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In traditional magnetic bearing motors, the magnetic bearing and the motor are usually driven and controlled separately, resulting in higher controller costs and limiting further expansion of their applications. The author presents a four‐degree‐of‐freedom (4DOF) magnetic bearing switched reluctance motor (MBSRM), consisting of two 8‐pole active radial magnetic bearings (RMBs) and two two‐phase 4/2‐pole switched reluctance motors (SRMs), driven simultaneously by a set of asymmetrical power converters together. Firstly, the structure, winding configuration and co‐excitation working principles of the 4DOF‐MBSRM system are described in detail. Then the radial force formula for an 8‐pole RMB and the torque mathematical model for a 4/2‐pole SRM are briefly derived based on equivalent magnetic circuits, respectively. Furthermore, a co‐excitation control strategy for the 4DOF MBSRM is developed wherein an instantaneous radial force is used to control its rotor shaft levitation, an instantaneous torque is employed for rotational control at low and medium speeds, and an average torque is used for high speed operation. Finally, the good performance of the co‐excitation control for the proposed 4DOF‐MBSRM is proved by simulation analysis. [ABSTRACT FROM AUTHOR]

The control of electric drives is an important topic due to the wide-spread use of such devices. Among these, multi-phase induction machines are gaining momentum in variable-speed applications. The usual control practice is the use of a speed Proportional–Integral loop that sets the current reference for an inner controller. This inner controller decides the voltage to be applied, which is realized by an electronic power converter. This paper presents an Artificial Intelligence (AI) scheme for tuning. It aims to optimize the usual figures of merit for drives. Moreover, tuning for both loops is tackled concurrently. The adjustment is performed relying on the operating region to address non-linear behavior. The results obtained using a five-phase induction motor illustrate that the proposed method can work in the entire operating range of the drive with improved results. [ABSTRACT FROM AUTHOR]

This article draws on comparative ethnography undertaken in a Malian train station where trains no longer circulate, and a market in Burkina Faso where the flow of customers has ebbed away. In doing so, we explore how workers deal with protracted economic and security crises that have eroded their working lives and thrown the meaning of their labour into question. In both sites, the primarily male workers perpetuated their routines, not only to sustain their workplaces but also to maintain both a sense of a meaningful working life and their masculine identity as breadwinners. They thereby aim to preserve the hope that trains and customers might one day return, restoring their work lives to their previous productive states. We focus on how workers engage in various rhythms of care to 'stay put' amidst an uncertain present, and an even more precarious future. Through acts of mutual support – assisting fellow workers, giving intergenerational advice, offering emotional support through religious care and food-sharing, and tending to the material conditions of their workplaces – they create a network of care grounded in both social and physical infrastructure. By analysing the ways in which workers care for each other and their space of work, this article sheds light on the ways masculine affective caring underpins their struggle to 'stay put' and continue deriving value from labour, even when this may appear difficult or impossible from the outside. In doing so, this dual case study illuminates ambiguous relationships between work and meaning, crisis and normalcy, and masculinity and care. [ABSTRACT FROM AUTHOR]

Conventional predictive position control (PPC) method balances the position, speed and current of permanent magnet synchronous machine with different weighting factors. However, tedious tuning work of weighting factors is needed. To simplify the tuning process, a cost function that includes the system position, and current information is constructed based on deadbeat control method. A novel method based voltage boundary is proposed to limit the current and speed simultaneously, the voltage regions corresponding to current and speed constraints are analyzed and the voltage duty cycle is further modified according to the voltage regions, the complex weighting factor turning work is avoided, the current and speed limits are easy to implement with proposed method and less position error can be achieved. Finally, the proposed method is experimentally compared with a conventional finite-control-set PPC method and a direct speed model predictive control method. [ABSTRACT FROM AUTHOR]

