Search Results (737)

In recent years, the rapid development of commercial satellite projects, such as low-Earth orbit (LEO) communication and remote sensing constellations, has driven the satellite industry toward low-cost, rapid development, and large-scale deployment. Commercial off-the-shelf (COTS) components have been widely adopted across various commercial satellite platforms due to their advantages of low cost, high performance, and plug-and-play availability. However, the space environment is complex and hostile. COTS components were not originally designed for such conditions, and they often lack systematically flight-verified protective frameworks, making their reliability issues a core bottleneck limiting their extensive application in critical missions. This paper focuses on COTS solid-state drives (SSDs) onboard the Jilin-1 KF satellite and presents a full-lifecycle reliability practice covering component selection, system design, on-orbit operation, and failure feedback. The core contribution lies in proposing a full-lifecycle methodology that integrates proactive design—including multi-module redundancy architecture and targeted environmental stress screening—with on-orbit data monitoring and failure cause analysis. Through fault tree analysis, on-orbit data mining, and statistical analysis, it was found that SSD failures show a significant correlation with high-energy particle radiation in the South Atlantic Anomaly region. Building on this key spatial correlation, the on-orbit failure mode was successfully reproduced via proton irradiation experiments, confirming the mechanism of radiation-induced SSD damage and providing a basis for subsequent model development and management decisions. The study demonstrates that although individual COTS SSDs exhibit a certain failure rate, reasonable design, protection, and testing can enhance the on-orbit survivability of storage systems using COTS components. More broadly, by providing a validated closed-loop paradigm—encompassing design, flight verification and feedback, and iterative improvement—we enable the reliable use of COTS components in future cost-sensitive, high-performance satellite missions, adopting system-level solutions to balance cost and reliability without being confined to expensive radiation-hardened products. Full article

The rise of the circular economy and e-commerce has led to the emergence of e-commerce closed-loop supply chains (ECLSCs). In practice, investing in process innovation (PI) is key to improving profitability and competitiveness. However, manufacturers at the downstream of ECLSCs often face financial constraints and quality uncertainty of used products, while research on how to select financing strategies under these conditions remains limited. To explore the optimal financing scheme for the ECLSC, this study investigates two financing schemes: bank financing (BF) and FinTech platform financing (FPF), which offers a combination of debt financing (DF) and equity financing (EF). Some key findings are derived. For the ECLSC, the FPF scheme is more profitable when the unit manufacturing cost for new components exceeds the threshold or PI costs are relatively low. Additionally, the FPF performs better when the FPF interest rate is low and the DF ratio is high. The BF is more beneficial when consumer sensitivity to recycling prices or service is low. The FPF enables the ECLSC to achieve maximum profits and minimize environmental impact within a specific range. Furthermore, the financing models are extended to incorporate considerations of fairness, where the optimal financing scheme is primarily influenced by the manufacturing cost. Full article

The global space economy, valued at approximately USD 400–630 billion (depending on definitional scope), is projected to expand rapidly, crossing USD 1 trillion as early as 2032 and reaching up to about USD 1.8 trillion by 2035. This growth has been driven by a surge (a roughly twelvefold increase) in satellite launches over the past decade, transforming Earth’s orbits into an increasingly congested domain plagued by space debris. The proliferation of space junk poses an escalating threat to orbital sustainability, yet effective governance mechanisms remain limited. This paper examines why conventional solutions for managing common-pool resources (command-and-control regulation, Pigouvian taxes, private property rights, allocation of tradable permits, and horizontal governance regimes) are not fully effective or are difficult to implement in addressing the orbital debris problem. Using a system dynamics perspective, the study qualitatively maps hypothesized feedback mechanisms shaping orbital expansion and space debris accumulation. It suggests that, under the assumed causal structure, reinforcing growth loops associated with geopolitical rivalry and commercial cost reductions linked to the New Space paradigm currently dominate over delayed balancing effects arising from the finite nature of orbital space, whose regenerative capacity is progressively degraded. There exists a threshold of exploitation beyond which orbital space effectively behaves as a non-renewable resource. The analysis suggests that, without binding international coordination, meaningful intervention may require the occurrence of a catalyzing crisis—e.g., a localized cascade of orbital object collisions that could transform stakeholder perceptions and enables active debris removal deployment. Full article

