Dealing with the islanded operation of a microgrid (MG), the micro sources must cooperate autonomously to regulate the voltage and frequency of the local power grid. Droop controller-based primary control is a method typically used to self-regulate voltage and frequency. The first problem of the droop method is that in a steady state, the microgrid's frequency and voltage deviate from their nominal values. The second concerns the power-sharing issue related to mismatched power line impedances between Distribution Generators (DGs) and MGs. A Secondary Control Unit (SCU) must be used as a high-level controller for droop-based primary control to address the first problem. This paper proposed a decentralized SCU scheme to deal with this issue using optimized PI controllers based on a Genetic Algorithm (GA) and Artificial Neural Networks (ANNs). The GA provides the appropriate adjustment parameters for all adopted PI controllers in the primary control-based voltage and current control loops and SCU-based voltage and frequency loops. ANNs are additionally activated in SCUs to provide precise online control parameter modification. In the proposed control structure, a virtual impedance method is adopted in the primary control scheme to address the power-sharing problem of parallel DGs. Further, in this paper, one of the main objectives includes electricity transmission over long distances using Low-Voltage DC Transmission (LVDCT) systems to reduce power losses and eradicate reactive power problems. Voltage Source Inverters (VSIs) are adopted to convert the DC electrical energy into AC near the consumer loads. The simulation results illustrated the feasibility of the proposed solutions in restoring voltage and frequency deviations, reducing line losses, as well as achieving active and reactive power sharing among the DGs connected to the MG.

• Keywords
• artificial neural network, distribution generators, genetic algorithm, microgrid, power sharing, secondary control, virtual impedance,
• MeSH
• Electric Impedance MeSH
• Electricity * MeSH
• Neural Networks, Computer MeSH
• Computer Simulation MeSH
• Electric Power Supplies * MeSH
• Publication type
• Journal Article MeSH

Access to clean water remains a critical global challenge, particularly in under-resourced regions. This study introduces an autonomous water treatment system leveraging Industry 4.0 technologies, including advanced smart sensors, real-time monitoring, and automation. The system employs a multi-stage filtration process-mechanical, chemical, and UV sterilization-to treat water with varying contamination levels. Smart sensors play a pivotal role in ensuring precise control and adaptability across the entire process. Experimental validation was conducted on three water types: pond, river, and artificially contaminated water. Results revealed significant reductions in key contaminants such as PPM, pH, and electrical conductivity, achieving water quality standards set by the WHO. Statistical analyses confirmed the system's reliability and adaptability under diverse conditions. These findings underscore the potential of smart, sensor-integrated, decentralized water treatment systems to effectively address global water security challenges. Future research could focus on scalability, renewable energy integration, and long-term operational durability to enhance applicability in remote areas.

• Keywords
• Industry 4.0, autonomous water treatment, decentralized solutions, smart sensors, water quality,
• Publication type
• Journal Article MeSH

The paper is focused on the identification, control design, and experimental verification of a two-input two-output hot-air laboratory apparatus representing a small-scale version of appliances widely used in the industry. A decentralized multivariable controller design is proposed, satisfying control-loop decoupling and measurable disturbance rejection. The proposed inverted or equivalent noninverted decoupling controllers serve for the rejection of cross-interactions in controlled loops, whereas open-loop antidisturbance members satisfy the absolute invariance to the disturbances. Explicit controller-structure design formulae are derived, and their equivalence to other decoupling schemes is proven. Three tuning rules are used to set primary controller parameters, which are further discretized. All the control responses are simulated in the Matlab/Simulink environment. In the experimental part, two data-acquisition, communication, and control interfaces are set up. Namely, a programmable logic controller and a computer equipped with the peripheral component interconnect card commonly used in industrial practice are implemented. A simple supervisory control and data acquisition human-machine interface via the Control Web environment is developed. The laboratory experiments prove better temperature control performance measured by integral criteria by 35.3%, less energy consumption by up to 6%, and control effort of mechanical actuator parts by up to 17.1% for our method compared to the coupled or disturbance-ignoring design in practice. It was also observed that the use of a programmable logic controller gives better performance measures for both temperature and air-flow control.

• Publication type
• Journal Article MeSH

Changes in spontaneous motility were studied in 11- to 19-day-old chick embryos after acute and chronic decapitation. Chronic decapitation was performed on the 2nd day of incubation, at stage 11--14. Up to the 15th day, acute decapitation merely reduced the frequency of spontaneous movements. In 17-day embryos it was followed by typical spinal shock, with transient complete disappearance of spontaneous movements of the embryo. The duration of spontaneous motor depression was proportional to the age of the embryo. After the 15th day of incubation, spinal decentralization changed continuous to discontinuous motor activity, with spontaneous paroxysms of high amplitude movements followed by long intervals of motor rest. Chronic decapitation was manifested, from the 15th day of incubation, in significant reduction of spontaneous movement frequency and again in discontinuous motility. A microscopic anatomical analysis of the spinal cord of decapitated embryos showed defects of the tracts in the lateral and ventromedial area of the cord and degenerative injury of the motoneurones in the ventral horns. Supraspinal control thus does not begin to act effectively on the spontaneous motility of chick embryos until about the 15th day of incubation. Supraspinal factors modulate both the frequency and the rhythm of spontaneous movements and are evidently also indispensable for normal morphological development of the spinal cord motor apparatus of chick embryos.

