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The objective of this work is to analyze and compare AC microgrid (ACMG) solutions to introduce the topic to new researchers. The methodology used to achieve this goal is a systematic literature review using five questions: (1) How have ACMGs evolved in five years? (2) What are the standards for ACMGs? (3) What are the different schemes for connecting MGs to the utility grid? (4) What are the different control schemes in ACMGs? (5) What is an appropriate way to compare results when working with ACMGs? The articles were published in Q1/Q2 journals as based on either the Scimago Journal Rank (SJR) and/or the Journal Citation Report (JCR) between 2018 and 2022 and were from three databases: (1) Web of Science (WoS), (2) Scopus, and (3) IEEE Xplore. Publications not describing pure ACMGs, review papers, publications not related to the questions, and papers describing work that did not meet a quality assessment were excluded, resulting in 34 articles being included in this review. Results show: (1) the energy sources and AC bus nature of microgrids over five years, (2) the identification and quantification of cited standards for microgrids, (3) the pros and cons of different schemes for connecting an AC microgrid to the main grid, (4) the control schemes, classified in a hierarchical control structure, and (5) the simulation tools and experimental benches used in microgrids. Most studies considered a generic energy source and a low-voltage three-phase AC bus, 16 standards were found, and the most cited standard was IEEE Standard 1547. The most common connection scheme to the utility grid was a direct connection, most of the works proposed a modification to a hierarchical control system scheme, and the most common simulation tool was MATLAB. The preferred experimental setup consisted of parallel inverters for testing a control scheme, a prototype when proposing a power electronic system, and a laboratory microgrid for testing fault detection methods.

There is a general agreement among researchers that supercritical carbon dioxide (sCO2) cycles will be part of the next generation of thermal power plants, especially in concentrating solar power (CSP) plants. While certain studies focus on maximizing the efficiency of these cycles in the hope of achieving a reduction in electricity costs, it is important to note that this assumption does not always hold true. This work provides a comprehensive analysis of the differences between minimizing the cost and maximizing the efficiency for the most remarkable sCO2 cycles. The analysis considers the most important physical uncertainties surrounding CSP and sCO2 cycles, such as turbine inlet temperature, ambient temperature, pressure drop and turbomachinery efficiency. Moreover, the uncertainties related to cost are also analyzed, being divided into uncertainties of sCO2 component costs and uncertainties of heating costs. The CSP system with partial cooling (sometimes with reheating and sometimes without it) is the cheapest configuration in the analyzed cases. However, the differences in cost are generally below 5% (and sometimes neglectable), while the differences in efficiency are significantly larger and below 15%. Besides the much lower efficiency of systems with simple cycle, if the heating cost is low enough, their cost could be even lower than the cost of the system with partial cooling. Systems with recompression cycles could also achieve costs below systems with partial cooling if the design’s ambient temperature and the pressure drop are low.

Microgrids represent a promising energy technology, because of the inclusion in them of clean and smart energy technologies. They also represent research challenges, including controllability, stability, and implementation. This article presents a dSPACE-control-platform-based implementation of a fixed-switching-frequency modulated model predictive control (M2PC) strategy, as an inner controller of a two-level, three-phase voltage source inverter (VSI) working in an islanded AC microgrid. The developed controller is hierarchical, as it includes a primary controller to share the load equally with the other power converter with its own local modulated predictive-based controller. All details of the implementation are given for establishing the dSPACE-based implementation of the control on a dSPACE ds1103 control platform, using MATLAB/Simulink for the controller design, I/O implementation and configuration with the embedded dSPACE’s real-time interface in Simulink, and then using the ControlDesk software for monitoring and testing of the real plant. The latter consists of the VSI operating with LCL filters, and sharing an RL load with a paralleled VSI with exactly the same controller. Finally, the obtained experimental waveforms are shown, with our respective conclusions representing this work, which is a very valuable tool for helping microgrid researchers implement dSPACE-based real-time simulations.

The effects of partial shading or dust accumulation on the panels of photovoltaic systems connected to the grid can generate a considerable reduction in energy performance, being necessary to provide the appropriate voltage to the grid regardless of the irradiance level. This paper addresses this problem and presents a comprehensive control strategy and its implementation for a grid-connected microinverter composed of a push–pull converter followed by an H-bridge inverter. In the push–pull converter, a hybrid MPPT algorithm and a PI control enable work in the MPP of the PV panel. In the H-bridge inverter, a cascade control consisting of a PI control and a predictive control allows the connection to the grid. A proof-of-concept prototype is implemented in order to validate the proposal. Experimental tests were performed by connecting the microinverter to a PV panel and a programmable photovoltaic panel emulator to check the MPPT performance. Furthermore, partial shading conditions were simulated on the dc source to check if the global maximum power point is reached. Experimental results demonstrate the feasibility of the topology and the control approach, obtaining MPPT performance in the topology above 99% at different power and voltage levels on the MPPT, even in the presence of partial shading conditions.

