Search Results (226)

This study addresses the issue of cross-interference that occurs when locked continuous light and signal photons are collinear during interferometer measurements. To tackle this, a temperature-controlled Fabry–Pérot cavity filter with a heterogeneous cascaded structure is proposed and applied. The system consists of six filtering stages, created by designing Fabry–Pérot cavities of three different lengths, each used twice (to match optical frequencies), along with temperature control settings. By applying differentiated linewidth regulation, the approach effectively suppresses interference from locked light while significantly enhancing the signal-to-noise ratio in photon detection. This method overcomes the challenge of interference from same-frequency noise photons in atomic ensemble-entangled sources, achieving a noise–photon extinction ratio on the order of 10⁶ and surpassing the frequency resolution limit of a single filter. Experimental results demonstrate that the system reduces the noise floor in the detection optical path to below 10⁻¹⁶, while maintaining a photon transmission efficiency above 53% for the signal. This technology effectively addresses key challenges in noise suppression and photon state fidelity optimization in optical fiber quantum communication, offering a scalable frequency–photon noise filtering solution for long-distance quantum communication. Furthermore, its multi-parameter cooperative filtering mechanism holds broad potential applications in areas such as quantum storage and optical frequency combs. Full article

This study proposes a Cooperative Traffic Controller System (CTS), an urban eco-network control system that leverages Multi-Agent Reinforcement Learning (MARL), to address urban road congestion and environmental pollution. The proposed system synergizes traffic signal timing optimization and speed guidance control, simultaneously enhancing network efficiency, reducing carbon emissions, and minimizing energy consumption. A Beta-enhanced Soft Actor-Critic (SAC) algorithm is applied to achieve the joint optimization of the traffic signal phasing and vehicle speed coordination. Experimental results show that in large-scale networks, the improved SAC reduces the average delay time per vehicle by approximately one minute, reduces CO₂ emissions by more than double, and reduces fuel consumption by 56%. Comparative analyses of the algorithm versus the PPO and standard SAC demonstrate its superior performance in complex traffic scenarios—specifically in congestion mitigation and emissions reduction. Full article

During field cooperative harvesting operations, the accuracy of the tracking behavior between the master and slave unmanned agricultural machines has always been a key factor affecting the quality of cooperative operations. To address this issue, this paper proposes a cooperative harvesting control method based on the prediction model combined with a dual-layer model predictive control (MPC). First, the variational mode decomposition (VMD) algorithm is used to decompose the historical speed, acceleration, and relative distance between master and slave machines into several intrinsic mode functions (IMF)with different frequencies. Then, the Transformer-LSTM model is employed to predict the future speed sequence of the master machine. Based on this, the future speed sequence is input into the dual-layer MPC. The upper-layer MPC adjusts the slave machine’s speed to approach the master machine’s speed and outputs a reference speed signal to the lower-layer MPC. The lower-layer MPC aims to minimize the deviation of the relative distance between the master and slave machines. Finally, the output is the final slave machine speed control signal. Experiments on master machine speed prediction, slave machine tracking, and cooperative harvesting operations were conducted. In the master machine speed prediction experiment, the VMD-Transformer-LSTM model showed significant performance advantages compared to the traditional LSTM, Transformer, and Transformer-LSTM models. The results of the slave machine tracking experiment indicated that the distance deviation in straight-line tracking was controlled within 7.1 cm, while the distance deviation in steering tracking was controlled within 13.7 cm, significantly improving the tracking accuracy. When using the proposed method for cooperative harvesting operations, the non-operating time was reduced by 58.62%, and the harvesting efficiency increased by 33.74%. This provides technical support for multi-machine cooperative harvesting. Full article

