Search Results (412)

Background: Diabetic ketoacidosis (DKA) in patients with kidney failure receiving dialysis presents a formidable clinical challenge. Standard DKA protocols, designed for patients with preserved renal function, often fail in this cohort and can be unsafe when applied without modification. Patients are at risk of iatrogenic fluid overload, dyskalaemia, and hypoglycaemia due to altered insulin kinetics, impaired gluconeogenesis, and the absence of osmotic diuresis. Purpose: This narrative review aims to synthesise current understanding of DKA pathophysiology in dialysis patients, delineate distinct clinical phenotypes, and propose individualised management strategies grounded in physiology-based reasoning, comparative guideline insights, and consensus-supported literature. Methods: We searched PubMed/MEDLINE, Embase, and Google Scholar (January 2004–June 2024) for adult dialysis populations, using terms spanning DKA, kidney failure, insulin kinetics, fluid balance, and cerebral oedema. Reviews, observational cohorts, guidelines, consensus statements, and physiology papers were prioritised; case reports were used selectively for illustration. Evidence was weighted by physiological plausibility and practice relevance. Nephrology-led authors aimed for a pragmatic, safety-first synthesis, seeking and integrating contradictory recommendations. Conclusions: Our findings highlight the critical need for a nuanced approach to fluid management, a tailored insulin strategy that accounts for glucose-insulin decoupling and prolonged insulin half-life, and careful consideration of potassium and acidosis correction. We emphasise the importance of recognising specific volume phenotypes (hypovolaemic, euvolaemic, hypervolaemic) to guide fluid therapy, and advocating the judicious use of variable-rate insulin infusions (‘dry insulin’) to mitigate fluid overload. We also show that service-level factors are critical. Dialysis-specific pathways, interdisciplinary training, and quality improvement metrics can reduce iatrogenic harm. By linking physiology with workflow adaptations, this review provides a physiologically sound, bedside-oriented map for navigating this complex emergency safely and effectively. In doing so, it advances an individualised model of DKA care for dialysis-dependent patients. Full article

With the rapid development of unmanned aerial vehicle (UAV) technology, quadrotor UAVs have demonstrated extensive application potential in various fields. However, due to parameter uncertainties and strong coupling, the flight attitude of quadrotors is prone to external disturbances, posing challenges for achieving precise control and stable flight. In this paper, we address the tracking control problem under unknown command rate variations by proposing a Modified Linear Active Disturbance Rejection Control (LADRC) strategy, aiming to enhance flight stability and anti-disturbance capability in complex environments. First, based on the attitude dynamics model of quadrotors, an LADRC technique is adopted to realize three-channel decoupling-free control. By integrating a parameter estimator, the proposed method can compensate unknown disturbances in real time, thereby improving the system’s anti-disturbance ability and dynamic response performance. Second, to further enhance system robustness, a linear extended state observer (LESO) is designed to accurately estimate the tracking error rate and total disturbances. Additionally, a Levant differentiator is introduced to replace the traditional differentiation component for optimizing the response speed of command rate. Finally, a modified LADRC controller incorporating error rate estimation is constructed. Simulation results validate that the proposed scheme maintains good tracking accuracy under high-frequency disturbances, providing an effective solution for stable UAV flight in complex scenarios. Compared with traditional control methods, the modified LADRC strategy exhibits significant advantages in tracking performance, anti-disturbance capability, and dynamic response. This research not only offers a novel perspective and solution for quadrotor control problems but also holds important implications for improving UAV performance and reliability in practical applications. Full article