Re-education of the tumor microenvironment with immune checkpoint inhibitors (ICI) has provided the most significant advancement in cancer management, with impressive efficacy and durable response reported. However, low response rates and a high frequency of immune-related adverse events (irAEs) remain associated with ICI therapies. The latter can be linked to their high affinity and avidity for their target that fosters on-target/off-tumor binding and subsequent breaking of immune self-tolerance in normal tissues. Many multispecific protein formats have been proposed to increase the tumor cell’s selectivity of ICI therapies. In this study, we explored the engineering of a bispecific Nanofitin by the fusion of an anti-epidermal growth factor receptor (EGFR) and anti-programmed cell death ligand 1 (PDL1) Nanofitin modules. While lowering the affinity of the Nanofitin modules for their respective target, the fusion enables the simultaneous engagement of EGFR and PDL1, which translates into a selective binding to tumor cells co-expressing EGFR and PDL1 only. We demonstrated that affinity-attenuated bispecific Nanofitin could elicit PDL1 blockade exclusively in an EGFR-directed manner. Overall, the data collected highlight the potential of this approach to enhance the selectivity and safety of PDL1 checkpoint inhibition.

The employment of microgrids and distributed power generation have exponentially increased over recent decades, due in part to the increased inclusion of renewable energies as these technologies become cheaper to install. However, microgrids are highly sensitive to power variation, leading to distortion of the grid voltage (amplitude and frequency changes) which could destabilize the entire microgrid under variation of loads and/or other power sources. In this context, a new control strategy is proposed for a photovoltaic grid connected system, operating under voltage variations typical of a low inertial electric power network. The main problem related to voltage fluctuation is that the variables may take the power converter out of the operating region, and therefore, all controllers, including the maximum power point tracking, will not work as designed. The analysis, based on the mathematical operating region, demonstrates that the control strategy can include overmodulation compensation—to overcome problems related to weak microgrids and systems variations—through the addition of smart power factor imposition and DC-link voltage variation in transient time when the variables are far from the nominal values. The proposal is validated through simulation in PSim®/Matlab® and implementation on a laboratory prototype, showing the feasibility of the designed algorithm.

The advancement of robotics in recent years has driven the growth of robotic applications for more complex tasks requiring manipulation capabilities. Recent works have focused on adapting learning methods to manipulation applications which are stochastic and may not converge. In this paper, a kinesthetic learning method based on fast marching square is presented. This method poses great advantages such as ensuring convergence and is based on learning from the experience of a human demonstrator. For this purpose, the demonstrator teaches paths by physically guiding one of the UR3 arms of a mobile manipulator. After this first phase, the fast marching Learning method is used to make the robot learn from this experience. As a novelty, an auto-learning functionality is presented, which provides the kinesthetic learning algorithm with an exploration capacity. The base of this algorithm is not only using the information provided by the taught trajectories, but also expanding its ability in order to explore unknown states of the environment. The effectiveness of the proposed method has been evaluated through simulations in 2D and 3D environments and in a real mobile manipulator. The learning process is analyzed with other 2D learning approaches using the LASA dataset and it is tested in complex 3D scenarios with different obstacles, proving its effectiveness.

In this paper, we present a study on coverage missions carried out by UAV formations in 3D environments. These missions are designed to be applied in tracking and search and rescue missions, especially in the case of accidents. In this manner, the presented method focuses on the path planning stage, the objective of which is to compute a convenient trajectory to completely cover a certain area in a determined environment. The methodology followed uses a Gaussian mixture to approximate a probability of containment distribution along with the Fast Marching Square (FM2) as path planner. The Gaussians permit to define a zigzag trajectory that optimizes the path. Next, a first 2D geometric path perpendicular to the Voronoi diagram of the Gaussian distribution is calculated, obtained by skeletonization. To this path, the height above the ground is added plus the desired flight height to make it 3D. Finally, the FM2 method for formations is applied to make the path smooth and safe enough to be followed by UAVs. The simulation experiments show that the proposed method achieves good results for the zigzag path in terms of smoothness, safety and distance to cover the desired area through the formation of UAVs.