Achieving a balance between rapid adaptation and robustness is a critical yet challenging objective in the design of industrial control systems. Model Reference Adaptive Control (MRAC) is a standard approach for managing system uncertainties; however, it suffers from a fundamental trade-off between adaptation speed and robustness. The high adaptation gains required for fast tracking often lead to parameter bursting or instability in the presence of noise. To resolve this issue, this paper proposes a new Dual-Loop Optimal Feedback Control (OFC) architecture applied to a Brushless DC (BLDC) motor drive. Unlike conventional methods that rely solely on tuning the adaptive mechanism, the proposed architecture introduces a parallel compensation loop designed to decouple disturbance rejection from reference tracking. This structure utilizes a Genetic Algorithm (GA) as an offline optimization engine to identify the Optimal Compensator gains that balance transient recovery with steady-state stability. Experimental validation demonstrates that the proposed Dual-Loop OFC architecture significantly outperforms traditional approaches. Specifically, it achieves an 88.99% reduction in overshoot and a 13.8% reduction in settling time compared to Conventional MRAC (CMRAC). Furthermore, it exhibits an 86.7% faster rise time compared to Self-Tuning Fuzzy PID (STFPID). These results confirm that the proposed Dual-Loop structure effectively mitigates the classic adaptability–robustness trade-off, offering a stable and high-performance solution for industrial actuators under varying operating conditions. Full article

Extended Reality (XR) technologies have matured into powerful tools for training in high-stakes domains, from emergency response to search and rescue. Yet current systems often struggle to balance real-time AI-driven personalisation with the need for human oversight and calibrated trust. This article synthesizes the programmatic contributions of a multi-study doctoral project to advance a design-and-evaluation framework for trustworthy adaptive XR training. Across six studies, we explored (i) recommender-driven scenario adaptation based on multimodal performance and physiological signals, (ii) persuasive dashboards for trainers, (iii) architectures for AI-supported XR training in medical mass-casualty contexts, (iv) theoretical and practical integration of Human-in-the-Loop (HITL) supervision, (v) user trust and over-reliance in the face of misleading AI suggestions, and (vi) the role of interaction modality in shaping workload, explainability, and trust in human–robot collaboration. Together, these investigations show how adaptive policies, transparent explanation, and adjustable autonomy can be orchestrated into a single adaptation loop that maintains trainee engagement, improves learning outcomes, and preserves trainer agency. We conclude with design guidelines and a research agenda for extending trustworthy XR training into safety-critical environments. Full article

Chronic pain is a pervasive and debilitating condition that affects millions of individuals worldwide. Unlike acute pain, which serves a protective physiological role, chronic pain persists beyond routine tissue healing and often arises without a discernible peripheral cause. Accumulating evidence indicates that chronic pain is not merely a symptom but a disorder of the central nervous system, underpinned by interacting molecular, neurochemical, and network-level alterations. Molecular neuroimaging using PET and MR spectroscopy has revealed dysregulated excitatory–inhibitory balance (glutamate/GABA), altered monoaminergic and opioidergic signaling, and neuroimmune activation (e.g., TSPO-indexed glial activation) in key pain-related regions such as the insula, anterior cingulate cortex, thalamus, and prefrontal cortex. Converging multimodal imaging—including functional MRI, diffusion MRI, and EEG/MEG—demonstrates aberrant activity and connectivity across the default mode, salience, and sensorimotor networks, alongside structural remodeling in cortical and subcortical circuits. Parallel advances in neuromodulation, including transcranial magnetic stimulation (TMS), transcranial electrical stimulation (tES), deep brain stimulation (DBS), and emerging biomarker-guided closed-loop approaches, provide tools to perturb these maladaptive circuits and to test mechanistic hypotheses in vivo. This review integrates neuroimaging findings with molecular and systems-level mechanistic insights into chronic pain and its modulation, highlighting how imaging markers can link biochemical signatures to neural dynamics and guide precision pain management and individualized therapeutic strategies. Full article

