Integral Mode Research Articles

Novel Surface Integral Equation-Based Sub-Structure Characteristic Mode Formulations for Lossy Composite Objects

Novel Surface Integral Equation-Based Sub-Structure Characteristic Mode Formulations for Lossy Composite Objects

A socio-cognitive perspective of knowledge integration in digital innovation networks

Digital innovation is a complex process in which actors seek to create new value pathways by combining digital resources in a layered modular architecture. While IS scholarship has a rich tradition of research on developing and implementing digital artefacts within intra-organisational contexts, our understanding of knowledge integration across distributed innovation networks is nascent and under-theorised. This is an important area of research given the rising importance of digital innovation networks and the challenges faced in integrating specialised knowledge, especially given the greater diversity, speed, reach, and scope made possible by digital technologies. Drawing on in-depth case study findings from a health IoT project involving multiple organisations and disciplines, we explore how knowledge is integrated across boundaries during the initiation stage of a digital innovation network. Our findings point to boundaries related to the digital platform’s organising vision, resource allocation, delivery roadmap, technical architecture, and intellectual property, to name but a few challenges. We then reveal five socio-cognitive modes of knowledge integration which actors strategically enact to cross syntactic, semantic, and pragmatic boundaries: Signalling, Assembling, Contesting, Discounting, and Finalising. The choice of mode depends on the perceived knowledge status (‘what they know’) and social status (‘who they are’) of network actors, which highlight the salience of both social and cognitive dependencies for knowledge integration. We further discuss the contribution of design objects for overcoming differences and distinctions between specialist actors in a digital innovation network.

Application Research of Power Measurement Data Exchange Based on Uninterruptible Power Supply

With the maturity of the smart meter embedded system integration mode, the power consumption information can be fed back to the management center by the intelligent terminal through the power Internet of Things. The smart terminal adopts the narrowband data communication mode. However, the narrowband channel interval is hindered by interference signals, resulting in serious data packet loss. Therefore, a stable and efficient acquisition scheme is needed to ensure its smooth interaction. Based on the application of smart meter data communication, we analyze the power consumption optimization and carrier transmission optimization of the power Internet of Things and propose a data analysis method based on self-learning and external characteristics, which is used to calculate the offline execution strategy of smart meters when they encounter factors such as power outage or intrusion. A production task-driving rule is designed. The external characteristics of deep learning data of the power Internet of Things are collected. The accuracy of data classification is judged according to the parallel Internet of Things of a convolutional neural network and a long-term and short-term memory deep neural network. When dealing with high-dimensional original data, the data network is graded to reduce the work of feature selection and the difficulty of training. Moreover, we improve the autonomous execution ability of an embedded terminal device in an offline state. We also strengthen the ability of abnormal data detection and judgment learning to meet the requirements of efficient and stable operation of the power grid. Simulation results verify that compared with the current mainstream schemes, the performance of the proposed scheme is improved by more than 17%. Besides, the fault tolerance rate is enhanced by 29%, and the power consumption after optimization is reduced by 26.3% and 42.8%. These effects highlight the role of data processing in embedded systems. It solves the problem of abnormal data and energy loss affecting the accuracy of error estimation of electric energy meters, opens up a new way for data acquisition and processing of large-scale smart meters, and further improves the service level of information management of power systems.

Reduced-Order Sliding Mode Observer-Based Backstepping Integral Logarithmic Sliding Mode Control: Application to Wing Aeroelastic System

Reduced-Order Sliding Mode Observer-Based Backstepping Integral Logarithmic Sliding Mode Control: Application to Wing Aeroelastic System

Research on the Optimization of Practical Teaching System under the Mode of Integration of Production and Teaching in Institute of Navigation Technology and Industry

Under the background of global economic integration and the rapid development of shipping industry, navigation technology education is facing challenges such as the disconnection between theory and practice and limited practical opportunities. In order to meet these challenges, this paper deeply analyzes the implementation status of the integration mode of production and teaching in Maritime Technology Industry College, and discusses its advantages and disadvantages in personnel training, curriculum system construction, teacher team development, training base construction and teaching quality monitoring. Through the strategies of modular curriculum design, virtual simulation training, enterprise internship opportunities, double-qualified teachers training and diversified evaluation system, this paper puts forward a set of plans to comprehensively optimize the practice teaching system. The program aims to enhance students' practical ability, innovation ability and professional accomplishment, make them better adapt to the needs of the industry, and provide high-quality talent guarantee for the sustainable development of the navigation technology industry. At the same time, this paper also emphasizes the importance of school-enterprise cooperation, and realizes the deep integration and sharing of educational resources and industrial resources through co-construction of curriculum system, teaching staff and training base. Finally, this paper looks forward to the potential contribution of the optimized practical teaching system in improving teaching quality, promoting industrial upgrading and technological innovation.