The problem of the output voltage regulation in a DC-DC boost converter feeding a DC microgrid is addressed in this research via the passivity-based control theory with a proportional–integral action (PI-PBC). Two external input estimators were implemented in conjunction with the proposed controller to make it sensorless and adaptive. The first estimator corresponds to the immersion & invariance (I&I) approach applied to calculate the expected value of the DC load, which is modeled as an unknown DC current. The second estimator is based on the disturbance–observer (DO) approach, which reaches the value of the voltage input. The main advantage of both estimators is that these ensure exponential convergence under steady-state operating conditions, and their parametrization only requires the definition of an integral gain. A comparative analysis with simulations demonstrates that the proposed PI-PBC approach is effective in regulating/controlling the voltage profile in unknown DC loads as compared to the adaptive sliding mode controller. Experimental validations have demonstrated that the proposed PI-PBC approach, in conjunction with the I&I and the DO estimators, allowed regulation of the voltage output profile in the terminals of the DC load with asymptotic stability properties and fast convergence times (1.87 ms) and acceptably overshoots (6.1%) when the voltage input varies its magnitude (from 10 to 12 V and from 10 to 8 V) considering that the DC load changed with a square waveform between 1 and 2 A with 100 Hz.

In this paper, a fixed-switching-frequency modulated model predictive control (M2PC) is established for a two-level three-phase voltage source inverter (VSI) working in an islanded AC microgrid. These small-scale power systems are composed by two or more VSIs which interface DGs, controlling the voltage amplitude and frequency in the system, and simultaneously sharing the load active and reactive power. Generally, these operational characteristics are achieved using hierarchical linear control loops, but with challenging limitations such as slow transient reaction to disturbances and high proneness to be affected by parameter modifications. Model predictive control may solve these issues. Nevertheless, the most used and developed predictive control scheme, the finite-set model predictive control (FS-MPC), presents the drawback of having the harmonic spectrum spread over all the frequencies. This brings issues with coupling between the different hierarchical control levels of the whole microgrid system, and eventually, when designing the filters for main-grid connection. This paper aims to solve these issues by developing the fixed-switching-frequency M2PC working with higher-level control loops for operation in an islanded AC microgrid. These advantages are proved in an AC microgrid configuration where methodology for paralleling multiple M2PC-regulated VSIs is described, with rapid transient response, inherent stability, and fully decentralised operation of individual VSIs, achieving proper load power sharing, eliminating circular currents, and proper waveforms for output currents and capacitor voltages. All these achievements have been confirmed via simulation and experimental verification.

Along with the increasing global burden of diabetes, diabetic foot infections (DFI) and diabetic foot osteomyelitis (DFO) remain major challenges for patients and society. Despite progress in the development of prominent international guidelines, the optimal medical treatment for DFI and DFO remains unclear as to whether local antibiotics, that is, topical agents and local delivery systems, should be used alone or concomitant to conventional systemic antibiotics. To better inform clinicians in this evolving field, we performed a narrative review and summarized key relevant observational studies and clinical trials of non-prophylactic local antibiotics for the treatment of DFI and DFO, both alone and in combination with systemic antibiotics. We searched PubMed for studies published between January 2000 and October 2022, identified 388 potentially eligible records, and included 19 studies. Our findings highlight that evidence for adding local antibiotic delivery systems to standard DFO treatment remains limited. Furthermore, we found that so far, local antibiotic interventions have mainly targeted forefoot DFO, although there is marked variation in the design of the included studies. Suggestive evidence emerging from observational studies underscores that the addition of local agents to conventional systemic antibiotics might help to shorten the clinical healing time and overall recovery rates in infected diabetic foot ulcers, although the effectiveness of local antibiotics as a standalone approach remains overlooked. In conclusion, despite the heterogeneous body of evidence, the possibility that the addition of local antibiotics to conventional systemic treatment may improve outcomes in DFI and DFO cannot be ruled out. Antibiotic stewardship principles call for further research to elucidate the potential benefits of local antibiotics alone and in combination with conventional systemic antibiotics for the treatment of DFI and DFO.

This paper presents an adaptive control to stabilize the output voltage of a DC–DC boost converter that feeds an unknown constant power load (CPL). The proposed controller employs passivity-based control (PBC), which assigns a desired system energy to compensate for the negative impedance that may be generated by a CPL. A proportional-integral (PI) action that maintains a passive output is added to the PBC to impose the desired damping and enhance disturbance rejection behavior, thus forming a PI+PBC control. In addition, the proposed controller includes two estimators, i.e., immersion and invariance (I&I), and disturbance observer (DO), in order to estimate CPL and supply voltage for the converter, respectively. These observers become the proposed controller for an adaptive, sensorless PI+PBC control. Phase portrait analysis and experimental results have validated the robustness and effectiveness of the adaptive proposed control approach. These results show that the proposed controller adequately regulates the output voltage of the DC–DC boost converter under variations of the input voltage and CPL simultaneously.