• MeSH
• Time Factors MeSH
• Chick Embryo MeSH
• Spinal Cord physiology   MeSH
• Motor Neurons physiology   MeSH
• Movement * MeSH
• Animals MeSH
• Check Tag
• Chick Embryo MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

This article proposes Persistence Administered Collective Navigation (PACNav) as an approach for achieving the decentralized collective navigation of unmanned aerial vehicle (UAV) swarms. The technique is based on the flocking and collective navigation behavior observed in natural swarms, such as cattle herds, bird flocks, and even large groups of humans. As global and concurrent information of all swarm members is not available in natural swarms, these systems use local observations to achieve the desired behavior. Similarly, PACNav relies only on local observations of the relative positions of UAVs, making it suitable for large swarms deprived of communication capabilities and external localization systems. We introduce the novel concepts ofpath persistenceandpath similaritythat allow each swarm member to analyze the motion of other members in order to determine its own future motion. PACNav is based on two main principles: (a) UAVs with little variation in motion direction have highpath persistence, and are considered by other UAVs to be reliable leaders; (b) groups of UAVs that move in a similar direction have highpath similarity, and such groups are assumed to contain a reliable leader. The proposed approach also embeds a reactive collision avoidance mechanism to avoid collisions with swarm members and environmental obstacles. This collision avoidance ensures safety while reducing deviations from the assigned path. Along with several simulated experiments, we present a real-world experiment in a natural forest, showcasing the validity and effectiveness of the proposed collective navigation approach in challenging environments. The source code is released as open-source, making it possible to replicate the obtained results and facilitate the continuation of research by the community.

• Keywords
• decentralized control, multi-robot systems, relative localization, swarm robotics, unmanned aerial vehicles,
• MeSH
• Unmanned Aerial Devices MeSH
• Communication MeSH
• Aircraft * MeSH
• Humans MeSH
• Robotics * MeSH
• Cattle MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Cattle MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

The effect of chronic administration of phenobarbital (from the 4th to the 16th day of incubation) combined with chronic spinal decentralization (decapitation at stage 11-13) on the development of spontaneous motor activity (recorded on the 17th day of incubation) was studied in 4 to 17-day-old chick embryos. 1. Combination of the two experimental treatments led to summation of their negative effect on development; spontaneous motor activity fell to 15.2% of the control value (to 26.9% after the isolated administration of phenobarbital and to 30.5% after isolated decapitation). 2. Metrazol activation of motor activity (100 mg/kg egg weight) after combination of the two factors was relatively no different from the results after their isolated use. 3. The acute administration of GABA (100 mg/kg e.w.) likewise induced relatively the same depression of spontaneous motility as after isolated chronic decapitation and the isolated chronic administration of phenobarbital. The results confirm the hypothesis of the significance of spontaneous activity of the spinal motoneurones for their survival and their actual functional development during the embryonic period.

• MeSH
• Central Nervous System embryology   physiology   MeSH
• Phenobarbital pharmacology   MeSH
• gamma-Aminobutyric Acid pharmacology   MeSH
• Chick Embryo drug effects   physiology   MeSH
• Motor Neurons physiology   MeSH
• Pentylenetetrazole pharmacology   MeSH
• Motor Activity drug effects   physiology   MeSH
• Animals MeSH
• Check Tag
• Chick Embryo drug effects   physiology   MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Phenobarbital MeSH
• gamma-Aminobutyric Acid MeSH
• Pentylenetetrazole MeSH

This article presents a unique framework for deploying decentralized and infrastructure-independent swarms of homogeneous aerial vehicles in the real world without explicit communication. This is a requirement in swarm research, which anticipates that global knowledge and communication will not scale well with the number of robots. The system architecture proposed in this article employs the UVDAR technique to directly perceive the local neighborhood for direct mutual localization of swarm members. The technique allows for decentralization and high scalability of swarm systems, such as can be observed in fish schools, bird flocks, or cattle herds. The bio-inspired swarming model that has been developed is suited for real-world deployment of large particle groups in outdoor and indoor environments with obstacles. The collective behavior of the model emerges from a set of local rules based on direct observation of the neighborhood using onboard sensors only. The model is scalable, requires only local perception of agents and the environment, and requires no communication among the agents. Apart from simulated scenarios, the performance and usability of the entire framework is analyzed in several real-world experiments with a fully-decentralized swarm of UAV deployed in outdoor conditions. To the best of our knowledge, these experiments are the first deployment of decentralized bio-inspired compact swarms of UAV without the use of a communication network or shared absolute localization. The entire system is available as open-source at https://github.com/ctu-mrs.