Control Design of the Quadrotor Aircraft based on the Integral Adaptive Improved Integral Backstepping Sliding Mode Scheme

Control Design of the Quadrotor Aircraft based on the Integral Adaptive Improved Integral Backstepping Sliding Mode Scheme

‘Pooling and Sharing’ and ‘Permanent Structured Cooperation’ as the Current EU’s Defense and Security Integration Modes

ABSTRACT When an urgent response in international relations is needed, the EU institutions and Member States’ governments face a deficiency of effective and practical mechanisms in security cooperation. Developing autonomous programs and concepts that address this dilemma, preventing duplication of endeavors and investments, and maximizing cost-effectiveness by broadening military-political consultations on all issues of common concern is challenging. This article analyses the path and logic of EU security integration in the recent decade. In this context, the origins and goals of the pooling and sharing concept are essential to analyze the continuity of security integration, where the Council’s introduction of Permanent Structured Cooperation in defense and security is an important step forward. Therefore, this article will investigate whether and how P&S and PESCO have been related and complemented, even though both differ in the prism of aims, logic, decision-making processes, and funding. Due to budgetary throwbacks in recent decades and the war in Ukraine intensified after February 2022, EU Member States’ governments might evaluate their approach to the level of engagement in common security programs.

Direct Power Control of BDFRG Based on Novel Integral Sliding Mode Control

Direct Power Control of BDFRG Based on Novel Integral Sliding Mode Control

Tracking performance and power quality enhancement of DFIG based wind turbine using robust integral terminal sliding mode control

The aim of this work is to develop a robust Integral Terminal Sliding Mode Control (ITSMC) strategy for a Doubly Fed Induction Generator (DFIG) wind turbine (WT) operating in challenging conditions. This controller is designed to manage the system's rotor side converter (RSC) and grid side converter (GSC), ensuring maximum power production, improved power quality, and accurate tracking of system state variables, even in the face of fluctuating wind conditions, parameter uncertainties, and external disturbances. The stability of the proposed controller is assured using the Lyapunov theory. The performance of ITSMC is compared with that of the conventional sliding mode controller (SMC) and backstepping controller through simulation tests, using the integral absolute error (IAE) as a performance metric. The results highlight the superiority of ITSMC, demonstrating its ability to precisely track reference values, eliminate static errors, and minimize chattering. ITSMC consistently achieves the lowest IAE for all tracked state variables and across all test scenarios. A comparative study analyzing the Total Harmonic Distortion (THD) of the proposed controller versus SMC, the backstepping controller, and other similar works in the literature shows a marked improvement in the THD of stator and filter currents by at least 24.53 % and 7.96 %, respectively. These findings underscore the controller's capability to enhance the power quality delivered to the grid.

Robust fractional-order load frequency control for hybrid power system concerning high wind penetration

Hybrid power systems concerning wind farms have witnessed significant dynamic characteristic changes due to unpredicted generation output and integration mode conversion between frequency-sensitive wind plants and non-scheduled ones. This work presents a robust fractional-order load frequency control (LFC) method for a multi-area hybrid power system in the presence of wind penetration uncertainties. To characterize the injection effect of wind farms, the power system is described by a model with an uncertain wind penetration factor in a pre-estimated range. Then, an enhancement of Levy’s identification method is developed to convert this model into a fractional-order reduced structure to design the load frequency controller, which is in a form of fractional-order PID with a filter for ease of engineering implementation. The closed-loop stability is analyzed by the stability boundary locus (SBL) method under different wind penetration levels. It is shown that superior frequency response performance and system robustness can be obtained if the controller is designed in terms of the model with the worse-case wind penetration. Illustrative examples including a three-area hybrid power system under a variety of wind penetration variations are given to show the effectiveness of the proposed method.