An accurate model of a proton-exchange membrane fuel cell (PEMFC) is important for understanding this fuel cell’s dynamic process and behavior. Among different large-scale energy storage systems, fuel cell technology does not have geographical requirements. To provide an effective operation estimation of PEMFC, this paper proposes a support vector machine (SVM) based model. The advantages of the SVM, such as the ability to model nonlinear systems and provide accurate estimations when nonlinearities and noise appear in the system, are the main motivations to use the SVM method. This model can capture the static and dynamic voltage–current characteristics of the PEMFC system in the three operating regions. The validity of the proposed SVM model has been verified by comparing the estimated voltage with the real measurements from the Ballard Nexa® 1.2 kW fuel cell (FC) power module. The obtained results have shown high accuracy between the proposed model and the experimental operation of the PEMFC. A statistical study is developed to evaluate the effectiveness and superiority of the proposed SVM model compared with the diffusive global (DG) model and the evolution strategy (ES)-based model.

Waldenström macroglobulinemia (WM) is a rare form of non-Hodgkin B-cell lymphoma with a variable clinical presentation that can impact a patient’s quality of life by causing anemia, peripheral neuropathy, serum hyperviscosity, extramedullary disease, and other symptoms. There are several safe and effective treatment regimens for patients with WM, and the choice of therapy should be made in a personalized fashion considering the patient’s symptoms, comorbidities, and genomic profile. Bruton tyrosine kinase (BTK) inhibitors are a new option to treat patients with WM. Zanubrutinib is a next-generation covalent BTK inhibitor designed to have fewer off-target effects than previous BTK inhibitors. This review summarizes the pharmacokinetic and pharmacodynamic properties of zanubrutinib as well as safety and efficacy findings. Then, it explores the health economic and outcomes research associated with the costs of treating patients with WM and the reasons why zanubrutinib may be a more cost-effective treatment option compared with ibrutinib, a first-generation BTK inhibitor. Future directions for the treatment of WM focus on the use of zanubrutinib in combination therapy. Combinations based on effective ibrutinib or acalabrutinib treatments may be effectively applied with zanubrutinib given the similar mechanism of action for these BTK inhibitors. Combination therapies could also help prevent the development of disease resistance, minimize toxicity, and support treatment regimens of finite duration.

Distributed power generation, micro-grids, and networks working in islanding mode have strong deviations in voltage quantities. These deviations can be divided into amplitude and frequency. Amplitude deviations are well-known and studied, as they are common in small and big grids. However, deviations on the ac mains frequency have not been widely studied. The literature shows control schemes capable of bearing these variations, but no systematic analysis has been performed to ensure stability. As the majority of power converters are designed for big grids, their analysis and design neglect frequency disturbances, therefore those devices allow a very small frequency operating window. For instance, in power converters that need to be synchronized to the grid, the standard deviation does not go beyond 0.5 Hz, and for grid-tied inverters it does not go beyond 1 Hz, whereas variations of around 8 Hz can be expected in micro-grids. This work presents a comprehensive analysis of the control system’s stability, where two different control schemes for a back-to-back static converter topology are implemented and studied under a wide variable grid frequency. Because the behavior of power converters is nonlinear and coupled, dynamic and static decouplers are usually introduced in the controller, being a key element on the scheme according to the findings. The results show that using just a static decoupler does not guarantee stability under frequency variations; meanwhile, when a dynamic decoupler is used, the operating window can be greatly extended. The procedure shown in this paper can also be extended to other control algorithms, making it possible to carefully choose the control system for a variable frequency condition. Simulated and experimental results confirm the theoretical approach.

In this paper, we present an implementation of selective harmonic elimination modulation technique in a 27-Level asymmetric multilevel converter. The main issue in this kind of converters is the generation of the gating patterns to obtain an optimized AC voltage waveform. State-of-the art solutions use deep mathematical analysis in the frequency domain by means of the Fourier series, but they are mainly applied for two-level or symmetric multilevel converters. On the other hand, the modulation for asymmetric multilevel converters is mainly focused on nearest level control or nearest vector control. In this work, we propose a novel modulating technique that takes advantage of the switching angles optimization for a 27-level waveform. In fact, different set of solutions are obtained and presented in order to define the modulation index as well as the value of the switching angles for the multilevel waveform. A modulation index sweep was performed for the entire operating region of the converter, where it can be observed that the number of levels decreases when the modulation index is low, which are calculated in order to minimize the total harmonic distortion (THD) of the resulting voltage waveform. In order to validate the proposal, these results for different modulation indexes values are simulated, obtaining a THD < 5% for a modulation index 0.75