Snow cover, as a critical component of the global climate system, strongly influences ecological processes in cold and temperate regions. However, how different ecosystem components—plants, soils, and microbes—respond to snow cover change remains poorly understood, especially in terms of their coordination. Here, we conducted a global meta-analysis of 1986 single and 1047 paired observations from snow manipulation experiments across diverse terrestrial ecosystems. Our results showed that snow removal generally reduced SWC and microbial diversity, whereas snow addition exerted smaller or more variable influences across ecosystem components. Among all variables, the effect of snow cover change on soil water content was most pronounced, whereas its impacts on other factors were generally weak. Notably, the direction and magnitude of responses often differed among ecosystem components exposed to the same treatments. Pairwise comparisons revealed frequent mismatches between plant and soil organism responses, indicating substantial ecosystem-level decoupling across biomes. These findings support the ecosystem asynchrony hypothesis and highlight the need for integrated approaches that link aboveground and belowground processes. Our study improves the understanding of ecosystem stability under changing snow regimes and provides insights for predicting future terrestrial responses to global climate change. Full article

This paper investigates actuator fault-tolerant cooperative control of multiple quadrotor unmanned aerial vehicles (multi-QUAVs) under restricted communication conditions, where only relative output measurements are available. By appropriately transforming and scaling the control inputs and outputs of the multi-QUAVs, an observable subsystem is constructed. A decoupled fault estimation observer is then designed for this subsystem to estimate actuator faults and the leader’s input signal. Based on the fault estimation information and relative measurement information among QUAVs, a node-based active fault-tolerant cooperative control law is developed. This approach enables multi-QUAVs to achieve consensus-based formation solely relying on relative output information, even in the presence of actuator faults. Finally, the effectiveness of the proposed active fault-tolerant cooperative control method is verified by simulation. Full article

Against the backdrop of China’s “dual carbon” strategy (carbon peaking and carbon neutrality), provincial-level carbon emission research is crucial for the implementation of related policies. However, existing studies insufficiently cover the driving mechanisms and scenario prediction for energy-importing provinces. This study can provide theoretical references for similar provinces in China to conduct research on carbon dioxide emissions from energy consumption. The carbon dioxide emissions from energy consumption in Jiangsu Province between 2000 and 2023 were calculated using the carbon emission coefficient method. The Tapio decoupling index model was adopted to evaluate the decoupling relationship between economic growth and carbon dioxide emissions from energy consumption in Jiangsu. An extended STIRPAT model was established to predict carbon dioxide emissions from energy consumption in Jiangsu, and this model was applied to analyze the emissions under three scenarios (baseline scenario, low-carbon scenario, and enhanced low-carbon scenario) during 2024–2030. The results show the following: (1) During 2000–2023, the carbon dioxide emissions from energy consumption in Jiangsu Province ranged from 215.22428 million tons to 783.94270 million tons, with an average of 549.96280 million tons. (2) The decoupling status between carbon dioxide emissions from energy consumption and economic development in Jiangsu was dominated by weak decoupling, accounting for 91.304%, while a small proportion (8.696%) of expansive coupling was also observed. (3) Under the baseline scenario, the carbon dioxide emissions from energy consumption in Jiangsu in 2030 will reach 796.828 million tons; under the low-carbon scenario, the emissions will be 786.355 million tons; and under the enhanced low-carbon scenario, the emissions will be 772.293 million tons. Furthermore, countermeasures and suggestions for reducing carbon dioxide emissions from energy consumption in Jiangsu are proposed, mainly including strengthening the guidance of policies and institutional systems, optimizing the energy consumption structure, intensifying technological innovation efforts, and enhancing government promotion and publicity. Full article

This study investigates how process manufacturing enterprises can optimize semi-finished inventory (SFI) distribution in delayed production models, with particular attention to differences in cost volatility between single- and multi-period planning scenarios. To address this research gap, we develop a mixed-integer programming model that determines optimal customer order decoupling point (CODP)/product differentiation point (PDP) positions and SFI quantities (both generic and dedicated) for each production period, employing particle swarm optimization for solution derivation and validating findings through a comprehensive case study of a steel manufacturer with characteristic long-period production processes. The analysis yields two significant findings: (1) single-period operations demonstrate marked cost sensitivity to service level requirements and delay penalties, necessitating end-stage inventory buffers, and (2) multi-period optimization generates a distinctive cost-smoothing effect through strategic order deferrals and cross-period inventory reuse, resulting in remarkably stable total costs (≤2% variation observed). The study makes seminal theoretical contributions by revealing the convex cost sensitivity of short-term inventory decisions versus the near-flat cost trajectories achievable through multi-period planning, while establishing practical guidelines for process industries through its empirically validated two-period threshold for optimal order deferral and inventory positioning strategies. Full article

