Active front-end (AFE) rectifiers have been becoming widely employed in power systems to achieve unity power factor and harmonic mitigations. The typical modeling approaches applied for AFE rectifiers in the literature mostly relied on two baselines named the detailed model and the time average model. The former approach deals with the switching element model (SEM) leads to significant harmonics in currents with distorted waveforms. The latter approach uses the average-value model (AVM) to overcome the currents’ harmonics as well as provide fast responses. However, even the AVM baseline has contained problems during the starting stage (lack of control signals) and over the dead-time periods which causes serious issues in the implementation process. This paper presents an improved dynamic AVM for AFE rectifiers by precisely considering the issues mentioned above along with the practical starting procedure and desirable initialization. The studied AFE rectifier is developed using the voltage-oriented control (VOC) technique based on the different modeling methodologies including SEM, Conventional AVM, and the proposed AVM. The performance of all models is analyzed and compared using simulation results with MATLAB/Simulink R2023a Function blocks for all the algorithm parts and SimScape elements for the electrical circuit model. The simulation results illustrate that the performance of the proposed AVM approach can closely resemble the behavior of the SEM baseline with low harmonic distortion.

Flux-switching permanent magnet (FSPM) motors have gained increasing attention in the electric vehicles (EVs) applications due to the advantages of high power density, high efficiency. However, the heat sources of both permanent magnet (PM) and armature winding are located on the limited stator space in the FSPM motors, which may result in the PM overheated and irreversible demagnetization caused by temperature rise and it is often ignored in the conventional thermal analysis. In this paper, a new electrical-thermal two-way coupling design method is proposed to analyze the electromagnetic performances, where the change of PM material characteristics under different temperatures is taken into consideration. Firstly, the motor topology and design equations are introduced. Secondly, the demagnetization curves of PM materials under different temperatures are modeled due to PM materials are sensitive to the temperature. And based on the electrical-thermal two-way coupling method, the motor performances are evaluated in details, such as the load PM flux linkage and output torque. Then, the motor is optimized, and the electromagnetic performances between initial and improved motors are compared. Finally, a prototype motor is manufactured, and the results are validated by experimental measurements.

The paper deals with two new properties of the linear time-optimal control problems with real non-positive eigenvalues of the system. They are the foundation of a new method of synthesizing the time-optimal control without the need to describe the switching hyper-surfaces. The so called “axes initialization” and the synthesis technique are illustrated on the already classical example of the time-optimal control of a double integrator.

The paper deals with one new property of the linear time-optimal control problems with real eigenvalues of the system, no matter of the number of eigenvalue multiplicity. This property unveils a prospective of synthesizing the time-optimal control without the need of describing the switching hyper-surfaces. The already chrestomathy example of the time-optimal control of a double integrator is resolved by the new technique and compared with the classical synthesis.

In this paper, we present a rigorous proof demonstrating the stabilization of percolation probability in supercritical regimes for percolation models. We analyze a sequence of expanding compact balls in ℝ௡, incorporating correction terms that vanish asymptotically, and show that the percolation probability within these regions converges to a finite, non‐zero value as the balls expand to cover the entire space. Our approach combines key concepts from percolation theory with measure‐theoretic tools, such as the Monotone Convergence Theorem and Fatouʹs Lemma, to rigorously establish the existence and uniqueness of the limiting percolation probability. The result extends classical results on percolation probability in lattice models and provides a new framework for understanding convergence in infinite systems. The non‐triviality of the limit is demonstrated in the supercritical regime, where percolation occurs with positive probability. The framework introduced here could serve as a bridge between discrete and continuous models in statistical physics

The process of developing therapies to treat rare diseases is fraught with financial, regulatory, and logistical challenges that have limited our ability to build effective treatments. Recently, a novel type of therapy called antisense therapy has shown immense potential for the treatment of rare diseases, particularly through single-patient N-of-1 trials. Several N-of-1 antisense therapies have been developed recently for rare diseases, including the landmark study of milasen. In response to the success of N-of-1 antisense therapy, the Food and Drug Administration (FDA) has developed unique guidelines specifically for the development of antisense therapy to treat N-of-1 rare diseases. This policy change establishes a strong foundation for future therapy development, and addresses some of the major limitations that previously hindered the development of therapies for rare diseases.

