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Share of renewable energy sources increased rapidly over last two decades primary as wind and solar power plants. Their increase was driven by governmental subsidies and priority access and dispatch regarding conventional units. Wind and solar power plants are inflexible sources because their generation depends on exterior, weather conditions and they cannot be controlled as conventional units. This paper will define term power system flexibility and provide an insight into flexibility of conventional and modern power systems. Detailed mathematical model of power system and all its components has been created and explained. Modeling has been executed as mixed integer linear program using Fico Xpress optimization suite. Using those models, flexibility analyses of power systems with different renewable energy sources share has been conducted

Objective We aimed to compare the cellular composition of bronchoalveolar lavage (BAL) fluids in children with chronic unexplained cough (group 1) and severely neurologically impaired children with chronic or recurrent respiratory problems (group 2) with the BAL cytology of children without pulmonary or systemic diseases (group 3). Methods Bronchoscopy with BAL fluid analysis was performed in all subjects. Children with respiratory symptoms underwent 24-hour multichannel intraluminal impedance monitoring. Results A significant difference was found between the groups in the total number of cells in BAL fluid cytology (191 [range, 24–12,747], 747 [range, 53–13,000], and 105 [range, 41–233] cells/μL, P = .015), in the percentage of neutrophils (21.2 [SD = 32.4], 49.4 [SD = 36.6], and 3.6 [SD = 2.4], P < .001), and in the percentage of lipid-laden macrophages (10.3 [SD = 11.4], 13.7 [SD = 15.8] and 0.44 [SD = 1.0], P < .001). Conclusion The BAL fluid cytology provides useful data for determining the cause of chronic unexplained cough and chronic or recurrent respiratory problems in severely neurologically impaired children.

Tuberculous trochanteric bursitis (TTB) is an extremely rare form of extrapulmonary tuberculosis. Due to a low clinical suspicion and poor collaboration among medical professionals, the diagnosis of TTB can be often delayed. In this report, we describe a case of neglected TTB in an adolescent girl that initially presented with right thigh swelling and fluctuance. The patient underwent repeated unsuccessful surgical treatment; however, dull pain and periodic wound drainage remained for eight years. Complete excision of fistula and trochanteric bursa and one year of oral antituberculous drug therapy led to complete recovery. This case report highlights tuberculosis as a diagnostic challenge, when rare localizations are affected. In addition, this report addresses several diagnostic pitfalls and reviews the literature regarding TTB in adolescent patients. Orthopedic surgeons need to consider TTB, when swelling, fluctuance or repeated wound drainage are present on the thigh.

According to International Maritime Organization, emissions coming from global shipping are expected to increase 50% to 250% by the year 2050. This concern led to the introduction of various regulations that aims to encourage ship owners and builders to explore innovative renewable technologies. The main focus of this article is on wind-assisted ship propulsion technologies, as a complement to ship propulsion, such as rigid sail, soft sail, wing sail, kite, and Flettner rotor. These technologies are not widely accepted because ship owners have doubts due to the lack of real-life results and their implementation and efficiency greatly depends on ship design and purpose. This article shows the progress in the field of wind-assisted ship propulsion in the last 15 years which proved the concept as they have the potential to reduce fuel consumption, thus emissions, by double digits. The conclusion is drawn, from fuel savings percentages, that rotor and soft sails technologies have great potential in the future of the shipping industry.