High Voltage Monolithic Active Pixel Sensors for the MOLLER experiment

The MOLLER experiment [1] aims to measure the parity-violating asymmetry (APV) in electron–electron scattering at 11 GeV, and thus determine the weak charge of the electron to a high precision (2.4%). Two of the key sub-systems in the experimental apparatus are the main detector array, consisting of 224 fused silica detector modules and an electron beam Compton polarimeter. The main detector array can be operated in either pulsed mode for particle tracking, or integration mode for the asymmetry measurement at high rate detection. A subset of these detector modules will be equipped with an array of High Voltage Monolithic Active Pixel Sensors (HVMAPS), to be used in particle tracking and allowing for real-time monitoring of the event profile in the main Møller region. HVMAPS are also used for the Compton polarimeter, consisting of four-plane planes of HVMAPS chips, housed in a vacuum chamber upstream of the interaction point. An overview of the implementation of the HVMAPS for the main detectors and Compton polarimeter is provided.

Efficacy and safety of step-by-step Baduanjin exercise based on doctor-nurse-patient integration mode for pulmonary rehabilitation in patients after lobectomy due to pulmonary tuberculosis: a randomized controlled clinical trial

BackgroundSome pulmonary tuberculosis patients may require lung resection surgery. Postoperative pulmonary rehabilitation is essential to restore the lung function and maintain quality of life. We aimed to study the pulmonary rehabilitation outcomes and complications of step-by-step Baduanjin exercise under a doctor-nurse-patient integration mode in patients after lobectomy due to pulmonary tuberculosis.MethodsWe performed a randomized controlled clinical trial in patients undergoing lobectomy due to pulmonary tuberculosis between September 2017 and August 2021. Eligible patients were randomly assigned into the control group or interventional group. The control group received routine postoperative care. The interventional group received step-by-step Baduanjin exercise based on the doctor-nurse-patient integration mode in addition to the routine care. The primary outcomes were the pulmonary functions, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC. The secondary outcomes were the maximum walking distance in a 6-min walk test and postoperative pulmonary complications, including atelectasis, pneumonia, and respiratory failure.ResultsA total of 100 patients were enrolled into the study, with 50 patients in the control and interventional groups. There were 60 female patients (60%). The mean patient age was 37.9 (± 2.8) years old. At the one- and two-month postoperative follow-ups, pulmonary function tests showed statistically significantly better performances in FEV1/prediction, FVC/prediction, and FEV1/FVC in the interventional group than the control group. The 6-min walk test also revealed longer walking distances in the interventional group than the control group. There were no statistically significant differences in postoperative complications between the two groups.ConclusionsA step-by-step Baduanjin exercise regimen under the doctor-nurse-patient integration mode could safely improve pulmonary rehabilitation in patients after lobectomy due to pulmonary tuberculosis.

The role of the hepatitis B virus genome and its integration in the hepatocellular carcinoma.

The integration of Hepatitis B Virus (HBV) is now known to be closely associated with the occurrence of liver cancer and can impact the functionality of liver cells through multiple dimensions. However, despite the detailed understanding of the characteristics of HBV integration and the mechanisms involved, the subsequent effects on cellular function are still poorly understood in current research. This study first systematically discusses the relationship between HBV integration and the occurrence of liver cancer, and then analyzes the status of the viral genome produced by HBV replication, highlighting the close relationship and structure between double-stranded linear (DSL)-HBV DNA and the occurrence of viral integration. The integration of DSL-HBV DNA leads to a certain preference for HBV integration itself. Additionally, exploration of HBV integration hotspots reveals obvious hotspot areas of HBV integration on the human genome. Virus integration in these hotspot areas is often associated with the occurrence and development of liver cancer, and it has been determined that HBV integration can promote the occurrence of cancer by inducing genome instability and other aspects. Furthermore, a comprehensive study of viral integration explored the mechanisms of viral integration and the internal integration mode, discovering that HBV integration may form extrachromosomal DNA (ecDNA), which exists outside the chromosome and can integrate into the chromosome under certain conditions. The prospect of HBV integration as a biomarker was also probed, with the expectation that combining HBV integration research with CRISPR technology will vigorously promote the progress of HBV integration research in the future. In summary, exploring the characteristics and mechanisms in HBV integration holds significant importance for an in-depth comprehension of viral integration.