Transformer models have emerged as frontrunners in the field of natural language processing, primarily due to their adept use of self-attention mechanisms to grasp the semantic linkages between words in sequences. Despite their strengths, these models often face challenges in single-task learning scenarios, particularly when it comes to delivering top-notch performance and crafting strong latent feature representations. This challenge is more pronounced in the context of smaller datasets and is particularly acute for under-resourced languages such as Arabic. In light of these challenges, this study introduces a novel methodology for text classification of Arabic texts. This method harnesses the newly developed Reverse Positional Encoding (RPE) technique. It adopts inductive-transfer learning (ITL) framework combined with a switching self-attention shared encoder, thereby increasing the model's adaptability and improving its sentence representation accuracy. The integration of Mixture of Experts (MoE) and Reverse Positional Encoding (RPE) techniques empowers the model to process longer sequences more effectively. This enhancement is notably beneficial for Arabic text classification, adeptly supporting both the intricate five-point and the simpler ternary classification tasks. The empirical evidence points to its outstanding performance, achieving accuracy rates of 87.20% for the HARD dataset, 72.17% for the BRAD dataset, and 86.89% for the LABR dataset, as evidenced by the assessments conducted on these datasets.

Digital agricultural technology extension service and sustainable food production have attracted attention from academia. However, the association between digital agricultural technology extension service and sustainable food production has not yet been fully investigated. This research investigates the average and heterogeneous impacts of digital agricultural technology extension service use on eco-efficiency among 1302 maize producing farmers from Northeast China major maize producing area in 2022 to fill this knowledge gap. The slack-based measure model with undesirable outputs is applied to calculate the eco-efficiency of maize production. To obtain an unbiased estimation of the average effect, the self-selection problem generated by observable and unobservable factors is solved by the endogenous switching regression model. Quantile regression is utilized to analyze the heterogeneous effect. Notably, the mediated effects model is utilized to examine the potential mechanism between them. Our findings indicate that digital agricultural technology extension service use can increase maize production's eco-efficiency. Digital agricultural technology extension service users would reduce eco-efficiency by 0.148 (21.11%) if they had not used the digital agricultural technology extension service. Digital agricultural technology extension service nonusers would improve eco-efficiency by 0.214 (35.20%) if they had used it. The robustness check reconfirms the results. Moreover, digital agricultural technology extension service use is more helpful to maize farmers who have lower eco-efficiency than those who have higher eco-efficiency. Digital agricultural technology extension service use can improve eco-efficiency of maize production through the application of organic fertilizers, green pesticides and biodegradable agricultural films.

The present article addresses the long-standing problem of the polymer brush bilayers under stationary shear flow at non-linear response regime where the system gets a non-Newtonian fluid. The main idea behind this research would be the fact that the immense lubricity of the polymer brush bilayers originates from a global restructuring that takes place at large shear rates. It is shown here that physical quantities like, stress tensor, viscosity tensor, the friction coefficient and the chain extensions could become dependent on the shear rate at non-Newtonian regime. Apparently, the sub-linear scaling of the physical quantities at large shear rates is solely due to the fact that the chains stretch in the shear direction.

The main objective of the paper is to provide a thorough analysis of currently used modulation control schemes for single phase bidirectional dual active bridge DC/DC converter. In this article, it will be shown that single phase shift, extended phase shift and Dual phase shift modulation schemes are special cases of triple phase shift (TPS) modulation scheme. The article aims to highlight six TPS switching modes and their complements with the operational constraints. Unlike previous studies that regarded TPS as a complex scheme, this paper simplifies the analysis of each mode and aims to standardize the understanding of TPS modulation in DAB converters. Power equations, range of power transferred and zero voltage switching (ZVS) are derived for all the modes under TPS without assuming fundamental component analysis. Additionally, a generic optimization algorithm is developed to show the advantages of TPS modulation and thus, detailed analysis presented in this paper provides valuable insights for single phase DAB converter designers in identifying a wide range of optimization algorithms to achieve higher efficiency under TPS modulation. This analysis contributes to the advancement of bidirectional DAB converter technology and facilitates its application in various power electronic systems.