The weakly hard real-time system model is used for describing the real-time systems that allow occasional violations of real-time timing constraints. These systems include real-time control systems, multimedia systems, and communication systems. In some approaches that deal with mitigating the system overload in real-time systems with periodic tasks, namely job-skipping algorithms, the constraints defined by the weakly hard real-time model are used as a mechanism for defining the pattern of task instances (jobs) that may be skipped in order to reduce the system load. The performance of these algorithms is usually evaluated with respect to the quality of service metric, which depends on the number of skipped jobs. In this work, we investigate the possibility of using genetic programming in the automated synthesis of scheduling heuristics for optimizing skipping patterns in order to increase the average quality of service in comparison with the conventional job-skipping algorithms. Using genetic programming to automatically synthesize heuristics allows for an easy and quick design of novel heuristics for various problem types and optimization criteria. We present two different approaches for implementing the proposed method. The first approach is to encapsulate the evolved heuristics into job-skipping algorithms known from the literature, namely Red Tasks as Late as Possible (RLP) and Blue When Possible (BWP). The idea of the second approach is to employ the evolved heuristics as standalone job-skipping algorithms. The results show an improvement of up to 15% in comparison with the state-of-the-art algorithms. The novel methods described in this work present a significant upgrade of the standard job-skipping algorithms as they provide a notable improvement in terms of quality of service while ensuring the fulfillment of weakly hard constraints. Moreover, the presented methods are computationally efficient and are therefore suitable for implementation on real-time operating systems, which is not the case with similar methods based on optimization techniques.

Battery-powered electric vehicles are gradually expanding their market outside of the typical public and private transportation sector. A good example is a growing demand for electrification of special-purpose vehicles such as compact urban vacuum sweeper trucks. These vehicles are characterized by low production numbers and specific limitations such as restricted volume for battery placement, specific working conditions, requirement to supply electro- hydraulic systems, etc. Therefore, the selection of optimal battery cell and identification of its required characteristics is not a straightforward task. This article addresses this by presenting a methodology for selecting optimal battery cell for compact urban vacuum sweepers. A laboratory testing procedure is established to measure electric and heating characteristics of candidate battery types and battery producers. After evaluation of the experimental test results using the Analytic Hierarchy Process (AHP), the most appropriate battery cell is selected. The experimental tests and the presented AHP methodology prove that battery cell selection for a specific purpose based solely on manufacturers' datasheet can result in a sub-optimal decision.

In this paper we point to some errors in recent paper by Asyaban et al. in which they devise an exact schedulability test. These errors are critical for the correct operation of the algorithm and they should be corrected.

Shift of the power system generation from the fossil to the variable renewables prompted the system operators to search for new sources of flexibility, i.e., new reserve providers. With the introduction of electric vehicles, smart charging emerged as one of the promising solutions. However, electric vehicle aggregators face the uncertainty both on the reserve activation and the electric vehicle availability. These uncertainties can have a detrimental effect on both the aggregators' profitability and users' comfort. State-of-the art literature mostly neglects the reserve activation or it's uncertainty. On top of that, they rarely model European markets which are different that those commonly addressed in the literature. This paper introduces a new method for modeling the reserve activation uncertainty, also termed as balancing energy procurement in the European context, based on the real historic data from the European power system. Three electric vehicle scheduling models were designed and tested: the deterministic, the stochastic and the robust. The results demonstrate that the current deterministic approaches inaccurately represent the activation uncertainty and that the proposed models that consider uncertainty, both the stochastic and the robust, substantially improve the results. Additionally, the sensitivity analysis for the robust model was performed and it demonstrates how a decision-maker can choose its level of conservativeness, portraying its risk- awareness.

Integration of renewable energy sources as one of the pillars of the power system decarbonization efforts is making a significant progress. However, large shares of renewables require additional flexibility to keep the system stable. Battery storage was identified as one of the solutions to restore the grid balance in short timeframes, from day-ahead to real time. Currently, the research community is trying to find an adequate technology for longer duration energy storage. Hydrogen, as an energy carrier, appears as a good choice for such task. Apart from hydrogen energy storage potential, it can also be used to implement power-to-gas technology able to mitigate renewable energy curtailment through the process of electrolysis. The produced hydrogen gas can be either used to partially decarbonize the natural gas grids or simply sold as hydrogen fuel. The main novelty of this paper is the creation of a mathematical model of a renewable power plant coupled with a battery storage and a hydrogen facility for trading in three day-ahead energy markets, i.e. electricity, natural gas and hydrogen, plus in the power balancing market subject to the imbalance settlement mechanism. This approach enables a long-term profitability analysis of different renewable, battery and hydrogen architectures (hydrogen energy storage, power-to-gas and their combination) and their participation in different markets. The results indicate that the battery energy storage provides balancing services to the transmission system operator almost exclusively, while it never provides balancing for its own imbalance needs, since this option is less financially attractive. The electrolyzer and the fuel cell operate at least one third of the year, depending on the observed case, and often provide a reserve. When considering the hydrogen market, the electrolyzer operates almost the entire year due to lucrative hydrogen prices. Both the battery storage and the hydrogen tank perform arbitrage in the day-ahead market, where the battery optimizes its operation on an hourly basis (short-term) and the hydrogen tank on a daily basis (medium- to long-term).