This paper addresses the problem of observer-based control (OBC) for nonlinear systems with time delay (TD). A novel hybrid modeling framework for nonlinear TD systems is first introduced by synergistically combining TD Takagi–Sugeno (TDTS) fuzzy and Lipschitz approaches. The proposed methodology broadens the range of representable systems by enabling Lipschitz nonlinearities to fulfill dual functions: they may describe essential dynamic behaviors of the system or represent aggregated uncertainties, depending on the specific application. The proposed TDTS–Lipschitz (TDTSL) model class features measurable premise variables while accommodating Lipschitz nonlinearities that may depend on unmeasurable system states. Then, through the construction of an appropriate Lyapunov–Krasovskii (L-K) functional, we derive sufficient conditions to ensure exponential stability of the augmented closed-loop model. Subsequently, through a decoupling methodology, these stability conditions are reformulated as a set of linear matrix inequalities (LMIs). Finally, the proposed OBC design is validated through application to a continuous stirred tank reactor (CSTR) with lumped uncertainties. Full article

China’s coastal fisheries face challenges to their sustainability due to climate and human-induced pressures on key habitat drivers. This study provides an 18-year (2003–2020) assessment of six key ecological and data-available environmental factors (sea-surface temperature (SST), salinity, transparency, currents (eastward velocity, EV; northward velocity, NV), and net primary productivity (NPP), selected for their ecological relevance and data availability, across the Bohai, Yellow, and East China Seas at a spatial resolution of 0.083°. Non-parametric trend tests and seasonal climatologies were applied using MODIS-Aqua and CMEMS data with a refined quasi-analytical algorithm (QAA-v6). The results show distinct gradients: SST ranging from 9 to 13 °C (Bohai Sea) to >20 °C (East China Sea); transparency ranging from <5 m (turbid coasts) to 29.20 m (offshore). Seasonal peaks occurred for SST (summer: 18.92 °C), transparency (summer: 12.54 m), and primary productivity (spring: 1289 mg/m²). Long-term trends reveal regional SST warming in the northern Yellow Sea (9.78% of the area), but cooling in the central East China Sea. Widespread increases in transparency were observed (65.14% of the area), though productivity declined significantly (27.3%). The drivers showed spatial coupling (e.g., SST–salinity r = 0.95), but the long-term trends were decoupled. This study provides a comprehensive and long-term assessment of multiple key habitat drivers across China’s coastal seas. The results provide an unprecedented empirical baseline and dynamic management tools for China’s changing coastal ecosystems. Full article

During the suspension flight of high-altitude scientific balloons in near-space, they are highly vulnerable to time-varying wind field disturbances, which tend to excite multiple distinctive torsional modes of the balloons themselves, thereby interfering with the observations of balloon-borne equipment. Focusing on the azimuth control of the balloon-borne gondola, this paper designs a simplified decoupling mechanism and a reaction wheel as actuators. Specifically, the reaction wheel achieves azimuth tracking through angular momentum exchange, while the simplified decoupling mechanism performs the functions of decoupling and unloading. To fully utilize the control performance of the actuating structure, this paper further proposes a control algorithm based on a nonlinear differential tracker and neural network PID. Simulation results demonstrate that under typical wind disturbances and sensor noise conditions, the proposed system exhibits excellent smoothness and high-precision and stable control performance. This research provides a significant basis for stable observation platforms in precise near-space observation missions. Full article