We reviewed various physical and biological manifestations of an unprecedented large-scale water temperature anomaly that emerged in the Northeast Pacific in late 2013. The anomaly dubbed “The Blob” persisted through 2014-2016, with some signs of its persistence through 2017-2018 and a possible reemergence in 2019. The tentative timeline of The Blob’s successive appearances around the Northeast Pacific is suggestive of its advection by currents around the Gulf of Alaska, along the Aleutians, into the Bering Sea, and eventually to the Bering Strait. During the initial phase of The Blob’s development in 2013-2014, advection along the Polar Front might have played a certain role. The extreme persistence and magnitude of The Blob resulted in numerous and sometimes dramatic ecosystem responses in the eastern Bering Sea. The multi-year duration of The Blob might have preconditioned the Bering Sea for the record low seasonal sea ice extent during the winter of 2017-2018 and disappearance of the cold pool in 2016 and 2018 that profoundly affected zooplankton, invertebrates, fishes, sea birds, and marine mammals. Comparison of time-series of population responses across trophic levels suggests that The Blob lowered primary production during spring, increasing small copepod production and jellyfish, and reducing energy transfer efficiently to higher trophic levels. While the Bering Sea’s water temperature, seasonal sea ice, and cold pool seem to return to the long-term mean state in 2022, it remains to be seen if the Bering Sea ecosystem will completely recover. The two most likely alternative scenarios envision either irreversible changes or hysteresis recovery.

Plasmonic nanocomposites have the ability to enhance light-matter interaction due to the plasmonic effects leading to promising potential applications. In this paper, we theoretically study the group index of the silver nanoparticle-gold nanoparticle-quantum dot plasmonic hybrid system in the optical region of the electromagnetic spectrum using the density matrix approach. The quantum dot is considered to be a three-level atomic system of a lambda configuration, interacting with strong control and weak probe fields. We find that the plasmonic hybrid system exhibits at near resonance a strong switching between slow and fast light, which can be controlled by the inclination angle of the gold nanoparticle and the size of the metals nanoparticles, in addition to the strength and detuning of the control field. Thus, the silver nanoparticle-gold nanoparticle-quantum dot could potentially be used in optoelectronic devices.

Humankind has entered a new era wherein a main characteristic is the convergence of various technologies providing services exerting major impact upon all aspects of human activity, be it social interactions as well as interactions with the natural environment. Fixed networks are about to play a major role in this convergence, since they form, along with mobile networks, the backbone that provides access to a broad gamut of services, accessible from any point of the globe. It is for this reason that we introduce a forward-looking approach for fixed networks, particularly focused on Fixed 6th Generation (F6G) networks. First, we adopt a novel classification scheme for the main F6G services, comprising six categories. This classification is based on the key service requirements, namely latency, capacity and connectivity. F6G networks differ from those of previous generations (F1G-F5G) in that they concurrently support multiple key requirements. We then propose concrete steps towards transforming the main elements of fixed networks, such as optical transceivers, optical switches etc. such that they satisfy the new F6G service requirements. Our study categorizes the main networking paradigm of optical switching into two categories namely ultra-fast and ultra-high capacity switching, tailored to different service categories. With regard to the transceiver physical layer, we propose: a) use of all-optical processing to mitigate performance barriers of analog to digital and digital to analog converters (ADC/DAC); b) exploitation of optical multi-band transmission, space division-multiplexing and adoption of more efficient modulation formats.

Antisense oligonucleotide (ASO)-mediated exon skipping has become a valuable tool for investigating gene function and developing gene therapy. Machine learning-based computational methods such as eSkip-Finder have been developed to predict the efficacy of ASOs via exon skipping. However, these methods are computationally demanding, and the accuracy of predictions remains suboptimal. In this study, we propose a new approach to reduce computational burden and improve prediction performance by using feature selection within machine learning algorithms and ensemble learning techniques. We evaluated our approach using a dataset of experimentally validated exon skipping events, dividing it into training and testing sets. Our results demonstrate that using a 3-way voting approach with random forest, gradient boosting, and XGBoost can significantly reduce computation time to under ten seconds while improving prediction performance, as measured by R2 for both 2’-O-methyl nucleotides (2OMe) and phosphorodiamidate morpholino oligomers (PMOs). Additionally, the feature importance ranking derived from our approach is in good agreement with previously published results. Our findings suggest that our approach has the potential to enhance the accuracy and efficiency of predicting ASO efficacy via exon skipping. It could also facilitate the development of novel therapeutic strategies. This study could contribute to the ongoing efforts to improve ASO design and optimize gene therapy approaches.