In human cells, the biogenesis of membrane proteins, which account for one quarter of polypeptides and sixty percent of human drug targets, is initiated at the membrane of the endoplasmic reticulum (ER). This process involves N-terminal signal peptides or transmembrane helices in the membrane protein precursors. Over one hundred proteins enable membrane-targeting and -insertion of the precursors as well as their folding and covalent modifications. Four targeting pathways to the Sec61 channel in the ER membrane with their effectors and three cooperating or independent membrane protein–insertases have been identified. We combined knock-down of individual components of these pathways and insertases in HeLa cells with label-free quantitative mass spectrometric analysis of the proteomes. Differential protein abundance analysis in comparison to control cells was employed to identify clients of components involved in the targeting or membrane insertion of precursors. Alternatively, knock-out cells or relevant patient fibroblasts were employed. The features of the client polypeptides were characterized to identify the client types of the different components and, ideally, their rules of engagement. In this review/article-hybrid, the focus is on global lessons from and limitations of the proteomic approach in answering the cell biological question, as well as on new aspects, such as N-terminal acetylation of membrane protein precursors. Full article

Model predictive control (MPC) has been proven effective in terms of cooperative control for wind turbines (WTs). Previous work was limited to segmented linearization at a specific operating point, which significantly affected the robustness of the MPC performance. Moreover, due to nonlinearity, frequent control switching would result in the instability and fluctuation of the closed-loop control system. To address these issues, this paper proposes a novel cooperative control strategy considering fatigue load suppression for wind turbines, which is named soft switch multiple model predictive control (SSMMPC). Firstly, based on the gap metric, a model bank is constructed to divide the nonlinear WT model into several linear segments. Then, the multiple MPC is designed in a wide range of operating points. To settle the control signal oscillation problem, a soft-switching rule based on the triangular–trapezoidal hybrid membership function is proposed during controller selection. Several simulations are performed to verify the effectiveness and flexibility of SSMMPC in the partial-load region and full-load region. The results confirm that the proposed SSMMPC exhibits excellent performance in both reference operating point tracking and fatigue load mitigation, especially for the main shaft torque and tower bending load. Full article

This paper investigates the interval type-2 (IT2) fuzzy adaptive fixed-time bipartite consensus self-triggered control for multiple quadrotor unmanned aerial vehicles with deferred full-state constraints and input saturation under cooperative-antagonistic interactions. First, a uniform nonlinear transformation function, incorporating a shifting function, is constructed to achieve the deferred asymmetric constraints on the vehicle states and eliminate the restrictions imposed by feasibility criteria. Notably, the proposed framework provides a unified solution for unconstrained, constant/time-varying, and symmetric/asymmetric constraints without necessitating controller reconfiguration. By employing interval type-2 fuzzy logic systems and an improved self-triggered mechanism, an IT2 fuzzy adaptive fixed-time self-triggered controller is designed to allow the control signals to perform on-demand self-updating without the need for additional hardware monitors, effectively mitigating bandwidth over-consumption. Stability analysis indicates that all states in the closed-loop attitude system are fixed-time bounded while strictly adhering to deferred time-varying constraints. Finally, illustrative examples are presented to validate the effectiveness of the proposed control scheme. Full article

Low-frequency (LF) time code timing technology holds significant importance in civilian applications such as radio-controlled clocks. This study focuses on the design and implementation of a high-precision Binary Phase Code (BPC) LF time code signal generator. A generator system was constructed, demonstrating good stability, superior resolution, and flexible adjustment capabilities for both amplitude and phase. The system employs an ARM + FPGA cooperative architecture: the ARM processor is responsible for parsing and scheduling the time code data, while the FPGA implements carrier wave generation and high-precision digital modulation. This digital processing is combined with analog circuitry to achieve digital-to-analog (D/A) signal conversion. Compared to traditional methods, carrier generation is achieved using Direct Digital Synthesis (DDS) technology. Digital modulation techniques enable the precise control of the modulation depth (adjustable between 70% and 90%) and phase (with a resolution of 1 ns). A sliding window algorithm was utilized for time difference calculation and compensation. Testing confirmed the stability of key signal parameters, including integrity, carrier frequency and modulation depth. These results validate the feasibility and superiority of the digital LF time code generation technology proposed in this study, providing a valuable reference for the development of next-generation timing equipment. Full article