The use of controlled power converters has been extended for high power applications, stacking off-the-shelve semiconductors, and allowing the implementation of, among others, AC drives for medium voltages of 2.3 kV to 13.8 kV. For AC drives based on power cells assembled with three-phase diode rectifiers and cascaded H-bridge inverters, a sophisticated input multipulse transformer is required to reduce the grid voltage, provide isolation among the power cells, and compensate for low-frequency current harmonics generated by the diode-based rectifiers. However, this input multipulse transformer is bulky, heavy, and expensive and must be designed according to the number of power cells, not allowing total modularity of the AC drives based on cascade H-bridges. This study proposes and evaluates a control strategy based on a finite control set-model predictive control that emulates the harmonic cancellation performed by an input multipulse transformer in a cascade H-bridge topology. Hence, the proposed method requires conventional input transformers and replaces the three-phase diode rectifiers. As a result, greater modularity than the conventional multicell converter and improved AC overall input current with a THD as low as 2% with a unitary displacement power factor are achieved. In this case, each power cell manages its own DC voltage using a nonlinear control strategy, ensuring stable system operation for passive and regenerative loads. The experimental tests demonstrated the correct performance of the proposed scheme.

This paper studies the Fast Marching Square (FM2) method as a competitive path planner for UAV applications. The approach fulfills trajectory curvature constraints together with a significantly reduced computation time, which makes it overperform with respect to other planning methods of the literature based on optimization. A comparative analysis is presented to demonstrate how the FM2 approach can easily adapt its performance thanks to the introduction of two parameters, saturation α and exponent β, that allow a flexible configuration of the paths in terms of curvature restrictions, among others. The main contributions of the method are twofold: first, a feasible path is directly obtained without the need of a later optimization process to accomplish curvature restrictions; second, the computation speed is significantly increased, up to 220 times faster than other optimization-based methods such as, for instance, Dubins, Euler–Mumford Elastica and Reeds–Shepp. Simulation results are given to demonstrate the superiority of the method when used for UAV applications in comparison with the three previously mentioned methods.

Signature-based Intrusion Detection Systems (SIDS) play a crucial role within the arsenal of security components of most organizations. They can find traces of known attacks in the network traffic or host events for which patterns or signatures have been pre-established. SIDS include standard packages of detection rulesets, but only those rules suited to the operational environment should be activated for optimal performance. However, some organizations might skip this tuning process and instead activate default off-the-shelf rulesets without understanding its implications and trade-offs. In this work, we help gain insight into the consequences of using predefined rulesets in the performance of SIDS. We experimentally explore the performance of three SIDS in the context of web attacks. In particular, we gauge the detection rate obtained with predefined subsets of rules for Snort, ModSecurity and Nemesida using seven attack datasets. We also determine the precision and rate of alert generated by each detector in a real-life case using a large trace from a public webserver. Results show that the maximum detection rate achieved by the SIDS under test is insufficient to protect systems effectively and is lower than expected for known attacks. Our results also indicate that the choice of predefined settings activated on each detector strongly influences its detection capability and false alarm rate. Snort and ModSecurity scored either a very poor detection rate (activating the less-sensitive predefined ruleset) or a very poor precision (activating the full ruleset). We also found that using various SIDS for a cooperative decision can improve the precision or the detection rate, but not both. Consequently, it is necessary to reflect upon the role of these open-source SIDS with default configurations as core elements for protection in the context of web attacks. Finally, we provide an efficient method for systematically determining which rules deactivate from a ruleset to significantly reduce the false alarm rate for a target operational environment. We tested our approach using Snort’s ruleset in our real-life trace, increasing the precision from 0.015 to 1 in less than 16 h of work.

Coverage path planning (CPP) is a field of study which objective is to find a path that covers every point of a certain area of interest. Recently, the use of Unmanned Aerial Vehicles (UAVs) has become more proficient in various applications such as surveillance, terrain coverage, mapping, natural disaster tracking, transport, and others. The aim of this paper is to design efficient coverage path planning collision-avoidance capable algorithms for single or multi UAV systems in cluttered urban environments. Two algorithms are developed and explored: one of them plans paths to cover a target zone delimited by a given perimeter with predefined coverage height and bandwidth, using a boustrophedon flight pattern, while the other proposed algorithm follows a set of predefined viewpoints, calculating a smooth path that ensures that the UAVs pass over the objectives. Both algorithms have been developed for a scalable number of UAVs, which fly in a triangular deformable leader-follower formation with the leader at its front. In the case of an even number of UAVs, there is no leader at the front of the formation and a virtual leader is used to plan the paths of the followers. The presented algorithms also have collision avoidance capabilities, powered by the Fast Marching Square algorithm. These algorithms are tested in various simulated urban and cluttered environments, and they prove capable of providing safe and smooth paths for the UAV formation in urban environments.