Transgender and gender-expansive (TGE) communities face persistent health inequities that are reproduced through everyday administrative and clinical encounters across care systems. A feedback-focused lens can clarify how those inequities are generated and sustained. Objective: To identify and validate feedback loops that create policy exposure and institutional gatekeeping in TGE healthcare and to surface leverage points to stabilize their continuity of care. Methods: Two facilitated, Zoom-based Group Model Building (GMB) sessions were conducted in March 2021 with eight TGE participants (mean age 38 years; range 22–63; transfeminine and transmasculine identities; multiracial, White, and SWANA racial identities) recruited through a Lesbian Gay Bisexual and Transgender (LGBT) community center, followed by a participant member-checking session to validate loop structure, causal direction, and interpretive accuracy. Analysis focused explicitly on identifying reinforcing and balancing feedback structures, rather than isolated barriers, to explain how policy exposure and institutional gatekeeping are generated over time. Results: Participants co-constructed a nine-variable Causal Loop Diagram (CLD) with six feedback structures, four reinforcing and two balancing that interact dynamically to amplify or dampen policy exposure, institutional gatekeeping, and continuity of care, which were organized across structural, institutional/clinical, and individual/community tiers. Reinforcing dynamics linked structural stigma, exclusion from formal employment, institutionalized provider bias, and enacted stigma to degraded care experience, increased trauma and distrust, and disrupted continuity, manifesting as policy exposure (e.g., coverage volatility, denials) and gatekeeping (e.g., discretionary documentation, referral hurdles). Community-based supports and peer/elder navigation functioned as balancing loops that reduced trauma, improved continuity and encounters, and, over time, dampened provider bias. A salient theme was the visibility/invisibility paradox: symbolic inclusion without workflow redesign can inadvertently increase exposure and reinforce harmful loops. Full article

This paper presents a closed-loop price–dispatch framework for park-scale virtual power plants (VPPs) with coupled electric–thermal processes under high penetrations of photovoltaics (PVs) and electric vehicles (EVs). The outer layer clears time-varying prices for operator electricity, operator heat, and user feed-in using an improved particle swarm optimizer with adaptive coefficients and velocity clamping. Given these prices, the inner layer executes a lightweight linear source decomposition with feasibility projection that enforces transformer limits, combined heat-and-power (CHP) and boiler constraints, ramping, energy balances, and EV state-of-charge requirements. PV uncertainty is represented by a small set of scenarios and a conditional value-at-risk (CVaR) term augments the welfare objective to control tail risk. On a typical winter day case, the coordinated setting aligns EV charging with solar hours, reduces evening grid imports, and improves a social welfare proxy while maintaining interpretable price signals. Measured outcomes include 99.17% PV utilization (95.14% self-consumption and 4.03% routed to EV charging) and a reduction in EV charging cost from CNY 304.18 to CNY 249.87 (−17.9%) compared with an all-from-operator benchmark; all transformer, CHP/boiler, and EV constraints are satisfied. The price loop converges within several dozen iterations without oscillation. Sensitivity studies show that increasing risk weight lowers CVaR with modest welfare trade-offs, while wider price bounds and higher EV availability raise welfare until physical limits bind. The results demonstrate an effective, interpretable, and reproducible pathway to integrate market signals with engineering constraints in park VPP operations. Full article

The integration of complex system concepts and sustainability in chemical engineering education is often limited to elective or separate courses rather than their integration into the core curriculum. This pedagogical gap can lead to graduates who lack a holistic understanding of the intricate interplay between industrial processes and the Earth’s ecological limits, and the feedback loops required to address complex global challenges. This paper presents a transformative approach to close this gap by embedding the Planetary Boundaries framework and system thinking across core chemical engineering courses, such as Material and Energy Balances, Reaction Engineering, and Process Design, and extending this integration to capstone projects. The framework treats the curriculum itself as an interconnected learning system in which key systems concepts are revisited and deepened through contextualized examples and digital modeling tools, including process simulators and life-cycle assessment. We map each boundary to illustrative process examples and learning activities and discuss practical implementation issues such as curriculum crowding, educator readiness, and data availability. This approach aligns with outcome-based education goals by making system thinking and absolute sustainability explicit learning outcomes, preparing future chemical engineers to design processes that respect planetary limits while balancing technical performance, economic feasibility, and societal needs. Full article