The adverse propagation environment in underground coal mine tunnels caused by enclosed spaces, rough surfaces, and dense scatterers severely degrades reliable wireless signal transmission, which further impedes the deployment of IoT applications such as gas monitors and personnel positioning terminals. However, the conventional power enhancement solutions are infeasible for the underground coal mine scenario due to strict explosion-proof safety regulations and battery-powered IoT devices. To address this challenge, we propose singular value decomposition-based Lagrangian optimization (SVD-LOP) to minimize transmit power at the mining base station (MBS) for IRS-assisted coal mine wireless communication systems. In particular, we first establish a three-dimensional twin cluster geometry-based stochastic model (3D-TCGBSM) to accurately characterize the underground coal mine channel. On this basis, we formulate the MBS transmit power minimization problem constrained by user signal-to-noise ratio (SNR) target and IRS phase shifts. To solve this non-convex problem, we propose the SVD-LOP algorithm that performs SVD on the channel matrix to decouple the complex channel coupling and introduces the Lagrange multipliers. Furthermore, we develop a low-complexity successive convex approximation (LC-SCA) algorithm to reduce computational complexity, which constructs a convex approximation of the objective function based on a first-order Taylor expansion and enables suboptimal solutions. Simulation results demonstrate that the proposed SVD-LOP and LC-SCA algorithms achieve transmit power peaks of $20.8\mathrm{dBm}$ and $21.4\mathrm{dBm}$, respectively, which are slightly lower than the $21.8\mathrm{dBm}$ observed for the SDR algorithm. It is evident that these algorithms remain well below the explosion-proof safety threshold, which achieves significant power reduction. However, computational complexity analysis reveals that the proposed SVD-LOP and LC-SCA algorithms achieve $\mathcal{O}\left(N^3\right)$ and $\mathcal{O}\left(N^2\right)$ respectively, which offers substantial reductions compared to the SDR algorithm’s $\mathcal{O}\left(N^7\right)$. Moreover, both proposed algorithms exhibit robust convergence across varying user SNR targets while maintaining stable performance gains under different tunnel roughness scenarios. Full article

This study examines the impact of corporate social responsibility (CSR) decoupling on investment efficiency through the lens of systems thinking, using 34,143 firm-year observations from Chinese listed firms between 2009 and 2022. CSR decoupling is conceptualized as a systemic misalignment between two interrelated governance subsystems: the externally facing legitimacy subsystem and the internally embedded strategic action subsystem. Drawing on legitimacy theory and systems thinking, we find that CSR decoupling significantly reduces investment efficiency, primarily through overinvestment, with no consistent evidence of underinvestment. Furthermore, this effect is amplified in tightly coupled supply chain systems and is especially pronounced in foreign-owned firms. The findings contribute to the integration of systems thinking into CSR and corporate governance research, emphasizing the role of structural coupling strength in shaping the consequences of symbolic–substantive misalignment. The study also offers managerial and policy implications for improving the alignment between external CSR communication and internal strategic execution to enhance investment discipline and long-term value creation. Full article

Environmental control in closed environment agricultural systems (CEA) is challenging due to the high energy demand and the dynamic interactions between plants and their heterogeneous phylloclimate. Optimization of crop production in CEA systems therefore requires a thorough understanding of whole-plant functioning and the interconnected plant-climate interactions. Such optimization is limited by an incomplete knowledge of how leaf-level measurements of gas exchange relate to whole-plant processes and how to scale-up point measurements of the heterogeneous environment to inform plant-level decisions. To address both, a dynamic whole-plant gas exchange system was developed to quantify the effect of temperature, relative humidity and light intensity on whole-plant photosynthetic and transpiration rates in lettuce (Lactuca sativa L.). Results showed that light intensity was the primary driver for whole-plant photosynthesis, with temperature optima increasing from 5 °C at a photosynthetic photon flux density (PPFD) of 150 µmol·m⁻²·s⁻¹ to 13 °C at 400 µmolm⁻²·s⁻¹. These optima for lettuce plants were 10 to 20 °C lower than those observed at leaf level due to a shifted balance between respiration and photosynthesis within the complex habitus of lettuce. The results showed a decoupling of transpiration and photosynthesis under high relative humidity, with vapour pressure deficit (VPD) values of 0.5 kPa or lower, which physically limited transpiration. The newly developed dynamic gas exchange system has proven to be a helpful tool for examining the relative importance and combined effects of environmental factors on whole-plant photosynthesis and transpiration. Potential future applications of this system include research on phylloclimate, implementation in production facilities, and validation of crop models. Full article