We propose a simple non-supersymmetric grand unified theory (GUT) based on the gauge group S O (10) × U (1) ψ . The model includes 3 generations of fermions in 16 ( + 1 ), 10 ( - 2 ) and 1 ( + 4 ) representations. The 16 -plets contain Standard Model (SM) fermions plus right-handed neutrinos, and the 10 -plet and the singlet fermions are introduced to make the model anomaly-free. Gauge coupling unification at M GUT ≃ 5 × 10 15 - 10 16 GeV is achieved by including an intermediate Pati–Salam breaking at M I ≃ 10 12 - 10 11 GeV, which is a natural scale for the seesaw mechanism. For M I ≃ 10 12 - 10 11 , proton decay will be tested by the Hyper-Kamiokande experiment. The extra fermions acquire their masses from U (1) ψ symmetry breaking, and a U (1) ψ Higgs field drives a successful inflection-point inflation with a low Hubble parameter during inflation, H inf ≪ M I . Hence, cosmologically dangerous monopoles produced from SO(10) and PS breakings are diluted away. This is the first SO(10) model we are aware of in which relatively light intermediate mass ( ∼ 10 10 - 10 12 GeV) primordial monopoles can be adequately suppressed. The reheating temperature after inflation can be high enough for successful leptogenesis. With the Higgs field contents of our model, a Z 2 symmetry remains unbroken after GUT symmetry breaking, and the lightest mass eigenstate among linear combinations of the 10 -plet and the singlet fermions serves as a Higgs-portal dark matter (DM). We identify the parameter regions to reproduce the observed DM relic density while satisfying the current constraint from the direct DM detection experiments. The present allowed region will be fully covered by the future direct detection experiments such as LUX-ZEPLIN DM experiment. In the presence of the extra fermions, the SM Higgs potential is stabilized up to M I . [ABSTRACT FROM AUTHOR]

In this study, simultaneous generation and transmission expansion planning is presented in the presence of wind farms. Short-circuit current constraint is included in the problem, and the impact of wind farms on short-circuit current is evaluated. This study presents a novel approach for reducing short-circuit current in composite generation and transmission expansion planning. In this way, new units and lines are determined such that the short-circuit currents of substations are less than the defined limit. In addition, an optimal level of short circuit is determined and the total cost is reduced. The proposed method is applied to a real case study, and its performance is demonstrated by comparison with other methods. [ABSTRACT FROM AUTHOR]

More and more distributed generations are connected in the distribution network. Intermittent output and different locations have a significant impact to the distribution network voltage, current, power flow, the traditional forward and backward substitution is unable to solve PV-type node and meshed network, the distributed generations increase the number of network constraints and increase the difficulty of searching the optimal solution. To solve the problem of classic self-healing method failure, based on the multi-agent system, a novel self-healing reconfiguration scheme is proposed for distribution network with distributed generations in this study. Multiple objectives are considered for minimum distributed generation output loss, minimum power loss, load balancing among the feeders and branch current constraint violation, improved forward-backward weep method is used to get power flow solution for different node types of distributed generations, a self-adaptive differential evolution algorithm with improved strategies is proposed to solve problem. The performance of proposed algorithm is analyzed for several case studies on IEEE 33-bus system. The simulation results show that the approach can improve the self-healing reconfiguration performance and adapt to the changes of dynamic conditions. [ABSTRACT FROM AUTHOR]

Different from the synchronization mechanism of synchronous generators, the non-synchronous generators must be synchronized with the grid through a controller. Generally, the virtual synchronous generator (VSG) control strategy is adopted for this purpose. In view of the current situation, where the control loops are not comprehensively considered in the research of the synchronization stability of the VSG, this paper considers multiple control loops, such as active frequency loops, virtual governors, power filters and current constraint control, to establish the mathematical model of the VSG and infinite system. On this basis, the correlation formula between power angle difference and control parameters is deduced. Adopting the phase plane method, the influence of different control loops and their parameters on the transient synchronization stability is analyzed. Finally, a setting principle of the frequency modulation coefficient of virtual governors is proposed, which not only meets the response speed of control systems, but also has good control performance. Key words: control parameters, frequency modulation coefficient, phase plane method, synchronization stability, virtual synchronous generator [ABSTRACT FROM AUTHOR]

Constrained multi-objective evolutionary algorithms (CMOEAs) can deal with multiple conflicting objective functions and constraints simultaneously and guide the population towards the optimal solution in the feasible domain, which has received extensive attention from researchers. This paper firstly introduces the relevant definitions of constrained multi-objective optimization problems (CMOPs) and three classifications of multi-objective evolutionary algorithms (MOEAs); secondly, it systematically analyzes the current constraint processing mechanisms in CMOEAs, and condenses the current four main constraint processing methods; Then, the research progress of CMOEAs is reviewed in detail from three aspects: dominance-based, index-based, and decomposition-based; finally, the challenges and future research directions of CMOEAs are pointed out. [ABSTRACT FROM AUTHOR]