Antisense oligonucleotide (ASO)-mediated exon skipping has emerged as a powerful tool for examining the function of genes and exons in basic research, as well as gene therapy. Computational methods, such as eSkip-Finder, have been developed to predict the efficacy of ASOs via exon skipping using machine learning. However, these methods can be computationally demanding and the prediction accuracy of the tool is not yet optimal. In this study, we propose an approach to reduce computational burden and improve prediction performance by utilizing feature selection within machine learning algorithms and employing ensemble learning techniques. The method was evaluated using a dataset of genes with experimentally validated exon skipping events. The dataset was divided into training and testing sets to assess the accuracy of the algorithm. Our results demonstrate that using a 3-way voting approach with random forest, gradient boosting, and XGBoost can significantly reduce computation time to under ten seconds while improving prediction performance, as measured by R2 for both 2’-O-methyl nucleotides (2OMe) and phosphorodiamidate morpholino oligomers (PMOs). Additionally, the feature importance ranking derived from our approach is in good agreement with previously published results. These findings suggest that this approach has the potential to enhance the efficiency and accuracy of predicting ASO efficacy via exon skipping, facilitating the development of novel therapeutic strategies.

Molecule radiation can be used as a tool to study colder regions in switching arc plasmas like arc fringes in contact to walls and ranges around current zero (CZ). This is demonstrated in the present study for the first time for the case of ablation-dominated high–current arcs as key elements of self–blast circuit breakers. The arc in a model circuit breaker (MCB) in CO2 with and an arc in a long nozzle under ambient conditions with peak currents between 5 and 10 kA were studied by emission and absorption spectroscopy in the visible spectral range. The nozzle material was polytetrafluoroethylene (PTFE) in both cases. Imaging spectroscopy was carried out either with high-speed cameras or with intensified CCD cameras. A pulsed high-intensity Xe lamp was applied as background radiator for the broad-band absorption spectroscopy. Emission of Swan bands from carbon dimers was observed at the edge of nozzles only or across the whole nozzle radius with highest intensity in the arc center, depending on current and nozzle geometry. Furthermore, absorption of C2 Swan bands and CuF bands were found with the arc plasma serving as background radiator. After CZ, only CuF was detected in absorption experiments.

In recent years, numerous topologies of single phase and three phase Field Excited Flux-Switching Machine (FEFSM) have been developed for several applications. Comparative study of three types of single-phase low-priced Field Excited Flux-Switching Machine (FEFSM) is presented in this paper. Both the conventional 8S/4P sub-part rotor design and 6S/3P salient rotor design have an overlapped winding arrangements between armature coil and field excitation coil that depicts high copper losses as well as results in increased size of motor. Additionally, FEFSM with salient structure of the rotor have high flux strength in the stator-core that has much impact on high iron losses. Copper consumption and iron loss being a crucial proportion in total machine losses. Therefore a novel topology of single phase modular rotor field excited FSM with 8S/6P configuration is proposed, which enable non-overlap arrangement between armature coil and FEC winding that facilitates devaluation in the copper losses. The proposed modular rotor design acquires reduced iron losses as well as reduced active rotor mass comparatively to conventional rotor design. It is very persuasive to analyze the best range of speed for these rotors to avoid cracks and deformation, the maximum tensile strength (can be measured with principal stress in research) of the rotor analysis is conducted using JMAG. A deterministic optimization technique is used to enhance the performance of 8S/6P modular rotor design. The electromagnetic performance of conventional sub-part rotor design, F1-A3-3P design and proposed novel-modular rotor design are analyzed by 3D-Finite Element Analysis (3D-FEA), includes flux linkage, flux distribution, flux strength, back-EMF, cogging torque, torque characteristics, iron losses and efficiency.

In computer networks, loss of data packets is inevitable, in particular, because of the buffer memory overflow of at least one of the nodes located on the path from the source to the receiver, including the latter. Such losses associated with overflows are hereinafter referred to as congestion of network nodes. There are many ways to prevent and eliminate overloads; these methods, in the majority, are based on the management of data flows. A special place is taken by the maintenance of packages, taking into account their priorities. The article considers a number of original technical solutions to improve the quality of control and reduce the required amount of buffer memory of network nodes. The ideas of these solutions are quite simple for their implementation in the development of appropriate software and hardware for telecommunication devices.

A review is here provided about the thermal effects on the optical chirality. To this goal, chiral objects dispersed in an embedding fluid are examined for their magnetoelectric coupling. Thermal effects on several chiral meta-atoms and their ensembles are examined. To this goal, DNA-like helical structures are examined in detail. Mechanical aspect of thermo-elasticity is reviewed along with transverse deformations, while drawing analogies from condensed-matter physics. In this respect, chirality-induced spin selection is reviewed along with the temperature-mediated elec-tron-phonon interactions. A wide range of materials such as polymers and biological cells are also examined for temperature effects. A transition temperature delineating a sign flip in the chirality parameter is identified as well. Chirality-associated functionalities such as ratchet motions, switching, and modulations are investigated for their respective thermal effects. Issues of fabri-cating chiral meta-atoms are also discussed.