Background: Impaired lung function has been detected in up to 65% of all childhood cancer survivors. It is often caused by exposure to radiation therapy and various chemotherapeutics. The first cytotoxic drug ever identified as a causative agent of lung injury was busulfan, reported in the early 1960s. Signs and symptoms of busulfan lung are nonspecific and it is therefore difficult to differentiate the condition from pulmonary impairment caused by other pulmotoxic agents, infections, pulmonary metastases, graft- versus- host disease, or other noninfectious post- transplant complications involving the lungs. Methods: A case example is provided to illustrate the difficulties in management of busulfan-induced lung injury in children. A retrospective review of cases of busulfan- induced lung injury indexed in PubMed until March 2019 was performed. Inclusion criteria for articles was available in full text in English. Results: Impaired lung function caused by busulfan may become an increasing problem for young survivors. Conclusion: Newly developed dyspnea or subclinical damage detected on pulmonary function tests, indicating primarily restrictive disease, should always arouse suspicion of busulfan-induced lung injury in a child conditioned with busulfan, especially after excluding other leading culprits of pulmonary damage affecting oncology patients.

There is an increasing number of experimental, genetic and clinical evidence of atopic dermatitis expression as a pre-condition for later development of other atopic diseases such as asthma, food allergy and allergic rhinitis. Atopic dermatitis is a heterogeneous, recurrent childhood disease, also present in the adult age. It is increasingly attributed to systemic features and is characterized by immunological and skin barrier integrity and function dysregulation. To maintain the protective function of the skin barrier, in particular the maintenance of pH, hydration and antimicrobial functions, the filaggrin, among others, plays a significant role. Filaggrin is a multifunctional, histidine-rich, insoluble protein. The lack of filaggrin is associated with various cutaneous (e.g. ichthyosis vulgaris, allergic contact dermatitis) and non-cutaneous (e.g. diabetes, inflammatory conditions of the gastrointestinal tract) diseases and may be a result of genetic, immunological factors combined with environmental factors. In this review we summarised (emphasized) recent findings in understanding the role of filaggrin in atopic dermatitis and other diseases, participants in the atopic march.

The aim of this study was to explore the differences in nutritional status and dietary intakes in 12∼17 yearold children living in urban (Zagreb) and the rural (Sinj and Drniš) area of Croatia. A validated food frequency questionnaire was used to assess dietary intake. For each participant, body weight and body height were measured and bioelectrical impedance was used to estimate the body fat percentage. There was an overall of 310 children included: 105 (33.9%) from urban area and 205 (66.1%) from rural area ; 191 (61.6%) were female with a mean age 14.9 (range 12∼17) years. When adjusted for age and gender, there was no statistically significant difference in body mass index for age Z-scores between urban and rural parts (0.23±0.07 vs. 0.30±1.15 ; P=0.650) or in average daily energy intake (2, 479.2±1, 111.2 kcal vs. 2, 338.2±920.2 kcal ; P=0.702). There was a statistically significant difference in nutritional status between genders, with a higher percentage of boys being overweight or obese compared to girls. When combined, ‘Fast food’ and ‘Snacks’ were major contributors to the total energy intake for both areas. The mean contribution of ‘Fast food’ to total energy intake was significantly higher in the urban area. The prevalence of obesity among Croatian children is high and unrelated to the urban/rural setting, which could be partially explained by the high intake of ‘Fast food’ and ‘Snacks’.