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The quench of a superconducting magnet in a high magnetic field environment causes irreversible damage to the magnet. A 32.4 T completely superconducting magnet consisting of a low-temperature superconducting (LTS) external magnet and a high-temperature superconducting (HTS) inserting magnet was developed and tested. The LTS external magnet quickly discharged after quenching when the system's peak center magnetic field reached 32.4 T. The inserting magnet, particularly the Coil 1 magnet on the magnet's innermost side, was damaged due to the quick current change in the LTS external magnet. This created a significant current inside the HTS magnet due to the mutual inductance effect. The overcurrent caused the degradation of Coil 1 magnet. The continuous critical current of DP69, DP80, DP85, and DP94 in the magnet was measured to investigate the degradation. Numerous circular burn sites in areas of degraded critical current were observed by optical and scanning electron microscopy (SEM). To analyze the causes of the degradation, a dynamic coupling model of LTS and HTS magnet during quench was developed. The simulation outcomes indicated that the locations exhibiting high hoop stress correspond to those where the normalized critical current density is observed to be notably low, proving that excessive hoop stress is the main reason for the critical current degradation in the coils. Furthermore, the model quantified the turn-to-turn loss in the Coil 1 magnet during the quenching process of the LTS magnet. It offered potential evidence for the circular burn-through points in the superconducting layer. [ABSTRACT FROM AUTHOR]

In this paper, we will give a general introduction to the Ali CMB Polarization Telescope (AliCPT) project, which is a Sino–US joint project led by the Institute of High Energy Physics and involves many different institutes in China. It is the first ground-based Cosmic Microwave Background (CMB) polarization experiment in China and an integral part of China's Gravitational-wave Program. The main scientific goal of the AliCPT project is to probe the primordial gravitational waves (PGWs) originating from the very early Universe. The AliCPT project includes two stages. The first stage, referred to as AliCPT-1, is to build a telescope in the Ali region of Tibet at an altitude of 5250 meters. Once completed, it will be the highest ground-based CMB observatory in the world and will open a new window for probing PGWs in the northern hemisphere. The AliCPT-1 telescope is designed to have about 7000 transition-edge sensor detectors at 95 GHz and 150 GHz. The second stage is to have a more sensitive telescope (AliCPT-2) with more than 20 000 detectors. Our simulations show that AliCPT will improve the current constraint on the tensor-to-scalar ratio r by one order of magnitude with three years' observation. Besides the PGWs, AliCPT will also enable a precise measurement of the CMB rotation angle and provide a precise test of the CPT symmetry. We show that three years' observation will improve the current limit by two orders of magnitude. [ABSTRACT FROM AUTHOR]

In engineering practical implications, assembly simulation is a useful solution to test the planned assembly process and address assembly issues. However, it is usually carried out by time-consuming human-computer interaction, which causes a lot of unavoidable laborious work. Assembly simulation could exhibit the design intent in virtual environment through the interactions between parts. Unfortunately, the models which modeled with current constraint-based method cannot provide sufficient interaction information to support assembly simulation, and the needed information should be added by designers manually. To solve this problem, this paper introduces the concept of interaction feature pair (IFP) and presents an automatic assembly simulation method based on IFP. The proposed IFP provides a form that endues a part with the capability of knowing which part is going to interact with and how to interact. Based on IFP, the automatic assembly simulation is carried out in two steps: First, a graph-based method in presented to generate the interaction sequence, which provides the information that when and which feature should be mated during assembly. Then, the randomized motion planning is employed in the established C-space to find a collision-free path for each part, and the planning results in C-space are transferred into the movements of parts in simulation environment. With these two steps, the parts could interact with other parts under a certain interaction sequence, which automatically simulates the assembly of the product. Finally, an implementation sample is presented and the results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the increased use of high voltage direct current (HVDC) systems, line commutated converters (LCC-HVDC) and voltage source converters (VSC-HVDC) tend to feed into AC systems over short electrical distances. The flexible power control of VSC-HVDC systems provides an effective approach to suppress the commutation failure of LCC-HVDC systems. A suppression method, based on a controllable operation region, is proposed in this study to reduce the probability of commutation failure in a hybrid dual-infeed HVDC system. First, the quantitative transient reactive power control requirement of VSC-HVDC inverter that could fulfill the suppression control boundary condition of commutation failure was analyzed. Given the maximum current constraint of the VSC-HVDC inverter and the primary frequency modulation constraint of the sending-end grid, a controllable operation region of the hybrid dual-infeed HVDC system was proposed. Furthermore, a commutation failure suppression control method, based on the controllable operation region, was proposed to mitigate continuous commutation failure. Finally, the validity and accuracy of the proposed method was verified by the simulation of PSCAD/EMTDC. The proposed control method can realize reasonable use of the reactive power control capability of the VSC-HVDC system, which effectively improves immunity to commutation failure of the LCC-HVDC system under grid fault. [ABSTRACT FROM AUTHOR]

