Real Time Fractional Robust Adaptive Scheme for Frequency Regulation in Double Area Hybrid Power System With Renewables

Load frequency regulation in hybrid grid is a very crucial issue. This work introduces robust-adaptive control methodology to provide accurate response against any disturbances. Control scheme of two main parts has been introduced. The first one is a novel fractional order model reference adaptive controller where fractional calculus merits and e-modification robust algorithm have been merged with the adaptive skills creating the fractional order model reference robust-adaptive controller. This robust-adaptive controller has utilized output feedback approach that requires only the output state without detailed system model information. The fractional orders have been optimized using a nature-inspired algorithm named Artificial Rabbits. The second part of the control scheme is a disturbance rejection observer that is able to estimate and eliminate external and internal disturbances. For fair comparison, results of the proposed scheme have been compared to that of the most efficient controllers obtained from the literature named fractional order proportional integral derivative controller and integral controller. Furthermore, the integer version of the proposed controller has been tested and compared with the proposed controller to prove the robustness of the fractional modification. To validate the superiority of the proposed controller, five challenging scenarios have been considered, encompassing load fluctuations, integration of renewable energy sources, changes in system parameters and time delay attacks. The proposed controller effectively minimizes area control error achieving stability and showing cost function enhancement of 15% to 152% compared to other tested controllers in all scenarios. Thus, it is strongly recommended for load frequency regulation in multi-area power systems

Three year experience with the cochlear BAHA attract implant: a systematic review of the literature

Background Bone conduction devices are widely used and indicated in cases of conductive, mixed or single sided deafness where conventional hearing aids are not indicated or tolerated. Percutaneous bone-conduction devices gave satisfactory hearing outcomes but were frequently complicated by soft tissue reactions. Transcutaneous bone conduction devices were developed in order to address some of the issues related to the skin-penetrating abutment. The aim of this article is to present a systematic review of the indications, surgical technique and audiological, clinical and functional outcomes of the BAHA Attract device reported so far. Methods A systematic computer-based literature search was performed on the PubMed database as well as Scopus, Cochrane and Google Scholar. Out of 497 articles, 10 studies and 89 reported cases were finally included in our review. Results The vast majority of implanted patients were satisfied with the aesthetics of the device scoring highly at the Abbreviated Profile of Hearing Aid Benefit, Glasgow Benefit Inventory and Client Oriented Scale of Improvement. Overall, hearing outcomes, tested by various means including speech in noise, free field hearing testing and word discrimination scores showed a significant improvement. Complications included seroma or haematoma formation, numbness around the area of the flap, swelling and detachment of the sound processor from the external magnet. Conclusions The functional and audiological results presented so far in the literature have been satisfactory and the complication rate is low compared to the skin penetrating Bone Conduction Devices. Further robust trials will be needed to study the long-term outcomes and any adverse effects

Parameters Identification of the Fractional-Order Permanent Magnet Synchronous Motor Models Using Chaotic Ensemble Particle Swarm Optimizer

© 2021 by the authors. In this paper, novel variants for the Ensemble Particle Swarm Optimizer (EPSO) are proposed where ten chaos maps are merged to enhance the EPSO’s performance by adaptively tuning its main parameters. The proposed Chaotic Ensemble Particle Swarm Optimizer variants (C.EPSO) are examined with complex nonlinear systems concerning equal order and variable-order fractional models of Permanent Magnet Synchronous Motor (PMSM). The proposed variants’ results are compared to that of its original version to recommend the most suitable variant for this non-linear optimization problem. A comparison between the introduced variants and the previously published algorithms proves the developed technique’s efficiency for further validation. The results emerge that the Chaotic Ensemble Particle Swarm variants with the Gauss/mouse map is the most proper variant for estimating the parameters of equal order and variable-order fractional PMSM models, as it achieves better accuracy, higher consistency, and faster convergence speed, it may lead to controlling the motor’s unwanted chaotic performance and protect it from ravage

Cryptosporidium Priming Is More Effective than Vaccine for Protection against Cryptosporidiosis in a Murine Protein Malnutrition Model

Cryptosporidium is a major cause of severe diarrhea, especially in malnourished children. Using a murine model of C. parvum oocyst challenge that recapitulates clinical features of severe cryptosporidiosis during malnutrition, we interrogated the effect of protein malnutrition (PM) on primary and secondary responses to C. parvum challenge, and tested the differential ability of mucosal priming strategies to overcome the PM-induced susceptibility. We determined that while PM fundamentally alters systemic and mucosal primary immune responses to Cryptosporidium, priming with C. parvum (106 oocysts) provides robust protective immunity against re-challenge despite ongoing PM. C. parvum priming restores mucosal Th1-type effectors (CD3+CD8+CD103+ T-cells) and cytokines (IFNγ, and IL12p40) that otherwise decrease with ongoing PM. Vaccination strategies with Cryptosporidium antigens expressed in the S. Typhi vector 908htr, however, do not enhance Th1-type responses to C. parvum challenge during PM, even though vaccination strongly boosts immunity in challenged fully nourished hosts. Remote non-specific exposures to the attenuated S. Typhi vector alone or the TLR9 agonist CpG ODN-1668 can partially attenuate C. parvum severity during PM, but neither as effectively as viable C. parvum priming. We conclude that although PM interferes with basal and vaccine-boosted immune responses to C. parvum, sustained reductions in disease severity are possible through mucosal activators of host defenses, and specifically C. parvum priming can elicit impressively robust Th1-type protective immunity despite ongoing protein malnutrition. These findings add insight into potential correlates of Cryptosporidium immunity and future vaccine strategies in malnourished children