Ancillary services used for active power balancing are called balancing services or operating reserves and their provision is vital for maintaining power system frequency at the nominal value. In a deregulated environment, where generation is unbundled from transmission and distribution operations, independently owned generating companies may elect to provide operating reserves. However, it is not easy to calculate the exact cost of reserve provision and, therefore, bid for it accurately. Although the cost efficiency of reserve provision can be improved by co-optimising energy and reserve markets, generating companies can still encounter monetary losses caused by the provision of reserve. Currently, these losses are compensated based on ex-post calculations. Hence, current energy and reserve prices do not adequately factor in the ex-post compensation caused by reserve provision. This study proposes an energy and reserve co-optimisation with an explicit consideration of two compensation mechanisms, i.e. lost opportunity and uplift payments. The problem is structured as a bilevel model. The upper level is a mixed-integer unit commitment problem and the lower level is a continuous economic dispatch problem. The case study shows that the proposed model increases market efficiency.

Purpose: Data on the relationship between gastroesophageal reflux (GER) and brief resolved unexplained events (BRUE) in infants is scarce. The aim of this study was to identify the characteristics of combined multichannel intraluminal impedance-pH (MII-pH) monitoring in infants who have experienced BRUE. Methods: We conducted a prospective study of infants who were hospitalized on account of BRUE and required 24- hour MII-pH monitoring. Results: Twenty-one infants (mean age, 4.7 months ; range, 0.9–8.9 months ; male/female, 11/10) participated in this study. BRUE symptoms associated with GER were found in 10 infants (47.6%). Based on the RI on pH-metry alone, only 7 (33.3%) infants were diagnosed with GERD. More than 100 GER episodes detected by MII were found in 10 (47.6%) infants. Nineteen percent of infants were diagnosed with GERD based on both pH and MII. Conclusion: Both acid and non-acid reflux seem to play a significant role in the pathogenesis of GER- related BRUE in infants.

Automatic Identification Systems (AIS) and Automatic Radar Plotting Aids (ARPA) are commonly used to detect targets for collision avoidance. However, AIS cannot detect targets without AIS transmitters and ARPA has limitations due to blind sector and small targets may not be detected. Advances in computer performance and video-based detection generated much interest in developing intelligent video surveillance systems to achieve autonomous navigation. To develop a reliable collision avoidance system, we propose the use of a visual camera for real-time object detection and target tracking. Moreover, the system should follow the International Regulations for Preventing Collisions at Sea (COLREGs) to avoid catastrophic accidents. In this paper only a part of the system is presented. For real-time object detection, the You Only Look Once (YOLO) ver. 3 convolutional neural network is used, and the target tracking filter based on a Kalman filter with built-in estimated relative position and velocity.

One of the key elements of Directive 2019/944 from the latest EU Energy Legislative package was the introduction of dynamic electricity pricing. This incentive for consumers to change their consumption patterns is supposed to be beneficial for many power system entities, from system operators to suppliers and RES owners. On the other hand, there are some indications that such pricing schemes can be detrimental for specific consumer groups, especially vulnerable household types. The aim of this paper is to investigate the benefits for a household to switch between different electricity pricing tariffs and start participating in an implicit demand response program. To answer this question, we use a detailed household model that includes all common appliances, as well as behind-the-meter electricity generation, energy storage and flexible loads, e.g. electric vehicle charger. The household is represented by a mixed-integer linear programming model. We take into account load patterns caused by different consumption habits of household members, different sets of appliances that can can be found in a household and different levels of household automation.