The thriving of high-voltage direct current transmission for hydropower tackles supply-demand imbalances but complicates grids safety, especially concerning the related challenges of varying numbers of hydroelectric units operating, including the effects of discrete rectifier station altering current and vibration zones with minimum numbers of hydroelectric units operating. Here, a mixed integer linear programming model considering high-voltage direct current safety constraints for daily peak-shaving of cascade hydropower plants serving multi-grids is proposed to address these challenges. First, the model integrates the altering current constraint across multiple intervals to ensure stable operation following the passive transition of the direct current terminal into islanded system state. Second, a power distribution strategy considering load differences is adopted to compensate for shortcomings of traditional peak shaving treatments for multiple grids to achieve effective results. Finally, a method for linearizing the segmented vibration zones of hydropower station with minimum numbers of units operating is adopted during model solving to ensure that the model meets safe specifications. The case study indicates that besides guaranteeing the proposed security constraints, the model reduces the average distance by 30.4 % and 30.3 % during the dry and flood seasons, respectively, with better calculation time and variance of the residual load. [ABSTRACT FROM AUTHOR]

This article presents an optimal current flow (OCF) technique for analyzing distribution systems with renewable energy generation. The overall aim of this study is to reduce the complexity of the traditional nonlinear models by representing the problem as a quadratic optimization network flow model with linear constraints. The objective of the OCF method is minimization of renewable generation costs with or without consideration of transmission losses. Taking advantage of the topological characteristic of the distribution system, the network constraints are represented by Kirchhoff current and voltage laws. In addition, the model considers the capacity limits of the distribution components (renewable generators, transformers and lines current flow). The robustness and fastness of the OCF method is tested on 34-bus, 69-bus, and 400-bus systems under balanced and unbalanced, conditions and in radial or meshed distribution systems under different load scenarios. The results demonstrate the accuracy, and efficiency of the proposed approach in determining the optimal operation of a distribution system with renewable energy generation. [ABSTRACT FROM AUTHOR]

Current stress and soft switching range are important performance indexes of dual active bridge DC–DC converter. Based on three‐phase shift control, Karush–Kuhn–Tucker (KKT) algorithm is used to solve the optimal control strategy of current stress under soft switching conditions, and the interval construction method that KKT cannot solve is given. Aiming at the problem that all or most of the switching devices lose the zero voltage switching (ZVS) soft switching characteristics when the current dual active bridge (DAB) modulation strategy is seriously mismatched in voltage gain or when the output power is relatively small, an optimized modulation strategy is proposed here, which not only realizes the minimum current stress within the full power range, but also ensures that at least six switching tubes can achieve ZVS on–off. The on‐state and switching losses of the system are further reduced, and the transmission efficiency of the converter is improved. [ABSTRACT FROM AUTHOR]

The integration of large‐scale distributed power sources increases the voltage fluctuation in AC/DC hybrid distribution network (AD‐HDN). Power electronics devices such as photovoltaic (PV) inverters, soft open point (SOP), and voltage source converters (VSCs) can be utilized for voltage/var control (VVC) to alleviate the risk of voltage fluctuation and violation. This paper proposes a distributed optimal VVC method in power electronics dominated AD‐HDN. Firstly, the reactive power and voltage characteristics of PV inverters, SOP, and VSCs are analysed, and an optimal VVC optimization model for AD‐HDN to minimize node voltage deviation, PV curtailment, and network loss is proposed. Then, the second‐order cone (SOC) relaxation technique is used to re‐formulate the model into a convex optimization model. A distributed optimal VVC framework based on the alternating direction method of multipliers (ADMM) is constructed. Based on the residual balance principle and relaxation technique, an accelerated ADMM method is further proposed to solve the proposed model. Finally, case studies are conducted on the IEEE 33‐node and 85‐node systems to verify the superiority and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The battery energy storage system (EES) deployed in power system can effectively counteract the power fluctuation of renewable energy source. In the planning and operation process of grid side EES, however, the incorporation of power flow constraints into the optimization problem will strongly affect the solving efficiency. Therefore, a bi‐level planning and operation co‐optimization model for EES is proposed based on a constraint boundarization technique. Firstly, a constraint boundarization method for considering power flow constraints is proposed to solve the efficiency problem of the optimization model. Secondly, in terms of the upper and lower bounds of storage's operation curve obtained by the constraint boundarization method, an operation risk evaluation index is defined to describe the potential risk of storage planning scheme. Thirdly, this paper establishes a bi‐level planning and operation co‐optimization model for EES, in which the planning problem with a goal of minimizing total cost is taken as an outer layer and the operation problem for pursuing renewable energy consumption and reducing the load curtailment is taken as an inner layer. Finally, case studies are carried out, and results demonstrate the feasibility and effectiveness of the proposed model and method. [ABSTRACT FROM AUTHOR]