In this paper, we propose a coverage method for the search of lost targets or debris on the ocean surface. The OSCAR data set is used to determine the marine currents and the differential evolution genetic filter is used to optimize the sweep direction of the lawnmower coverage and get the sweep angle for the maximum probability of containment. The position of the target is determined by a particle filter, where the particles are moved by the ocean currents and the final probabilistic distribution is obtained by fitting the particle positions to a Gaussian probability distribution. The differential evolution algorithm is then used to optimize the sweep direction that covers the highest probability of containment cells before the less probable ones. The algorithm is tested with a variety of parameters of the differential evolution algorithm and compared to other popular optimization algorithms.

The use of renewable energies sources is taking great importance due to the high demand for electricity and the decrease in the use of fossil fuels worldwide. In this context, electricity generation through photovoltaic panels is gaining a lot of interest due to the reduction in installation costs and the rapid advance of the development of new technologies. To minimize or reduce the negative impact of partial shading or mismatches of photovoltaic panels, many researchers have proposed four configurations that depend on the power ranges and the application. The microinverter is a promising solution in photovoltaic systems, due to its high efficiency of Maximum Power Point Tracking and high flexibility. However, there are several challenges to improve microinverter’s reliability and conversion efficiency that depend on the proper control design and the power converter design. This paper presents a review of different control strategies in microinverters for different applications. The control strategies are described and compared based on stability, dynamic response, topologies, and control objectives. One of the most important results showed that there is little research regarding the stability and robustness analysis of the reviewed control strategies.

Several studies have demonstrated that melanoma-derived extracellular vesicles (EVs) are involved in lymph node metastasis; however, the molecular mechanisms involved are not completely defined. Here, we found that EMILIN-1 is proteolyzed and secreted in small EVs (sEVs) as a novel mechanism to reduce its intracellular levels favoring metastasis in mouse melanoma lymph node metastatic cells. Interestingly, we observed that EMILIN-1 has intrinsic tumor and metastasis suppressive-like properties reducing effective migration, cell viability, primary tumor growth, and metastasis. Overall, our analysis suggests that the inactivation of EMILIN-1 by proteolysis and secretion in sEVs reduce its intrinsic tumor suppressive activities in melanoma favoring tumor progression and metastasis.

In this work, an evaluation and quantification of the impact of using mixtures based on supercritical carbon dioxide “s-CO2” (s-CO2/COS, s-CO2/H2S, s-CO2/NH3, s-CO2/SO2) are made as a working fluid in simple and complex recompression Brayton s-CO2 power cycle configurations that have pressure drops in their components. These cycles are coupled with a solar thermal plant with parabolic-trough collector (PTC) technology. The methodology used in the calculation performance is to establish values of the heat recuperator total conductance (UAtotal) between 5 and 25 MW/K. The main conclusion of this work is that the cycle’s efficiency has improved due to using s-CO2 mixtures as working fluid; this is significant compared to the results obtained using the standard fluid (pure s-CO2). Furthermore, a techno-economic analysis is carried out that compares each configuration’s costs using pure s-CO2 and a mixture of s-CO2/COS with a molar fraction (70/30), respectively, as working fluid where relevant results are obtained. These results show that the best configuration in terms of thermal efficiency and cost is the RCC-RH for pure sCO2 with values of 41.25% and 2811 $/kWe, while for the mixture sCO2/COS, the RCC-2RH configuration with values of 45.05% and 2621 $/kWe is optimal. Using the mixture costs 6.75% less than if it is used the standard fluid (s-CO2).

A new type of Fresnel array has been devised and constructed as an answer to the need to reduce the investment costs of solar thermal collectors, without jeopardizing their efficiency in capturing solar radiation at high temperatures. The array of mirror bands is fixed onto a horizontal platform, which rotates around a virtual vertical axis, so that the sun is in the extrapolated vertical plane of symmetry of the array. The receptor central line is also placed in said plane, and it is physically made of at least one tube at each side of the plane. The geometrical relation between the mirrors and the receptor is therefore fixed. The platform rotates with the same speed as that of the sunlight’s azimuthal component. On the contrary, the angle of incidence of the sunlight on the mirrors changes as the sun rises and declines in its daily apparent motion, but this effect does not disturb the radiation concentration kinematics, although it induces a shift along the receptor. This is a new configuration based on the use of simple and cheap flat mirrors to obtain circular cylindrical mirrors. These mirrors are made of originally flat mirrors that are bent by applying an inexpensive and simple bending technique patented by our research group. The radius of curvature of each mirror is tuned to the distance from the mirror to the receiver central line. The integration of different scientific domains (such as structural analysis) and elementary technologies (such as 3D printing) in this innovative solar radiation concentrator and receiver can lead to a large reduction in costs. Nevertheless, the first experimental campaign has shown additional problems in the receiver configuration, which should be addressed in a next stage of research. This paper explains the methodology used and procedures in the development of the first prototype of the Sundial.