Real-time operating systems typically have support for static task scheduling algorithms only. However, real-time applications often require dynamic scheduling algorithms in order to meet their timing constraints. Furthermore, in the case of overloaded conditions, i.e., scenarios when there is no feasible schedule, the total tardiness of real-time tasks can be significantly decreased by using a custom dynamic priority assignment. This paper presents a method for integrating custom scheduling heuristics to an open source real-time operating system (FreeRTOS). The FreeRTOS task management subsystem was modified in order to support dynamic task priority assignment. The method was evaluated by simulating the execution of periodic preemptable task sets and the results were compared with the default FreeRTOS scheduler with respect to the total weighted tardiness and weighted number of late jobs measure. The system performance in both underloaded and overloaded conditions was improved by using custom dynamic scheduling policies.

While the latest European energy regulations emphasise the active power system participation of the household level end-users, the large industrial facilities are still not fully exploiting all the market opportunities to decrease their costs and become more competitive. Significant cost reduction can be achieved by offering flexibility services in the electricity market. This is especially valid in the case when the industrial consumers are multi-energy hubs where shifting and optimising usage of input energy vectors creates additional opportunities. Research gaps were identified and a price responsive demand response model for a multi- energy industry facility under uncertainty was developed. The uncertainty aspects are modelled both by the robust optimisation and by the two- stage stochastic optimisation. Additionally, we develop a linear energy flow-based model of an industrial steam system which better encompasses losses and makes the model more realistic. The model is validated on a real-world case of a multi-energy industry facility and the results indicate that cost savings of up to 18 % can be achieved compared to the passive and deterministic, mass flow-based business-as-usual behaviour.

Integration of renewable energy sources accompanied with decommission of fossil fueled power plants inherently results in lack of power system flexibility. In turn, this reduced flexibility calls for additional balancing services. In parallel to this, the process of transport sector electrification is in place and the large fleets of electric vehicles (EVs) could prove to be one of the solutions for increased power system flexibility needs. If managed adequately, EVs could be able to provide the missing balancing services. In this paper, a model of EV day-ahead market and frequency containment reserve bidding is defined in order to asses the potential challenges that could arise during such service provision. Special attention is given to the EV battery state of energy, since the batteries are energy-limited resources and specific issues may arise both at individual EV and fleet level.

In traditional power systems production always followed consumption, while nowadays consumers are incentivized to take active part in electricity markets. In energy intensive industry large portion of the product cost goes to energy expenses. Thus, optimizing operations based on market signals can create substantial benefits for industrial prosumers. Industries with more than one energy input vector, e.g. electricity and gas, both being bought from their respective day ahead markets are investigated in this paper. The paper introduces enthalpy modeling versus conventional mass flow which increases the scheduling efficiency. Proposed optimization model is based on stochastic mixed integer linear programming where prices of electricity are treated as stochastic process as oppose to deterministic approach usually used. Goal of optimization is to reduce overall energy cost. Also, it must provide bidding strategy for both day-ahead markets. Idea is to reduce market variability by proper device scheduling, utilizing flexibility between energy vectors and behind the meter production of electricity.

Wireless sensor networks based on energy-neutral energy-harvesting nodes have been in the focus of researchers for years as they bring significant benefits regarding the efficiency and the cost of the final product. In this paper, we focus on timing and energy aspects of energy-harvesting sensor node operation. A typical wireless sensor network application enables user to adjust refresh rates of certain measurements which are executed on a sensor node. Energy-aware scheduling of measurements, i.e. task scheduling, is crucial for maintaining target refresh rates demanded by the user. In this paper, we devise an off-line and on-line scheduling approach for energy-aware scheduling of tasks on sensor nodes. Moreover, we show why earlier real-time energy-harvesting models are inadequate in these applications. We evaluated our approach on synthetically generated task sets and initial results show that further research in this direction can bring practical benefits in real-world applications.