In a complex and dynamic battlefield environment, enabling autonomous underwater vehicles (AUVs) to reach dynamic targets in the shortest possible time using global autonomous planning is a key issue affecting the completion of search tasks. In this study, ahierarchicalAUV task planning method that uses a combination of hierarchical programming and a snake optimization algorithm is proposed for two typical cases where the platform can provide initial target information. This method decomposes the search task problem into a three-level programming problem, with the outer task planning goal of achieving the shortest encounter time between AUV and dynamic targets; the goal of task planning in the middle layer is to achieve the shortest actual navigation time for AUVs under different operating conditions; and the internal task planning is responsible for considering the comprehensive trajectory optimization under navigation constraints such as threat zone, path length, and path smoothness. The snake optimization algorithm was used for solving each layer of task planning. The feasibility of the proposed method was verified through simulation experiments of AUV search tasks under two types of initial target information conditions. The simulation results show that this method can achieve task planning for AUV searching for dynamic targets under various constraint conditions, optimize the encounter time between AUV and dynamic targets, and have strong engineering practical value. It has certain reference significance for task planning problems similar to underwater unmanned equipment. [ABSTRACT FROM AUTHOR]

A dc voltage restorer (dc‐VR) with optimal droop control is developed to reduce the power loss and solve the dynamic current imbalance simultaneously of the zonal dc distribution system integrating multi‐parallel energy storage. Firstly, the power loss model composed of line loss and converter loss is built and it is proved to be a strictly convex function with respect to droop coefficients, which indicates the power loss can be mitigated by optimizing the current distribution. Thus, an image‐based droop optimization method is proposed to search for the optimal droop coefficients. Then, the economy of voltage compensation on power loss reduction is investigated and an ESS‐combined dc‐VR is designed, including an interleaved parallel architecture and a capacitor‐integrated electric spring (C‐ES). Unified virtual inertia is proposed for interleaved parallel bridge arms to make their dynamic performance consistent. And the newly introduced C‐ES can keep the bus voltage at the rated level to reduce the system cost. Therefore, the problem of dynamic currents imbalance is addressed from the points of converter structure (dc‐VR) and control system (unified inertia), and the power loss can be reduced by voltage recovery (C‐ES) and optimizing the current reallocation which is achieved by updating sharing coefficients from the image‐based droop optimization method. Finally, the simulation cases validate the effectiveness of the proposed optimal‐droop dc‐VR on dynamic current balance and power loss reduction, and hardware in the loop experiment results prove the consistent dynamic characteristics of the dc‐VR's arms. [ABSTRACT FROM AUTHOR]

To address the impact of load disturbances on the full-speed-range control of an interior permanent magnet synchronous motor (PMSM), an active disturbance rejection control (ADRC) method is proposed. The speed loop employs phased field-weakening control (FW) based on ADRC, while the current loop utilizes proportional-integral-derivative (PID) control. Starting from the motor parameters, the Lagrange multiplier method was used to derive the critical speeds for the maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) ratios, and the timing for the field-weakening control was analyzed. A full-speed-range control model of the motor was established, and an ADRC-based speed loop controller was designed to achieve smooth transitions between high speeds and anti-disturbance solid capabilities. Based on the proposed control strategy, a 21 kW PMSM was used as the research object, and a full-speed-range control simulation model was developed in MATLAB/SIMULINK to verify the strategy. Compared to the traditional PID control, the simulation results demonstrate that the proposed strategy effectively observes and compensates for load disturbances, significantly reducing initial torque oscillations under three different operating conditions. After a sudden load increase, torque oscillations were reduced by 16%, with the stator current reaching steady state 0.03 s faster, response speed improving by 0.02 s, smooth transitions between speed ranges, and enhanced anti-disturbance performance. [ABSTRACT FROM AUTHOR]

Due to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII‐MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33‐node system with the DCDNs is validated under different scenarios. The hybrid NSGAII‐MOPSO performs better in obtaining the Pareto front than the NSGA‐II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed. [ABSTRACT FROM AUTHOR]