This study investigates multi-level coupled dynamic issues in near-space balloon-borne astronomical observation platforms subjected to multi-source disturbances, proposing an integrated azimuth pointing control scheme combining unified modeling with composite control strategies. A nonlinear dynamic model is established to characterize inertial coupling effects between the gondola system and secondary gimbal platform. The velocity-loop feedback mechanism utilizing fiber-optic gyroscopes achieves base disturbance decoupling, while an adaptive fuzzy PID controller enhances position-loop disturbance rejection capabilities. A gain adaptation strategy coordinates hierarchical control dynamics, complemented by anti-windup constraints safeguarding actuator operational boundaries. Simulation verifications confirm the exceptional high-precision pointing capability and robust stability under representative wind disturbances and sensor noise conditions. The system maintains a superior control performance across parameter perturbation scenarios, demonstrating consistent operational reliability. This study provides an innovative technical paradigm for precision observation missions in near space. Full article

The complex interference created by several sources for pipelines has not been sufficiently studied. In this study, four types of interference sources were monitored and analyzed. AC voltage monitoring, DC potential monitoring, current density monitoring, and excavation observation and measurement for test pieces and the decouplers were employed to assess the AC/DC interference of one real buried pipeline in situ. The peak value obtained from the second measurement at Pile 33 decreased from 1341.8 V to 143.7 V, indicating that the 1341.8 V in the first measurement may be caused by a sudden grounding of the electrode, while the 143.7 V may be caused by the normal induced voltage. The most negative DC interference potential between the pipeline and the Cu/CuSO₄ reference electrode was −11.946 V. The most positive DC interference potential between the pipeline and the Cu/CuSO₄ reference electrode was 4.862 V. Pile 3 had a maximum DC current density of 240 mA/m², and Pile 4 had a maximum AC current density of 0.615 A/m². After excavating the test piece at Pile 3, the point with maximum DC interference, there were obvious pitting corrosion characteristics, and the corrosion products were mainly γ-FeOOH and Fe₃O₄. It indicated that the coupling of long-term higher positive DC current density or (DC potential) and short-term higher transient AC voltage or (AC current density) may lead to corrosion. After excavating the test piece at the point with maximum AC interference, namely, Pile 4, there were no significant AC or DC corrosion characteristics. This finding suggested that the combination of long-term low AC current voltage or (low AC current density) and long-term more negative low DC current density or (DC potential) did not result in obvious corrosion. The decouplers in this measurement significantly reduced AC interference above 2 V, but the isolation of transient AC shocks and AC interference below 2 V were not significant. During analysis of AC and DC interference, in addition to considering the value of the interference, the duration time of the interference was also an important factor. Instantaneous sharp peaks cannot represent the long-term average voltage or potential current density. The average value should be used as the main basis for judgement, and the instantaneous value should be used as the secondary basis for judgement. Full article

Leveling of the crane support platform plays a vital role in operational safety and lifting efficiency; it requires both precise horizontal positioning and the rational distribution of outrigger load. However, the current synchronous leveling methods mainly focus on displacement synchronization leveling while neglecting the control of outrigger load, resulting in the problem of individual outrigger overloading. To address this problem, a synchronous leveling control method with variable load constraints (SLCM-VLC) is proposed in this paper based on the framework of model predictive control. Firstly, the proposed method conducts independent outrigger modeling and decoupling of outriggers through adjacent cross-coupling; then a displacement synchronization controller (DSC) is designed to ensure efficient synchronous leveling. Secondly, a collaborative controller of displacement and force (DFCC) under variable load constraints is designed to overcome the limitations of traditional independent optimization. Subsequently, an extended state observer (ESO) is introduced to compensate for environmental disturbances and control deviations. Finally, the effectiveness of the proposed method is verified through a co-simulation using Matlab, Adams, and Solidworks. The results show that, compared with existing leveling control methods, the proposed method can achieve high precision and rapid leveling under smaller peak load, thereby extending the service life of the platform’s electric cylinders. Full article