Calcium (Ca²⁺) signaling is a fundamental regulatory mechanism controlling essential processes in the endothelium, vascular smooth muscle cells (VSMCs), and the extracellular matrix (ECM), including maintaining the endothelial barrier, modulation of vascular tone, and vascular remodeling. Cytosolic free Ca²⁺ concentration is tightly regulated by a balance between Ca²⁺ mobilization mechanisms, including Ca²⁺ release from the intracellular stores in the sarcoplasmic/endoplasmic reticulum and Ca²⁺ entry via voltage-dependent, transient-receptor potential, and store-operated Ca²⁺ channels, and Ca²⁺ elimination pathways including Ca²⁺ extrusion by the plasma membrane Ca²⁺-ATPase and Na⁺/Ca²⁺ exchanger and Ca²⁺ re-uptake by the sarco(endo)plasmic reticulum Ca²⁺-ATPase and the mitochondria. Some cell membranes/organelles are multifunctional and have both Ca²⁺ mobilization and Ca²⁺ removal pathways. Also, the individual Ca²⁺ handling pathways could be integrated to function in a regenerative, capacitative, cooperative, bidirectional, or reciprocal feed-forward or feed-back manner. Disruption of these pathways causes dysregulation of the Ca²⁺ signaling dynamics and leads to pathological cardiovascular conditions such as hypertension, coronary artery disease, atherosclerosis, and vascular calcification. In the endothelium, dysregulated Ca²⁺ signaling impairs nitric oxide production, reduces vasodilatory capacity, and increases vascular permeability. In VSMCs, Ca²⁺-dependent phosphorylation of the myosin light chain and Ca²⁺ sensitization by protein kinase-C (PKC) and Rho-kinase (ROCK) increase vascular tone and could lead to increased blood pressure and hypertension. Ca²⁺ activation of matrix metalloproteinases causes collagen/elastin imbalance and promotes vascular remodeling. Ca²⁺-dependent immune cell activation, leukocyte infiltration, and cholesterol accumulation by macrophages promote foam cell formation and atherosclerotic plaque progression. Chronic increases in VSMCs Ca²⁺ promote phenotypic switching to mesenchymal cells and osteogenic transformation and thereby accelerate vascular calcification and plaque instability. Emerging therapeutic strategies targeting these Ca²⁺-dependent mechanisms, including Ca²⁺ channel blockers and PKC and ROCK inhibitors, hold promise for restoring Ca²⁺ homeostasis and mitigating vascular disease progression. Full article

This study highlights the security control challenge for multi-agent systems (MASs) with integrated attack detectors under deception attacks (DAs). We develop an adaptive backstepping security control strategy designed to simultaneously detect DAs and maintain cooperative system performance. First, a DA detection mechanism is proposed using a state observer. The analytical results reveal that observer errors grow unbounded under DAs but converge to zero in attack-free scenarios, enabling effective attack identification. Following detection, we integrate a Nussbaum function into the backstepping control framework to manage unknown time-varying output gains. Additionally, adaptive parameters, dynamically adjusted based on DA signals, are designed to compensate for actuator and sensor deviations induced by attacks. Rigorous Lyapunov-based analysis proves that the proposed controller ensures output tracking under deception attacks, the timely detection of attack signals, and the boundedness of all closed-loop signals. Numerical simulations further confirm the theoretical findings and demonstrate the effectiveness of the proposed method. Full article

The IgLON family of tumor suppressor genes (TSG) impact a variety of cellular processes involved in cancer and non-cancer biology. OPCML is a member of this family and its inactivation is an important control point in oncogenesis and tumor growth. Here, we analyze RNA-Seq expression ratios in ovarian cancers from The Cancer Genome Atlas (TCGA) (189 subjects at Stage III) to identify genes that exhibit a cooperative survival impact (via Kaplan–Meier survival curves) with OPCML expression. Using enrichment analyses, we reconstruct functional pathway impacts revealing interactions of OPCML, and then validate these in independent cohorts of ovarian cancer. These results emphasize the role of OPCML’s regulation of receptor tyrosine kinase (RTK) signaling pathways (PI3K/AKT and MEK/ERK) while identifying three new potential RTK transcriptomic linkages to KIT, TEK, and ROS1 in ovarian cancer. We show that other known extracellular signaling receptor ligands are also transcriptionally linked to OPCML. Several key genes were validated in GEO datasets, including KIT and TEK. Considering the range of OPCML impacts evident in our analyses on both external membrane interactions and cytosolic signal transduction, we expand the understanding of OPCML’s broad cellular influences, demonstrating a multi-functional, pleiotropic, tumor suppressor, in keeping with prior published studies of OPCML function. Full article