A novel optimized dynamic fractional-order MPPT controller using hunter pray optimizer for alleviating the tracking oscillation with changing environmental conditions

Data availability: No data was used for the research described in the article.Copyright Crown [The Authors] © 2023. Introducing new control strategies in the photovoltaic (PV) system to continuously harvest the maximum power with the changes in environmental conditions is a crucial issue. Therefore, this paper proposes an efficient maximum power point tracker (MPPT) using the perspective of fractional calculus to provide an accurate dynamic response to the rapid changes in environmental conditions. The proposed control scheme is an integration between the fractional proportional–integral (FPI) controller and dynamic variable fractional-order perturb and observe (P&O) MPPT. To optimally identify the proposed MPPT controller parameters, a novel hunter-pray optimizer (HPO) is implemented as it is featured by its efficient balance between exploration and exploitation capacity. The proposed MPPT controller is examined with a series of experiments under dynamically changed environmental conditions. Furthermore, a detailed comparison is conducted versus a set of state-of-the-art including; incremental conductance (INC), basic P&O, MPPT-based particle swarm optimizer(PSO), MPPT-based Grey Wolf Optimizer(GWO), and MPPT-based cuckoo search algorithm (CSA). The results prove that the proposed MPPT is capable to track the global maximum generated power with a notable steady-state response and is almost free of oscillations which ensures an optimal adaptive dynamic performance in response to the rapid variation in the environmental conditions. Moreover, the proposed approach affirms its superiority compared to the set of state-of-the-art techniques in providing the highest maximum power levels in the shortest conversion time. The outcomes provide proof of the remarkable impacts of integrating fractional calculus in enhancing the dynamic response of the proposed MPPT because of the extra degree of freedom that enhance the flexibility of the MPPT

The self-management of longer-term depression: learning from the patient, a qualitative study

Background Depression is a common mental health condition now viewed as chronic or long-term. More than 50 % of people will have at least one further episode of depression after their first, and therefore it requires long-term management. However, little is known about the effectiveness of self-management in depression, in particular from the patients’ perspective. This study aimed to understand how people with longer-term depression manage the condition, how services can best support self-management and whether the principles and concepts of the recovery approach would be advantageous. Methods Semi-structured in depth interviews were carried out with 21 participants, recruited from a range of sources using maximum variation sampling. Interpretative Phenomenological Analysis was used by a diverse team comprised of service users, practitioners and academics. Results Four super-ordinate themes were found: experience of depression, the self, the wider environment, self-management strategies. Within these, several prominent sub-themes emerged of importance to the participants. These included how aspects of themselves such as hope, confidence and motivation could be powerful agents; and how engaging in a wide range of chosen activities could contribute to their emotional, mental, physical, social, spiritual and creative wellbeing. Conclusions Services in general were not perceived to be useful in specifically facilitating self-management. Increased choice and control were needed and a greater emphasis on an individualised holistic model. Improved information was needed about how to develop strategies and locate resources, especially during the first episode of depression. These concepts echoed those of the recovery approach, which could therefore be seen as valuable in aiding the self-management of depression. Keywords: Depression; Patients’ perspective; Qualitative research; Recovery; Self-help; Self-managemen

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky

Environmental dependence of the galaxy stellar mass function in the Dark Energy Survey Science Verification Data

Measurements of the galaxy stellar mass function are crucial to understand the formation of galaxies in the Universe. In a hierarchical clustering paradigm it is plausible that there is a connection between the properties of galaxies and their environments. Evidence for environmental trends has been established in the local Universe. The Dark Energy Survey (DES) provides large photometric datasets that enable further investigation of the assembly of mass. In this study we use ~3.2 million galaxies from the (South Pole Telescope) SPT-East field in the DES science verification (SV) dataset. From grizY photometry we derive galaxy stellar masses and absolute magnitudes, and determine the errors on these properties using Monte-Carlo simulations using the full photometric redshift probability distributions. We compute galaxy environments using a fixed conical aperture for a range of scales. We construct galaxy environment probability distribution functions and investigate the dependence of the environment errors on the aperture parameters. We compute the environment components of the galaxy stellar mass function for the redshift range 0.15<z<1.05. For z<0.75 we find that the fraction of massive galaxies is larger in high density environment than in low density environments. We show that the low density and high density components converge with increasing redshift up to z~1.0 where the shapes of the mass function components are indistinguishable. Our study shows how high density structures build up around massive galaxies through cosmic time