To address the limitations of traditional timber mortise-and-tenon joints, particularly their low pull-out resistance and rapid stiffness degradation under cyclic loading, this study proposes a novel integrated sleeve mortise-and-tenon steel–timber composite beam–column joint. Building upon prior experimental validation and numerical model verification, a comprehensive parametric study was conducted to systematically investigate the influence of key geometric parameters on the seismic performance of the joint. The investigated parameters included beam sleeve thickness (1–10 mm), sleeve length (150–350 mm), bolt diameter (4–16 mm), and the dimensions and thickness of stiffeners. The results indicate that a sleeve thickness of 2–3 mm yields the optimal overall performance: sleeves thinner than 2 mm are prone to yielding, while those thicker than 3 mm induce stress concentration in the timber beam. A sleeve length of approximately 250 mm provides the highest initial stiffness and a ductility coefficient exceeding 4.0, representing the best seismic behavior. Bolt diameters within the range of 8–10 mm produce full and stable hysteresis loops, effectively balancing load-carrying capacity and energy dissipation; smaller diameters lead to pinching failure, whereas larger diameters trigger premature plastic deformation in the timber. Furthermore, stiffeners with a width of 40 mm and a thickness of 2 mm effectively enhance joint stiffness, promote a uniform stress distribution, and mitigate local damage. The optimized joint configuration demonstrates excellent ductility, stable hysteretic behavior, and a high load capacity, providing a robust technical foundation for the design and practical application of advanced steel–timber composite connections. Full article

A fast modelling framework is presented for loss estimation in current-source microinverters. The power stage is modelled with ideal switches and simplified magnetics to keep simulations lightweight, while dedicated estimators reconstruct core, conduction, and switching losses from simulated waveforms using Steinmetz-based and analytical models. The method is demonstrated on an interleaved active-clamp flyback with H-bridge unfolder but remains topology-agnostic and applicable to other current source (CS) DC/DC variants. Control includes maximum power point tracking (MPPT) with voltage-reference tracking, a PID loop, simplified grid synchronization, and peak-current regulation. Dynamic tests under irradiance and grid-voltage variations confirm stable operation and correct MPPT behaviour. A steady-state loss breakdown at 0.75 p.u. irradiance predicts ~97% overall efficiency, consistent with reported microinverter performance. The framework enables rapid design exploration and efficiency prediction without full device-level modelling, balancing accuracy and computational speed. Full article

Manganese is a critical raw material and there is currently a great interest in decarbonization in the metallurgical sector for its production. Hydrogen use in manganese and its alloys’ production is in principle possible for sustainable production; however, this requires a technological shift from traditional carbothermic processes to completely new processes; like the HAlMan process. To design a process, it is crucially important to optimize the process conditions (such as temperature) and minimize the quantity of hydrogen gas and the related energy consumptions. In the present work, energy and mass balances for a hydrogen-based reduction reactor were carried out employing thermodynamics software and analytical approaches from room temperatures to 900 °C. It was found that the quantity of hydrogen gas required for the pre-reduction of manganese ore can be significantly reduced via coupling the reduction reactor with a calciner and the hot charge of the calcined ore into the reduction reactor. Moreover, hot H₂-H₂O gas mixture from the reduction reactor outlet can be used for preheating the hydrogen feed of the reactor, and the calcination of the ore, while a portion or all its hydrogen can be recovered and looped. The integrated coupled calcination-reduction process was found to be operated with no external energy supply, or insignificant fuel use. Full article