As LHC’s Run3 unfolds, we peer deeper into the couplings of the 125GeV Higgs (h125) and also test for extra scalars. Even before such extra scalars are found, one can probe them by using the fact that theories with multiple Higgs doublets allow for substantial deviations of the couplings of h125 from their SM values. Indeed, the observed couplings already place stringent limits on such theories. We investigate the curious possibility that h125 couples to the top quark mostly as a scalar, while it couples to the bottom quark mostly as a pseudoscalar. This possibility was allowed by 2017 data for the so-called C2HDM; a two Higgs doublet model with a single source of explicit CP violation. It was shown recently that this possibility disappears when using the full experimental data of 2024. Here we discuss a three Higgs doublet with explicit CP violation (C3HDM), and show that the curious CP-even/CP-odd t/b possibility is partly resuscitated, prompting further experimental exploration of this prospect. [ABSTRACT FROM AUTHOR]

The engineering of actuation systems for active exoskeletons presents a significant challenge due to the stringent demands for mass reduction and compactness, coupled with complex specifications for actuator dynamics and stroke length. This challenge is met with a model-based methodology. Models for human body, exoskeleton and parametric actuation systems are derived and coupled. Beginning with an inverse dynamics human body simulation, loads in human joints are estimated, and the corresponding support torques are derived. Under the assumption of a control law ensuring these support torques, an optimization problem is stated to determine actuation system parameters such as the number of stator coils and number of battery cells. Lastly, results from the optimization are validated using sophisticated models. The methodology is applied to an exemplary exoskeleton and compared to an approach derived from previous studies. [ABSTRACT FROM AUTHOR]

This paper proposes a fixed-time disturbance observer-based funnel control method for a controllable excitation linear synchronous motor (CELSM) with state constraints and disturbances. This approach simultaneously resolves the issues of prescribed tracking performance and state constraints, taking into account disturbances. We employ a fixed-time disturbance observer (DO) to estimate both matched and mismatched disturbances. Additionally, we design a modified funnel variable to confine the tracking error within a prescribed region and the singularity problem is avoided. An integral barrier Lyapunov function (iBLF) is utilized to directly tackle state constraints. Furthermore, we employ a fixed-time differentiator (FTD) to address the "explosion of complexity" issue in backstepping control. Theoretical analysis demonstrates that the tracking error asymptotically converges to the origin within a prescribed region while satisfying state constraints. Finally, simulation results demonstrate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

Short-range gravity experiments are more suitable for the testing of high-order Lorentz symmetry breaking effects. In our previous work, we proposed a new experimental design based on precision torsion balance technology to test the Lorentz violation force effect that varies inversely with the fourth power of distance (corresponding to mass dimension d = 6 term), and the corresponding experiment is currently underway. In this paper, we focus on analyzing the potential of this experimental scheme to test the Lorentz violation force that varies inversely with the sixth power of distance (corresponding to mass dimension d = 8 term). The results show that, compared with the current best limit, the new experimental scheme can improve the constraints on the Lorentz violation coefficients with d = 8 by at least one order of magnitude. [ABSTRACT FROM AUTHOR]

One of the fundamental problems of spacecraft dynamics related to ensuring its angular orientation in the basic coordinate system is considered. The problem of electrodynamic attitude control for a spacecraft in an elliptical near-Earth Keplerian orbit is studied. A mathematical model describing the attitude dynamics of the spacecraft under the action of the Lorentz torque, the magnetic interaction torque, and the gravitational torque is constructed. The multipole model of the Earth's magnetic field is used. The possibility of electrodynamic attitude control for the spacecraft's angular stabilization in the orbital frame is analyzed based on the Euler–Poisson differential equations. The problem of electrodynamic compensation of disturbing torque due to the orbit eccentricity is solved. The control strategy for spacecraft electrodynamic attitude stabilization is presented. Electromagnetic parameters that allow stabilizing the spacecraft's attitude position in the orbital frame are proposed. The disturbing gravity gradient torque is taken into account. The convergence of the control process is verified by computer modeling. Thus, the possibility and advisability of using the electrodynamic method for the spacecraft attitude control and its angular stabilization in the orbital coordinate system in an elliptical orbit is shown. [ABSTRACT FROM AUTHOR]

With the increasing penetration of electric vehicles (EVs) in road traffic, the spatial and temporal stochasticity of the travel pattern and charging demand of EVs as a mode of transportation and an electrical load have generated different degrees of congestion impacts on both the power grid and the transportation network. Based on this, this paper proposes a power–transportation-coupled distribution network optimization strategy based on stochastic user traffic equilibrium theory. First, a stochastic user equilibrium-mixed traffic flow allocation model that expresses user non-completely rational path selection behavior is established, and the traffic flow equilibrium solution is obtained using an improved method of successive algorithm and mapped to charging loads. Second, a distribution network power flow optimization model under the coupled power–transportation architecture is established to optimize the operation state of the distribution network by combining distributed resources such as energy storage, demand response loads, wind power, photovoltaic, and gas turbines. [ABSTRACT FROM AUTHOR]