Multi-UAV systems are attracting, especially in the last decade, the attention of researchers and companies of very different fields due to the great interest in developing systems capable of operating in a coordinated manner in complex scenarios and to cover and speed up applications that can be dangerous or tedious for people: search and rescue tasks, inspection of facilities, delivery of goods, surveillance, etc. Inspired by these needs, this work aims to design, implement and analyze a trajectory planning and collision avoidance strategy for multi-UAV systems in 3D environments. For this purpose, a study of the existing techniques for both problems is carried out and an innovative strategy based on Fast Marching Square—for the planning phase—and a simple priority-based speed control—as the method for conflict resolution—is proposed, together with prevention measures designed to try to limit and reduce the greatest number of conflicting situations that may occur between vehicles while they carry out their missions in a simulated 3D urban environment. The performance of the algorithm is evaluated successfully on the basis of certain conveniently chosen statistical measures that are collected throughout the simulation runs.

The human genome contains nearly 100 deubiquitinating enzymes (DUBs) responsible for removing ubiquitin moieties from a large variety of substrates. Which DUBs are responsible for targeting which substrates remain mostly unknown. Here we implement the bioUb approach to identify DUB substrates in a systematic manner, combining gene silencing and proteomics analyses. Silencing of individual DUB enzymes is used to reduce their ubiquitin deconjugating activity, leading to an increase of the ubiquitination of their substrates, which can then be isolated and identified. We report here quantitative proteomic data of the putative substrates of 5 human DUBs. Furthermore, we have built a novel interactive database of DUB substrates to provide easy access to our data and collect DUB proteome data from other groups as a reference resource in the DUB substrates research field.

The thermal management of magnetic components for power electronics is crucial to ensure their reliability. However, conventional thermal models for magnetic components are known to have either poor accuracy or excessive complexity. Contrary to these models, the use of Thermal Resistance Matrices is proposed in this paper instead, which combine both accuracy and simplicity. They are usually used to characterize semiconductor devices, but not for magnetic components. The guidelines to apply Thermal Resistance Matrices for magnetic components are discussed in detail. The accuracy of this model is validated by 3D FEA simulations and experimental results, showing an absolute error lower than 5 ∘C and a relative error between −6.4% and 3.9%, which is outstanding compared to the carried-out literature review.

Antimetastatic properties on both murine and human osteosarcoma cell lines (POS-1 and KHOS) have been evidenced using exopolysaccharide (EPS) derivatives, produced by Alteromonas infernus bacterium. These derivatives had no significant effect on the cell cycle neither a pro-apoptotic effect on osteosarcoma cells. Based on this observation, these EPSs could be employed as new drug delivery systems for therapeutic uses. A theranostic approach, i.e., combination of a predictive biomarker with a therapeutic agent, has been developed notably by combining with true pair of theranostic radionuclides, such as scandium 47Sc/44Sc. However, it is crucial to ensure that, once complexation is done, the biological properties of the vector remain intact, allowing the molecular tropism of the ligand to recognize its molecular target. It is important to assess if the biological properties of EPS evidenced on osteosarcoma cell lines remain when scandium is complexed to the polymers and can be extended to other cancer cell types. Scandium-EPS complexes were thus tested in vitro on human cell lines: MNNG/HOS osteosarcoma, A375 melanoma, A549 lung adenocarcinoma, U251 glioma, MDA231 breast cancer, and Caco2 colon cancer cells. An xCELLigence Real Cell Time Analysis (RTCA) technology assay was used to monitor for 160 h, the proliferation kinetics of the different cell lines. The tested complexes exhibited an anti-proliferative effect, this effect was more effective compared to EPS alone. This increase of the antiproliferative properties was explained by a change in conformation of EPS complexes due to their polyelectrolyte nature that was induced by complexation. Alterations of both growth factor-receptor signaling, and transmembrane protein interactions could be the principal cause of the antiproliferative effect. These results are very promising and reveal that EPS can be coupled to scandium for improving its biological effects and also suggesting that no major structural modification occurs on the ligand.