Sphaerodactylidae play a crucial role in ecosystems, possessing significant ecological, scientific, and conservation value. They contribute to pest control and the maintenance of ecological balance, and also provide abundant materials for research in evolutionary biology and biodiversity. To refine the phylogenetic position of Teratoscincus scincus within the Sphaerodactylidae using mitogenomic data, this study sequenced the complete mitochondrial genome of T. scincus using the Illumina NovaSeq Xplus platform, and subsequently performed assembly, annotation, and analysis. The phylogenetic relationships of T. scincus within the Sphaerodactylidae were analyzed using 13 protein-coding genes (PCGs) from the mitochondrial genome via Bayesian inference (BI) and maximum likelihood (ML) methods. The complete mitochondrial genome of T. scincus is 16,943 bp in length and consists of 13 PCGs, 22 tRNA genes, 2 rRNA genes, and 1 control region (D-loop). The base composition shows a distinct AT preference, with the highest A + T content (56.3%) found in the PCGs region. A phylogenetic tree was constructed based on the amino acid sequences of 13 PCGs from the mitochondrial genomes of nine Sphaerodactylidae species retrieved from GenBank and the newly sequenced T. scincus generated in this study. The results confirm that T. scincus belongs to the genus Teratoscincus within the family Sphaerodactylidae. Phylogenetic analysis reveals that T. scincus and Teratoscincus keyserlingii cluster into a monophyletic group, suggesting a close phylogenetic relationship. Additionally, the phylogenetic tree provides new molecular evidence for understanding the formation mechanism of Sphaerodactylidae diversity. This study not only enriches the mitochondrial genome database of Sphaerodactylidae but also lays an important foundation for subsequent research on the adaptive evolution and conservation biology of T. scincus. Full article

Microbial fuel cells (MFCs) utilizing livestock wastewater represent a critical path toward sustainable energy and net-zero emissions. To maximize this potential, this study investigates a novel circuit configuration, integrating twin MFCs with dual supercapacitors in a closed-loop system, to enhance charge storage and electricity generation. By utilizing molasses-seawater anolytes, the study establishes a performance benchmark for optimizing energy recovery in future livestock wastewater treatment applications. The self-adjusting potential difference between interconnected MFCs is verified, and supercapacitors significantly improve energy harvesting by reducing load impedance and balancing capacitor plate charges. Voltage gain across supercapacitors exceeds that of single MFC charging, demonstrating the benefits of series integration. Experimental results reveal that catholyte properties—electrical conductivity, salinity, pH, and dissolved oxygen—strongly influence MFC performance. Optimal conditions for a neutralized anolyte (pH 7.12) include dissolved oxygen levels of 5.37–5.68 mg/L and conductivity of 24.3 mS/cm. Under these conditions, supercapacitors charged with sterile diluted seawater catholyte store up to 40% more energy than individual MFCs, attributed to increased output current. While the charge balance mechanism of supercapacitors contributes to storage efficiency, its impact is less pronounced than that of conductivity and oxygen solubility. The interplay between electrochemical activation and charge balancing enhances overall electricity harvesting. These findings provide valuable insights into optimizing MFC-supercapacitor systems for renewable energy applications, particularly in livestock wastewater treatment. Full article

This paper presents a method for dimensional synthesis of a pulse-type adjustable speed mechanical drive, realized through a Watt II six-bar linkage combined with an overrunning clutch. The goal is to achieve a transmission ratio that varies smoothly and linearly by adjusting the angle of a control lever, while meeting kinematic, geometric, and force constraints. The kinematic characteristics are derived analytically using vector-loop equations, enabling comparison with a predefined linear reference function. An optimization problem is formulated to minimize the maximum deviation between the actual and reference output angles across the entire operating interval. The solution employs a metaheuristic algorithm for global search followed by a local refinement phase. Three optimization scenarios are analyzed, each with different levels of design freedom regarding the parameters defining the linear reference function. The results demonstrate a clear trade-off between accuracy and functional tunability, highlighting the most effective balance for practical applications. This approach can be used for designing mechanical drives with adjustable speed features and can be applied to other complex linkage systems. Full article