The 3D bioprinting technique has made enormous progress in tissue engineering, regenerative medicine and research into diseases such as cancer. Apart from individual cells, a collection of cells, such as organoids, can be printed in combination with various hydrogels. It can be hypothesized that 3D bioprinting will even become a promising tool for mechanobiological analyses of cells, organoids and their matrix environments in highly defined and precisely structured 3D environments, in which the mechanical properties of the cell environment can be individually adjusted. Mechanical obstacles or bead markers can be integrated into bioprinted samples to analyze mechanical deformations and forces within these bioprinted constructs, such as 3D organoids, and to perform biophysical analysis in complex 3D systems, which are still not standard techniques. The review highlights the advances of 3D and 4D printing technologies in integrating mechanobiological cues so that the next step will be a detailed analysis of key future biophysical research directions in organoid generation for the development of disease model systems, tissue regeneration and drug testing from a biophysical perspective. Finally, the review highlights the combination of bioprinted hydrogels, such as pure natural or synthetic hydrogels and mixtures, with organoids, organoid–cell co-cultures, organ-on-a-chip systems and organoid-organ-on-a chip combinations and introduces the use of assembloids to determine the mutual interactions of different cell types and cell–matrix interferences in specific biological and mechanical environments. [ABSTRACT FROM AUTHOR]

Environmental deoxyribonucleic acid (eDNA) metabarcoding offers advantages over physical capture for identifying and quantifying animals in monitoring programs. In this study, the fish community was sampled at three stations (inner, middle, and outer estuary) in three estuaries in August 2020, and four estuaries in June and August 2021 (Prince Edward Island, Canada) using both beach seining and eDNA metabarcoding. Two 12S primer sets, 12S-160 and 12S-248F, with different amplicon lengths, yielded similar results. eDNA metabarcoding consistently detected species captured by 186 co-located beach seines and revealed additional species. It also detected monthly (June–August), interannual (2020–2021), and spatial shifts in the fish community, distinguishing stations separated by as little as 0.4 km. Positive correlations existed between eDNA metabarcoding species reads and beach seining captures. These findings suggest eDNA metabarcoding complements physical capture methods for characterizing nearshore fish communities in Prince Edward Island's estuaries. While eDNA techniques lack certain population parameter information provided by physical methods, such as size, sex, and age structure, they offer a more comprehensive diversity assessment and presence–abundance insights, especially in inaccessible environments. [ABSTRACT FROM AUTHOR]

Paint-free bodywork has become an attractive alternative for rail vehicles, in the direction of easy maintainability and low manufacturing costs. However, conventional resistance spot welding inevitably leaves indentation marks to detrimentally reduce the optical homogeneity of the paint-free bodywork. In light of this, indentation-free resistance spot welding is proposed for joining SUS301L stainless steel sheets in order to achieve superior surficial integrity. A tiny SUS301L steel ball with a diameter of 1.5 mm was chosen as the intermediate filler between two steel sheets to avoid the formation of surficial indentation. The influence of welding current and welding time on the mechanical properties of joints was studied. The optimal parameters of the mechanical properties were obtained when the welding current was 8.0 kA, the welding time was 150 ms, the electrode pressure was 0.35 MPa, and the electrodes were cylindrical planar electrodes, which was determined by comparing the tensile shear test results. The surficial indentation depth was less than 1% of the plate thickness, and no observable indentations were seen on the surface of the optimized welding spots. [ABSTRACT FROM AUTHOR]

The construction duration of long-span arch bridges is excessively prolonged due to insufficient closing precision and the non-convergence of traditional cable adjustment calculation methods. This study investigates cable force management in long-span concrete-filled steel tubular (CFST) arch bridges during cable-stayed buckle construction, aiming to improve construction safety and precision in arch rib alignment. Using the Pingnan Third Bridge and Tian'e Longtan Bridge as practical examples, the research develops a multi-objective optimization method for cable forces that integrates influence matrices, constrained minimization, and a forward iterative approach. This method offers a robust strategy for tensioning and cable-stayed buckling, enabling real-time monitoring, calculation, and adjustment during the construction of large-span CFST arch bridges. The results reveal that the iterative approach notably enhances calculation efficiency compared to conventional methods. For instance, field measurements at the Pingnan Third Bridge show a minimal arch closure error of only 3 mm. Additionally, the study addresses concerns about excessive stress in exposed steel tubes during concrete casting. By optimizing the sequence of main arch closure and concrete casting, stress in the exposed steel tube is reduced from 373 MPa to 316 MPa, thus meeting specification requirements. In summary, the multi-objective cable force optimization method demonstrates superior efficiency in determining cable tension and controlling rib alignment during cable-stayed buckle construction of long-span CFST arch bridges. [ABSTRACT FROM AUTHOR]