A review is here provided on the thermal effects on the optical chirality. To this goal, chiral objects dispersed in an embedding fluid are examined for their magnetoelectric coupling. Archetypal twisted-Omega particles are examined with respect to electron transport, phonon dynamics, and temperature effects. Continuum-mechanical aspect of thermo-elasticity is reviewed along with transverse deformations. A transition temperature delineating a sign flip in the chirality parameter is identified as well.

Full-order state-space models represent the starting point for the development of advanced control methods for wind turbine systems (WTSs). Regarding existing control-oriented WTS models, two research gaps must be noted: (i) There exists no full-order WTS model in form of one overall ordinary differential equation that considers all dynamical effects which significantly influence the electrical power output; (ii) all existing reduced-order WTS models are subject to rather arbitrary simplifications and are not validated against a full-order model. Therefore, in this paper, two full-order nonlinear state-space models (of 11th and 9th-order in the (a, b, c)- and (d, q)-reference frame, resp.) for variable-speed variable-pitch permanent magnet synchronous generator WTSs are derived. The full-order models cover all relevant dynamical effects with significant impact on the system’s power output, including the switching behavior of the power electronic devices. Based on the full-order models, by a step-by-step model reduction procedure, two reduced-order WTS models are deduced: A non-switching (averaging) 7th-order WTS model and a non-switching 3rd-order WTS model. Comparative simulation results reveal that all models capture the dominant system dynamics properly. The full-order models allow for a detailed analysis covering the high frequency oscillations in the instantaneous power output due to the switching in the power converters. The reduced-order models provide a time-averaged instantaneous power output (which still correctly reflects the energy produced by the WTS) and come with a drastically reduced complexity making those models appropriate for large-scale power grid controller design.

The Ramsey theory based approach to the phase transitions of the second order is suggested. The phase transitions of the second order are seen as switching of physical interactions/chemical bonds between the entities forming the primitive cell of the material. Such a switching is typical for a phase change materials. If the energy of the primitive cell is kept constant under the change in the spatial order of the chemical bonds, the phase transition of the second order takes place. The switching of interactions between the entities forming the primitive cell is accompanied by the breaking of the initial symmetry of the cell. The order parameter/the degree of ordering characterizing the ordering within the primitive cell is re-defined. The introduced degree of ordering quantifies ordering of links/interactions/chemical bonds between entities constituting the 2D lattice; whereas, the classical “Landau degree of order” quantifies the symmetry breaking under variation in spatial locations of these entities. The suggested approach is generalized easily for 3D primitive cells. Thermal capacity of the non-symmetrical phase is larger than that of the symmetrical phase. For the primitive cells built of six interacting entities, the Ramsey Theory predicts inevitable appearance of the unstable monochromatic triangles, when the links correspond to attraction or repulsion interactions. The situation becomes different for the primitive cells built of five interacting entities.

This study examines Brazil's complex economic journey from 1930 to 2000, exploring the interplay between historical legacies, policy choices, and global economic forces in shaping the nation's development trajectory. It argues that Brazil's economic history during this period is characterized by a series of paradoxes: rapid industrialization alongside persistent inequality, economic miracles followed by devastating crises, and modernization efforts constrained by colonial-era structures. The analysis begins with the Estado Novo of Getúlio Vargas, tracing the evolution of Brazil's economy through state-led industrialization, the "Economic Miracle" of the military regime, the debt crisis and hyperinflation of the 1980s, and the neoliberal reforms of the 1990s. Special attention is given to the enduring impact of slavery and colonial land distribution on Brazil's social and economic structures. The study highlights how these historical factors have contributed to ongoing challenges such as regional disparities, income inequality, and the "Brazil Cost." By examining these issues, the paper provides insights into the complexities of economic development in postcolonial societies and the challenges of overcoming historical constraints in the pursuit of equitable and sustainable growth.

This paper explores the Wilsonian renormalization group of probe-D-branes, focusing on the Dirac-Born-Infeld (DBI) action. The analysis involves deriving the constant of motion and formulating the Wilsonian renormalization group equation. The study extends to the infrared regime, considering both zero and non-zero temperatures. Additionally, thermodynamic aspects related to the functional form of the grand potential are discussed. The investigation provides insights into the renormalization of probe-D-branes and their thermodynamic properties.