• Keywords
• Distributed Control, Relative Localization, Swarm Robotics, Unmanned Aerial Vehicle,
• Publication type
• Journal Article MeSH

OBJECTIVE: To give an overview of available internal tobacco industry documents on the transnational tobacco companies' (TTCs) efforts to enter the new market of the emerging democracy of Hungary and how it developed allies in its efforts at resisting tobacco control regulations. METHOD: Internal tobacco industry documents relevant to Hungary, available on the World Wide Web, were searched between 26 July and 30 November 2001. Documents on the identification of Central and Eastern Europe (CEE) as a great market potential have been reviewed; another set of reviewed documents are of particular relevance to Hungary, as they indicate who the main partners of the industry are. CONCLUSIONS: TTCs not only invaded the markets of the fragile new CEE democracies by making their product widely available, but also introduced sophisticated lobbying and marketing tactics. TTCs will try to shape the country's regulatory framework in a manner to help increase their profits. The fiercer the reaction of TTCs against a planned regulatory measure is, the more impact on the health of the population could be expected from the introduction and enforcement of that measure.

• MeSH
• Democracy MeSH
• Documentation MeSH
• Internationality MeSH
• Internet MeSH
• Humans MeSH
• Marketing * MeSH
• Politics MeSH
• Social Control Policies MeSH
• Tobacco Industry organization & administration   trends   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Research Support, U.S. Gov't, P.H.S. MeSH
• Geographicals
• Hungary MeSH

Swarm behaviors offer scalability and robustness to failure through a decentralized and distributed design. When designing coherent group motion as in swarm flocking, virtual potential functions are a widely used mechanism to ensure the aforementioned properties. However, arbitrating through different virtual potential sources in real-time has proven to be difficult. Such arbitration is often affected by fine tuning of the control parameters used to select among the different sources and by manually set cut-offs used to achieve a balance between stability and velocity. A reliance on parameter tuning makes these methods not ideal for field operations of aerial drones which are characterized by fast non-linear dynamics hindering the stability of potential functions designed for slower dynamics. A situation that is further exacerbated by parameters that are fine-tuned in the lab is often not appropriate to achieve satisfying performances on the field. In this work, we investigate the problem of dynamic tuning of local interactions in a swarm of aerial vehicles with the objective of tackling the stability-velocity trade-off. We let the focal agent autonomously and adaptively decide which source of local information to prioritize and at which degree-for example, which neighbor interaction or goal direction. The main novelty of the proposed method lies in a Gaussian kernel used to regulate the importance of each element in the swarm scheme. Each agent in the swarm relies on such a mechanism at every algorithmic iteration and uses it to tune the final output velocities. We show that the presented approach can achieve cohesive flocking while at the same time navigating through a set of way-points at speed. In addition, the proposed method allows to achieve other desired field properties such as automatic group splitting and joining over long distances. The aforementioned properties have been empirically proven by an extensive set of simulated and field experiments, in communication-full and communication-less scenarios. Moreover, the presented approach has been proven to be robust to failures, intermittent communication, and noisy perceptions.

• Keywords
• field experiments and simulations, flocking, swarm (methodology), swarm robot control, unmanned aerial vehicle,
• Publication type
• Journal Article MeSH

A well-established political economic literature has shown as multi-level governance affects the inefficiency of public expenditures. Yet, this expectation has not been empirically tested on health expenditures. We provide a political economy interpretation of the variation in the prices of 6 obstetric DRGs using Italy as a case study. Italy offers a unique institutional setting since its 21 regional governments can decide whether to adopt the national DRG system or to adjust/waive it. We investigate whether the composition and characteristics of regional governments do matter for the average DRG level and, if so, why. To address both questions, we first use a panel fixed effects model exploiting the results of 66 elections between 2000 and 2013 (i.e., 294 obs) to estimate the link between DRGs and the composition and characteristics of regional governments. Second, we investigate these results exploiting the implementation of a budget constraint policy through a difference-in-differences framework. The incidence of physicians in the regional government explains the variation of DRGs with low technological intensity, such as normal newborn, but not of those with high technological intensity, as severely premature newborn. We also observe a decrease in the average levels of DRGs after the budget constraint implementation, but the magnitude of this decrease depends primarily on the presence of physicians among politicians and the political alignment between the regional and the national government. To understand which kind of role the relevance of the political components plays (i.e., waste vs. better defined DRGs), we check whether any of the considered political economy variables have a positive impact on the quality of regional obstetric systems finding no effect. These results are a first evidence that a system of standardized prices, such as the DRGs, is not immune to political pressures.

• Keywords
• Budget cuts, DRG, Health care deficits, Health care spending, Italy, Politicians, Regional governments,
• MeSH
• Healthcare Financing MeSH
• Diagnosis-Related Groups economics   trends   MeSH
• Humans MeSH
• Politics * MeSH
• Budgets statistics & numerical data   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Italy MeSH