Input specificity of NMDA-dependent GABAergic plasticity in the hippocampus

Sensory experiences and learning induce long-lasting changes in both excitatory and inhibitory synapses, thereby providing a crucial substrate for memory. However, the co-tuning of excitatory long-term potentiation (eLTP) or depression (eLTD) with the simultaneous changes at inhibitory synapses (iLTP/iLTD) remains unclear. Herein, we investigated the co-expression of NMDA-induced synaptic plasticity at excitatory and inhibitory synapses in hippocampal CA1 pyramidal cells (PCs) using a combination of electrophysiological, optogenetic, and pharmacological approaches. We found that inhibitory inputs from somatostatin (SST) and parvalbumin (PV)-positive interneurons onto CA1 PCs display input-specific long-term plastic changes following transient NMDA receptor activation. Notably, synapses from SST-positive interneurons consistently exhibited iLTP, irrespective of the direction of excitatory plasticity, whereas synapses from PV-positive interneurons predominantly showed iLTP concurrent with eLTP, rather than eLTD. As neuroplasticity is known to depend on the extracellular matrix, we tested the impact of metalloproteinases (MMP) inhibition. MMP3 blockade interfered with GABAergic plasticity for all inhibitory inputs, whereas MMP9 inhibition selectively blocked eLTP and iLTP in SST-CA1PC synapses co-occurring with eLTP but not eLTD. These findings demonstrate the dissociation of excitatory and inhibitory plasticity co-expression. We propose that these mechanisms of plasticity co-expression may be involved in maintaining excitation-inhibition balance and modulating neuronal integration modes.

Field-free multistate spin–orbit torque devices for programmable image edge recognition circuit

The application of spin–orbit torque (SOT) devices to neuromorphic computing platforms is focused on the development of hardware circuit architectures. However, the inter-device variability, the integration modes of devices and peripheral circuits, and appropriate application scenarios are still unclear, limiting the development of SOT devices in neuromorphic computing. To solve this problem, this paper first proposes a circuit compensation scheme for the difference in resistance values of SOT devices, which solves this variability problem at the circuit level. Moreover, a synergistic scheme with the circuit is developed based on the correspondence between the multistate resistance characteristics of the SOT devices and a convolutional algorithm. To achieve this, a multichannel SOT convolutional kernel circuit architecture is built, which implements an image edge recognition application. Finally, based on a simulation model, an image edge recognition hardware circuit based on our CoPt-SOT devices is implemented, which is capable of performing image edge recognition with an accuracy of 96.33%. This scheme provides technical support and development prospects for SOT devices in neural network hardware applications.

Reconstruction algorithm for cross-waveband optical computing imaging

Abstract In a single-pixel fast imaging setup, the data collected by the single-pixel detector needs to be processed by a computer, but the speed of the latter will affect the image reconstruction time. Here we propose two kinds of setups which are able to transform non-visible into visible light imaging, wherein their computing process is replaced by a camera integration mode. The image captured by the camera has a low contrast, so here we present an algorithm that can realize a high quality image in near-infrared to visible cross-waveband imaging. The scheme is verified both by simulation and in actual experiments. The setups demonstrate the great potential for single-pixel imaging and high-speed cross-waveband imaging for future practical applications.

A novel weighted exponential sliding mode controller with a modified reaching law for the frequency regulation of a renewable integrated isolated AC microgrid

This paper investigates the development and application of a novel hybrid controller through novel sliding surface and novel reaching law, Weighted Exponential Sliding Mode Control with Modified Reaching Law (WESMC-MRL), for frequency regulation in an isolated Microgrid (MG) with intermittent Renewable Energy Sources (RESs) such as solar and wind. Major contributions include the analysis of frequency regulation of isolated MG controlled by WESMC-MRL under various load perturbations. The performance of WESMC-MRL is compared with conventional Linear Quadratic Regulator (LQR), Sliding Mode Control (SMC), and Integral Sliding Mode Control (ISMC) controllers. Outcomes indicate that the WESMC-MRL effectively regulates the MG frequency with minimal chattering, and outperforms LQR SMC, and ISMC in terms of settling time, overshooting, and undershooting in frequency deviation. With the WESMC-MRL the maximum frequency deviation is found only 0.00724 Hz and undershoot is negligible. The proposed controller is also robust against RES integration variability, disturbances, and nonlinearities making it a promising solution for reliable and stable MG operation.