The substantial value held by smart contracts (SCs) makes them an enticing target for malicious attacks. The process of fixing vulnerabilities in SCs is intricate, primarily due to the immutability of blockchain technology. This research paper introduces a systematic literature review (SLR) that evaluates rectification systems designed to patch vulnerabilities in SCs. Following the guidelines set forth by the PRISMA statement, this SLR meticulously reviews a total of 31 papers. In this context, we classify recently published SC automated repair frameworks based on their methodologies for automatic program repair (APR), rewriting strategies, and tools for vulnerability detection. We argue that automated patching enhances the reliability and adoption of SCs, thereby allowing developers to promptly address identified vulnerabilities. Furthermore, existing automated repair tools are capable of addressing only a restricted range of vulnerabilities, and in some cases, patches may not be effective in preventing the targeted vulnerabilities. Another key point that should be taken into account is the simplicity of the patch and the gas consumption of the modified program. Alternatively, large language models (LLMs) have opened new avenues for automatic patch generation, and their performance can be improved by innovative methodologies. [ABSTRACT FROM AUTHOR]

To alleviate the power flow congestion in active distribution networks (ADNs), this paper proposes a two-stage load transfer optimization model based on Neo4j-Dueling DQN. First, the Neo4j graph model was established as the training environment for Dueling DQN. Meanwhile, the power supply paths from the congestion point to the power source point were obtained using the Cypher language built into Neo4j, forming a load transfer space that served as the action space. Secondly, based on various constraints in the load transfer process, a reward and penalty function was formulated to establish the Dueling DQN training model. Finally, according to the ε − g r e e d y action selection strategy, actions were selected from the action space and interacted with the Neo4j environment, resulting in the optimal load transfer operation sequence. In this paper, Python was used as the programming language, TensorFlow open-source software library was used to form a deep reinforcement network, and Py2neo toolkit was used to complete the linkage between the python platform and Neo4j. We conducted experiments on a real 79-node system, using three power flow congestion scenarios for validation. Under the three power flow congestion scenarios, the time required to obtain the results was 2.87 s, 4.37 s and 3.45 s, respectively. For scenario 1 before and after load transfer, the line loss, voltage deviation and line load rate were reduced by about 56.0%, 76.0% and 55.7%, respectively. For scenario 2 before and after load transfer, the line loss, voltage deviation and line load rate were reduced by 41.7%, 72.9% and 56.7%, respectively. For scenario 3 before and after load transfer, the line loss, voltage deviation and line load rate were reduced by 13.6%, 47.1% and 37.7%, respectively. The experimental results show that the trained model can quickly and accurately derive the optimal load transfer operation sequence under different power flow congestion conditions, thereby validating the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Purpose: Social entrepreneurship, leveraging economic activities to achieve social benefits, offers women the opportunity to freely and actively shape the contours of their work in meaningful ways. This study aims to examine how Chinese women use job crafting in social entrepreneurship to align their gender identity, forge meaningful work and new relationships and navigate mixed gender expectations. Design/methodology/approach: The study is based on 19 in-depth interviews with young women engaging in social entrepreneurship in China. Using a grounded theory approach, the study explores how women craft their gender identity into the unconventional career path of creating their social venture, focusing on the creative combination of task, relational and cognitive crafting in shaping social entrepreneurship. Findings: The findings suggest that women make social entrepreneurship meaningful by actively aligning their gender experiences to delineate a relational and cognitive causal path between their social enterprise, their identity as women and their moral values. By working for a larger social cause, women may cognitively reframe their gender identity to compromise financial performance for social impact. Originality/value: Current studies on social entrepreneurship in China have yet to examine its development through a gender lens. This study uses job crafting to highlight the distinctive gender meaning-making process for Chinese women to enhance their work identity and to challenge normative gender expectations. The study shows that job crafting enables women to view their social ventures as a means of gender empowerment, helping them to reconcile the paradoxical pressures of normative gender expectations and scaling up their businesses. [ABSTRACT FROM AUTHOR]