexia nervosa, bulimia nervosa, schizophrenia, and conduct disorder. There were an estimated 171 million (127–228) DALYs due to mental disorders globally across sex and age in 2023, equivalent to an age-standardised DALY rate of 2070·5 DALYs (1519·1–2750·5) per 100 000 population. Mental disorders contributed to 6·1% (4·8–7·6) of all-cause DALYs in 2023, making them the fifth leading cause of global DALYs (up from 12th in 1990). DALYs were almost entirely composed of YLDs. Mental disorders were the leading cause of YLDs in 2023 (up from second in 1990), explaining 17·3% (14·8–20·6) of all-cause global YLDs. Leading causes of mental disorder DALYs were anxiety disorders (ranked 11th among the 304 diseases and injuries at Level 4 of the GBD cause hierarchy), major depressive disorder (15th), and schizophrenia (41st). Globally in 2023, mental disorder age-standardised DALY rates were higher among females (2239·6 [1643·7–3014·1] per 100 000) than among males (1900·2 [1399·8–2510·8] per 100 000), and peaked in the 15–19 years age group (2617·3 [1850·6–3696·8] per 100 000). All locations showed increased mental disorder DALY rates in 2023 compared with 1990, ranging across countries and territories from 1302·4 (952·7–1683·7) per 100 000 in Viet Nam to 3555·8 (2661·9–4715·0) per 100 000 in the Netherlands. Across SDI quintiles, DALY rates ranged from 1853·0 (1352·1–2469·3) per 100 000 for middle SDI to 2184·1 (1606·1–2890·3) per 100 000 for high SDI. Interpretation A significant health burden was imposed by mental disorders in all countries and territories in 2023, irrespective of the health resources available. In some instances, this burden has increased over time and is unevenly distributed across populations. Stronger surveillance systems, particularly in low-income and middle-income countries, are required. Additionally, we need more coordinated and inclusive policies to reduce the burden through early treatment and prevention, tailored to sex and age differences across locations. Responding to the mental health needs of our global population, especially those most vulnerable, is an obligation, not a choice. Funding Gates Foundation, Queensland Health, and University of Queensland.

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The urban-type residential houses built before World War Two represent a large part of the built environment in Hungary. Due to their physical condition and low energy-efficiency the retrofit of these buildings is very much advisable nowadays. In this paper we propose an approach based on fuzzy signatures and state machines, that helps decision support for determining the renovation scenario concerning necessity, cost efficiency and quality. Using the knowledge obtained from diagnostic surveys done during the previous decades by architect experts, and technical guides and the available database of contractors billing, a protocol for the preparation for optimized refurbishment is proposed, based on the concept of an extended fuzzy state machine model. In this combined model the theoretical concepts of finite-state machine and fuzzy state machine, and also the principles of fuzzy signatures are applied. © Springer International Publishing Switzerland 2014.

The paper presents a parallel approach for the efficient solution of a one-dimensional and a two-dimensional problem by parallel finite element method. These problems are case studies. The non-overlapping domain decomposition method has been used to cut the problem into subregions or also called sub-domains, and it reduces the large mass matrix into smaller parts. The independent sub-domains, and the assembling of these equation systems can be handled by the independent processors of a supercomputer, i.e. in a parallel way. The execution time and speedup of parallel finite element method have been compared to the serial one.