Background: Emerging and re-emerging infectious diseases (EIDs and Re-EIDs) cause significant economic crises and public health problems worldwide. Epidemics appear to be more frequent, complex, and harder to prevent. Early warning systems can significantly reduce outbreak response times, contributing to better patient outcomes. Improving early warning systems and methods might be one of the most effective responses. This study employs a bibliometric analysis to dissect the global research hotspots and evolutionary trends in the field of infectious disease early warning, with the aim of providing guidance for optimizing public health emergency management strategies. Methods: Publications related to the role of early warning systems in detecting and responding to infectious disease outbreaks from 1999 to 2024 were retrieved from the Web of Science Core Collection (WoSCC) database. CiteSpace software was used to analyze the datasets and generate knowledge visualization maps. Results: A total of 798 relevant publications are included. The number of annual publications has sharply increased since 2000. The USA produced the highest number of publications and established the most extensive cooperation relationships. The Chinese Center for Disease Control & Prevention was the most productive institution. Drake, John M was the most prolific author, while the World Health Organization and AHMED W were the most cited authors. The top two cited references mainly focused on wastewater surveillance of SARS-CoV-2. The most common keywords were “infectious disease”, “outbreak”, “transmission”, “virus”, and “climate change”. The basic keyword “climate” ranked the first and long duration with the strongest citation burst. “SARS-CoV-2”, “One Health”, “early warning system”, “artificial intelligence (AI)”, and “wastewater-based epidemiology (WBE)” were emerging research foci. Conclusions: Over the past two decades, research on early warning of infectious diseases has focused on climate change, influenza, SARS, virus, machine learning, warning signals and systems, artificial intelligence, and so on. Current research hotspots include wastewater-based epidemiology, sewage, One Health, and artificial intelligence, as well as the early warning and monitoring of COVID-19. Research foci in this area have evolved from focusing on climate–disease interactions to pathogen monitoring systems, and ultimately to the “One Health” integrated framework. Our research findings underscore the imperative for public health policymakers to prioritize investments in real-time surveillance infrastructure, particularly wastewater-based epidemiology and AI-driven predictive models, and strengthen interdisciplinary collaboration frameworks under the One Health paradigm. Developing an integrated human–animal–environment monitoring system will serve as a critical development direction for early warning systems for epidemics. Full article

Existing resource allocation models for multi-hop relay networks lack the systematic joint optimization of relay selection and power allocation. Therefore, a multi-hop relay network model based on a joint optimization strategy is proposed, aimed at realizing the energy efficiency optimization of the system through the cooperative optimization of relay selection and power allocation. The proposed model not only takes into account the node transmitting power and communication link but also combines the specified system quality of service requirements. On this basis, the FD-Dink energy efficiency optimization algorithm is proposed. By integrating an enhanced D* algorithm with a forward maximum signal-to-noise ratio (FMSNR) and the Dinkelbach–Lagrange multiplier method, the proposed strategy resolves relay selection and power control problems in a coordinated framework so as to determine the optimal energy efficiency communication link of a multi-hop relay network model. Case studies demonstrate that this joint optimization strategy significantly improves the system energy efficiency of the multi-hop relay network and shows superiority in dynamic path planning and global power allocation, offering significant theoretical and practical implications. Full article