Enhanced thermally integrated Carnot battery using low-GWP working fluid pair: Multi-aspect analysis and multi-scale optimization

Thermally integrated Carnot battery (TICB) emerges as a promising technology for long-duration energy storage. This study aims to improve its multi-dimensional performance from the optimization design level, thereby promoting its competitiveness. Firstly, a refined system architecture is developed, integrating subsystem layout modification and advanced thermal integration mode. Sixteen potential working fluid pairs are formed by screening low-GWP refrigerants as drop-in substitutes for R245fa. Then, a comprehensive evaluation framework is established to characterize this technology from energy, exergy, and economic perspectives, and a collaborative optimization method is introduced to facilitate integrated optimization. Finally, a whole cycle cumulative exergy analysis is conducted to explore directions for further improvement. Results indicate that, compared to the basic architecture, the round-trip efficiency (RTE) of the proposed system is elevated by over 30%. The use of different alternative refrigerants in the charging and discharging cycles makes the TICB not only sustainable but also more efficient. The thermodynamic dilemma of determining the heat pump evaporation temperature disappears with a closed-type heat source. To maximize overall thermo-economics, sufficient heat pump subcooling and evaporator internal superheat are necessary, and the ideal storage temperature span and pinch point temperature difference of heat exchangers must be identified. The collaborative optimization displays that the first-rank working fluid pair is R1234ze(Z)-R1224yd(Z), with an RTE of 85.2%, a volumetric energy density of 3.10 kWh/m3, and a levelized cost of storage of 0.303 $/kWh, respectively. Furthermore, the RTE is highly sensitive to the insulation quality of storage tanks. A mere 2.5% performance degradation can lead to a 10% points decline in RTE. Internal exergy destruction is primarily caused by poor heat transfer matching, while external exergy loss mainly results from underutilized heat sources during non-charging periods. Therefore, we recommend the district heating network as the target heat source for the dual-period TICB. These achievements offer a valuable reference for the research and development of efficient, affordable, and sustainable TICB.

GA-NIFS: NIRSpec reveals evidence for non-circular motions and AGN feedback in GN20

ABSTRACT We present rest-frame optical data of the $z\sim 4$ submillimetre galaxy GN20 obtained with the JWST Near Infrared Spectrograph (NIRSpec) in integral field spectroscopy mode. The H$\alpha$ emission is asymmetric and clumpy and extends over a projected distance of >15 kpc. To first order, the large-scale ionized gas kinematics are consistent with a turbulent ($\sigma \sim 90$ km s$^{-1}$), rotating disc ($v_{\rm rot}\sim 500$ km s$^{-1}$), congruent with previous studies of its molecular and ionized gas kinematics. However, we also find clear evidence for non-circular motions in the H$\alpha$ kinematics. We discuss their possible connection with various scenarios, such as external perturbations, accretion, or radial flows. In the centre of GN20, we find broad-line emission (full width at half-maximum $\sim 1000{-}2000$ km s$^{-1}$) in the H$\alpha$ + [N ii] complex, suggestive of fast, active galactic nucleus-driven winds or, alternatively, of the broad-line region of an active black hole. Elevated values of [N ii] $\lambda 6583$/H$\alpha \ \gt\ 0.4$ and of the Hα equivalent width EW(H$\alpha)\ \gt\ 6$ Å throughout large parts of GN20 suggest that feedback from the active black hole is able to photoionize the interstellar medium. Our data corroborate that GN20 offers a unique opportunity to observe key processes in the evolution of the most massive present-day galaxies acting in concert, over 12 billion years ago.

A double-layer Q-learning driven memetic algorithm for integrated scheduling of procurement, production and maintenance with distributed resources

The existing research on integrated production scheduling typically focuses on activities related to both production and post-production (e.g., operation and maintenance), with limited consideration for simultaneously integrating pre-production activities (e.g., raw material procurement). However, achieving the equilibrium between the manufacturer and the demander for intelligent manufacturing systems requires the optimal scheduling solution that integrates both pre-production and post-production activities. Inspired by this, we investigate a novel integrated scheduling problem that concurrently considers raw material procurement, production scheduling and equipment maintenance (abbreviated as SIPPM). A mixed-integer linear programming model is developed to simultaneously minimize the total costs for the manufacturer and the demander. Furthermore, a double-layer Q-learning driven memetic algorithm (DQMA) is proposed to solve the SIPPM. In DQMA, a well-tailored three-layer hybrid encoding method is presented for chromosome representation. The global search of DQMA employs three crossover and three mutation operators. Moreover, a knowledge-based local search operator with six methods, guided by an effective double-layer Q-learning structure, is devised to enhance local exploitation capabilities. The superiority of DQMA is verified through comparison with three popular multi-objective optimization algorithms on 108 newly established benchmark instances. The proposed integrated scheduling mode is proven to be more effective than two separated scheduling modes without considering raw material procurement.