SARS-CoV-2 (Severe Acute Respiratory Syndrome Corona Virus 2), a novel virus of the beta coronavirus group RNA viruses, is responsible for a zoonotic disease named COVID-19 (coronavirus disease from 2019). The main receptor through which the virus enters the host cell is angiotensin-converting enzyme 2 (ACE2), known as a multifunctional protein. ACE2 expression has been found in oral and nasal mucosa, lungs, adipose tissue, heart, brain, kidneys, vascular tissue, stomach, liver. Upon entry of the virus into the target host cells, two processes are initiated, the host’s immune response and the infl ammatory cascade. As immune (innate and adaptive) and infl ammatory responses change throughout life both qualitatively and quantitatively, both processes are responsible for varying degrees of disease severity depending on the patient’s age. Short-time experience with SARS-CoV-2 infection has shown that: (i) children and adolescents develop the disease with mild symptoms, mainly on upper respiratory airways; (ii) the disease has a more severe course in adult patients with associated chronic diseases such as cardiovascular and renal diseases, chronic respiratory diseases, diabetes, etc.; and (iii) the most severe, often fatal disease occurs in the elderly, due to more pronounced processes of immunosenescence and infl amm-aging., RSARS-CoV-2 (engl. Severe Acute Respiratory Syndrome Coronavirus 2), novi virus iz skupine RNA betakoronavirusa, odgovoran je za zoonotsku bolest nazvanu COVID-19 (bolest uzrokovana koronavirusom iz 2019.). Glavni receptor pomoću kojega virus ulazi u stanicu domaćina je angiotenzin konvertirajući enzim 2 (ACE2), poznat kao multifunkcionalni protein. Receptor ACE2 prisutan je u oralnoj i nosnoj sluznici, plućima, masnom tkivu, srcu, mozgu, bubrezima, vaskularnom tkivu, želucu, jetri. Nakon ulaska virusa u ciljne stanice domaćina pokreću se dva procesa, imunosni odgovor domaćina i upalna kaskada. Budući da se imunosni (urođeni i stečeni) i upalni odgovori tijekom života mijenjaju u kvalitativnom i kvantitativnom smislu, oba procesa su odgovorna za različit stupanj ozbiljnosti bolesti, ovisno o pacijentovoj dobi. Kratkotrajno iskustvo s infekcijom uzrokovanom virusom SARS-CoV-2 pokazalo je da: (i) djeca i adolescenti razvijaju bolest s blagim simptomima, uglavnom na gornjim dišnim putevima; (ii) bolest ima teži tijek u odraslih bolesnika s pridruženim kroničnim bolestima kao što su kardiovaskularne i bubrežne bolesti, kronične respiratorne bolesti, dijabetes i sl.; (iii) najteži, često fatalni oblik pojavljuje se u starijih osoba zbog izraženijih procesa imunosenescencije i upale pri starenju.

In this paper a novel optimization method called Multi-Objective Ant Lion Optimizer (MOALO) is proposed for tuning synchronous generator excitation controls in multi machine power system. Devices used in excitation control are automatic voltage regulator (AVR) and power system stabilizer (PSS). Two area four machine model (TAFM) is used for observing power system dynamics through several various operating states. In a performance analysis of a proposed algorithm two objective functions are used. First objective function uses integral of time weighted absolute error of rotor speed, voltage and tie line active power data, while second objective function uses mean value of time domain transitional process quality indicators such as overshoot, undershoot and settling time. A proposed algorithm is tested and its performance is compared with performances of two other multi objective swarm intelligence algorithms: Multi- Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Salp Swarm Algorithm (MOSSA). Results are compared and presented as sets of solutions composed in Pareto fronts.

This paper proposes a method to define the value of an emergency service which the microgrid can provide both to the system operator and its own users. This means the microgrid operates as a market-driven grid-tied energy community. However, it also needs to be able to disconnect from the main grid and maintain stable operation in the off-grid regime. To evaluate this, this paper demonstrates the following microgrid models: i) on-grid mixed integer linear programming (MILP) model of a microgrid driven by market signals ; ii) dynamic model of a microgrid during transitioning into off-grid mode. Based on these models, this paper defines constraints that determine monetary value of providing flexibility to the system operator and security of supply to end-users during transition to off-grid mode.