Obesity is a significant global health issue, profoundly affecting metabolic and cardiovascular health and other related chronic conditions. In Chile, the prevalence of obesity is among the highest within the Organisation for Economic Cooperation and Development (OECD) countries, highlighting a critical public health challenge. This narrative review examines current evidence on the independent and potential synergistic roles of omega-3 fatty acids and exercise in managing obesity-related metabolic dysfunction. Omega-3 fatty acids, particularly eicosapentaenoic acid (EPA), have been shown to lower triglyceride levels, enhance lipid metabolism, and modulate inflammation via pathways involving peroxisome proliferator-activated receptors (PPARs) and sterol regulatory element-binding protein-1c (SREBP-1c). Exercise interventions, such as moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT), provide distinct yet complementary metabolic benefits. Specifically, MICT improves body fat distribution and mitochondrial efficiency, whereas HIIT has notable effects on metabolic adaptability and insulin signaling. Additionally, emerging evidence points toward a potential role of the kinin-kallikrein system, particularly kallikrein 7 (KLK7), in obesity-associated insulin resistance. Despite these promising findings, several knowledge gaps persist regarding optimal dosing, intervention timing, population-specific effects, and the exact mechanisms behind the potential synergistic interactions between omega-3 supplementation and structured exercise. This review emphasizes the importance of conducting further research, particularly controlled clinical trials, to clarify these combined interventions’ effectiveness and establish targeted therapeutic strategies tailored to individual metabolic profiles. Full article

Mesenchymal progenitor cells (MPC) are effective in reducing tissue loss, preserving white matter, and improving forelimb function after a spinal cord injury (SCI). We proposed that by preconditioning the mouse by the intravenous delivery (IV) of MPCs for 24 h following SCI, this would provide a more favorable tissue milieu for an NSC intraspinal bridging transplantation at day three and day seven. In combination, these transplants will provide better anatomical and functional outcomes. The intravenous MSCs would provide cell protection and reduce inflammation. NSCs would provide a tissue bridge for axonal regeneration and myelination and reconnect long tract spinal pathways. Results showed that initial protection of the injury site by IV MPCs transplantation resulted in no increased survival of the NSCs transplanted at day seven. However, integration of transplanted NSCs was increased at the day three timepoint, indicating MPCs influence very early immune signaling. We show, in this study, that MPC transplantation resulted in a co-operative NSC cell survival improvement on day three post-SCI. In addition to increased NSC survival on day three, there was an increase in NSC-derived mature oligodendrocytes at this early timepoint. An in vitro analysis confirmed MPC-driven oligodendrocyte differentiation, which was statistically increased when compared to control NSC-only cultures. These observations provide important information about the combination, delivery, and timing of two cellular therapies in treating SCI. This study provides important new data on understanding the MPC inflammatory signaling within the host tissue and timepoints for cellular transplantation survival and oligodendroglia differentiation. These results demonstrate that MPC transplantation can alter the therapeutic window for intraspinal transplantation by controlling both the circulating inflammatory response and local tissue milieu. Full article

This paper addresses the event-triggered neuroadaptive bipartite containment tracking problem for networked unmanned aerial vehicles (UAVs) subject to resource constraints and actuator failures. A fully distributed event-triggered mechanism is innovatively developed to eliminate dependency on global information while rigorously excluding the Zeno phenomenon through nonperiodic threshold verification. The proposed mechanism enables neighboring UAVs to exchange information and update control signals exclusively at triggering instants, significantly reducing communication burdens and energy consumption. To handle unknown nonlinear dynamics under resource-limited scenarios, a novel event-triggered neural network (NN) approximation scheme is established where weight updating occurs only during event triggers, effectively decreasing computational resource occupation. Simultaneously, an adaptive robust compensation mechanism is constructed to counteract composite disturbances induced by actuator failures and approximation residuals. Based on the Lyapunov stability analysis, we theoretically prove that all closed-loop signals remain uniformly ultimately bounded while achieving prescribed bipartite containment objectives, where follower UAVs ultimately converge to the dynamic convex hull formed by multiple leaders with cooperative-competitive interactions. Finally, numerical simulations are conducted to validate the effectiveness of the theoretical results. Comparative simulation results show that the proposed event-triggered control scheme reduces the utilization of resources by $95\%$ and $67\%$ compared with the traditional time-triggered and static-triggered mechanisms, respectively. Full article