The single-phase matrix converter is an AC-AC power topology which consists of six bidirectional switches and it is considered the key unit in cascade or multilevel configurations. In this paper, a comparison between two control techniques is presented, one based on a proportional-integral-derivative control module with a pulse width modulator, and the other known as finite-state model predictive control. Simulation and experimental results are presented and discussed to demonstrate the feasibility and performance of both techniques.

Superconducting links are an innovative solution for bulk power transmission, distinguished by their compact dimensions, high efficiency and small environmental footprint. As with any new technology field, there is a large amount of design possibilities for such links, each of them having a profound impact on the system configuration. For instance, changing the material can imply a change in the working temperature from 20 to 70 K and has consequences on the maximum link length. This article presents the dichotomic decision possibilities for the optimized design of a high-power superconducting link, focusing on some of the key components of the cable system. The complex design optimization process is exemplified using the European project Best Paths, in which the first 3-gigawatt-class superconducting cable system was designed, optimized, manufactured, and successfully tested.

In atherosclerosis, circulating angiogenic cells (CAC), also known as early endothelial progenitor cells (eEPC), are thought to participate mainly in a paracrine fashion by promoting the recruitment of other cell populations such as late EPC, or endothelial colony-forming cells (ECFC), to the injured areas. There, ECFC replace the damaged endothelium, promoting neovascularization. However, despite their regenerative role, the number and function of EPC are severely affected under pathological conditions, being essential to further understand how these cells react to such environments in order to implement their use in regenerative cell therapies. Herein, we evaluated the effect of direct incubation ex vivo of healthy CAC with the secretome of atherosclerotic arteries. By using a quantitative proteomics approach, 194 altered proteins were identified in the secretome of pre-conditioned CAC, many of them related to inhibition of angiogenesis (e.g., endostatin, thrombospondin-1, fibulins) and cell migration. Functional assays corroborated that healthy CAC released factors enhanced ECFC angiogenesis, but, after atherosclerotic pre-conditioning, the secretome of pre-stimulated CAC negatively affected ECFC migration, as well as their ability to form tubules on a basement membrane matrix assay. Overall, we have shown here, for the first time, the effect of atherosclerotic factors over the paracrine role of CAC ex vivo. The increased release of angiogenic inhibitors by CAC in response to atherosclerotic factors induced an angiogenic switch, by blocking ECFC ability to form tubules in response to pre-conditioned CAC. Thus, we confirmed here that the angiogenic role of CAC is highly affected by the atherosclerotic environment.

Microgrids need control and management at different levels to allow the inclusion of renewable energy sources. In this paper, a comprehensive literature review is presented to analyse the latest trends in research and development referring to the applications of predictive control in microgrids. As a result of this review, it was found that the application of predictive control techniques on microgrids is performed for the three control levels and with adaptations of the models in order to include uncertainties to improve their performance and dynamics response. In addition, to ensure system stability, but also, at higher control levels, coordinated operation among the microgrid’s components and synchronised and optimised operation with utility grids and electric power markets. Predictive control appears as a very promising control scheme with several advantages for microgrid applications of different control levels.

This paper compares the annual performance of Integrated Solar Combined Cycles (ISCCs) using different solar concentration technologies: parabolic trough collectors (PTC), linear Fresnel reflectors (LFR) and central tower receiver (CT). Each solar technology (i.e. PTC, LFR and CT) is proposed to integrate solar energy into the combined cycle in two different ways. The first one is based on the use of solar energy to evaporate water of the steam cycle by means of direct steam generation (DSG), increasing the steam production of the high pressure level of the steam generator. The other one is based on the use of solar energy to preheat the pressurized air at the exit of the gas turbine compressor before it is introduced in the combustion chamber, reducing the fuel consumption. Results show that ISCC with DSG increases the yearly production while solar air heating reduces it due to the incremental pressure drop. However, air heating allows significantly higher solar-to-electricity efficiencies and lower heat rates. Regarding the solar technologies, PTC provides the best thermal results.

Monocytes are bone marrow-derived leukocytes that are part of the innate immune system. Monocytes are divided into three subsets: classical, intermediate and non-classical, which can be differentiated by their expression of some surface antigens, mainly CD14 and CD16. These cells are key players in the inflammation process underlying the mechanism of many diseases. Thus, the molecular characterization of these cells may provide very useful information for understanding their biology in health and disease. We performed a multicentric proteomic study with pure classical and non-classical populations derived from 12 healthy donors. The robust workflow used provided reproducible results among the five participating laboratories. Over 5000 proteins were identified, and about half of them were quantified using a spectral counting approach. The results represent the protein abundance catalogue of pure classical and enriched non-classical blood peripheral monocytes, and could serve as a reference dataset of the healthy population. The functional analysis of the differences between cell subsets supports the consensus roles assigned to human monocytes.