Achieving persistent glycemic control in a painless and convenient way is the ultimate goal of diabetes management. Herein, an “enzyme‐free” polymeric microneedle (MN)‐array patch composed of a ...boronate‐containing hydrogel semi‐interpenetrated by biocompatible silk fibroin is developed. Consistent with the previous reports, the presence of the boronate‐hydrogel allows for glucose‐responsive diffusion‐control of insulin, while the crystalline fibroin component serves as a matrix‐stiffener to validate skin penetration. Remarkably, this “enzyme‐free” smart artificial on‐skin pancreas prototype remains stable for at least 2 months in an aqueous environment. Furthermore, it establishes sustained as well as acute glucose‐responsive insulin delivery, and is to the authors' knowledge, the first successful material design addressing such two technical challenges at once on an MN format. This long‐acting, on‐demand insulin delivery technology may offer a candidate for a next‐generation diabetes therapy that is remarkably stable, safe, economically efficient, and capable of providing both acute‐ and continuous glycemic control in a manner minimally dependent on patient compliance.
An electronics‐free, enzyme‐free, and nanoparticle‐free smart artificial on‐skin pancreas, which is a hybrid microneedle‐array patch fabricated with a glucose‐sensitive boronate‐hydrogel and biocompatible silk fibroin semi‐interpenetrating network, is developed to continuously monitor glucose levels whilst autonomously delivering insulin on demand. This microneedles‐array patch offers long‐acting persistent glycemic control in a safe, convenient, and painless way, which will significantly improve patients' life quality.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Aims
To explore parents’ experiences of using remote monitoring technology when caring for a very young child with type 1 diabetes during a clinical trial.
Methods
Interviews were conducted with ...parents of 30 children (aged 1–7 years) participating in a trial (the KidsAP02 study) comparing hybrid closed‐loop insulin delivery with sensor‐augmented pump therapy. In both arms, parents had access to remote monitoring technology. Data analysis focused on identification of descriptive themes.
Results
Remote monitoring technology gave parents improved access to data which helped them pre‐empt and manage glucose excursions. Parents observed how, when children were in their own care, they could be more absent while present, as their attention could shift to non‐diabetes‐related activities. Conversely, when children were others’ care, remote monitoring enabled parents to be present while absent, by facilitating oversight and collaboration with caregivers. Parents described how remote monitoring made them feel more confident allowing others to care for their children. Parents’ confidence increased when using a hybrid closed‐loop system, as less work was required to keep glucose in range. Benefits to children were also highlighted, including being able to play and sleep uninterrupted and attend parties and sleepovers without their parents. While most parents welcomed the increased sense of control remote monitoring offered, some noted downsides, such as lack of respite from caregiving responsibilities.
Conclusions
Remote monitoring can offer manifold benefits to both parents and very young children with type 1 diabetes. Some parents, however, may profit from opportunities to take ‘time out’.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Aim
Hybrid closed‐loop (HCL) therapy improves glycaemic control in adolescents with type 1 diabetes; however, little is known about their lived experience using these systems. The aim of this study ...was to explore the lived experiences of youth with type 1 diabetes using HCL therapy, and their parents, to provide insight into their lived experiences.
Methods
Adolescents and young adults aged 12–25 years, who used Medtronic MiniMed™ 670G HCL system during a 6‐month randomised clinical trial, and their parents, were invited to participate in a semi‐structured interview at the end of the study. Open‐ended questions were used to explore the lived experiences of families using HCL. The interviews were audio‐recorded, transcribed and analysed using thematic analysis to determine the main themes.
Results
In all, 17 young people with type 1 diabetes mean ± SD age: 17.5 ± 4.2 years, diabetes duration: 11.0 ± 4.9 years and HbA1c 64 ± 9 mmol/mol (8.0 ± 0.8%) and 10 parents were interviewed. Three themes were identified: (1) ‘Developing confidence and trust in the system’, (2) ‘Reduction in anxiety’ and (3) ‘Issues with device’. They reported a positive experience using HCL, with improvements in glucose levels and increased independence with diabetes management. However, frustration around the number of alarms and notifications associated with the system were also identified as issues.
Conclusion
Both youth and parents acknowledged the benefits of this first‐generation HCL system in improving glycaemic outcomes and in providing flexibility and independence. These lived experiences provide valuable information in the introduction and provision of targeted education with HCL therapy.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Urged by the necessity to establish sustainable supply chains (SCs), this study focuses on exploring the closed-loop inventory routing problem (CIRP) for perishable food packed by multi-type ...returnable transport items (RTIs). The selling revenue of perishable food is dependent on food's remaining shelf life and the specific type of RTIs used for packaging. RTI selection decisions need to be jointly considered in the CIRP to weigh the potential benefits against associated costs. For this problem, we first develop an integer linear programme (ILP) to maximise the total profit of the holistic SC. Subsequently, we design a tailored kernel search (KS) matheuristic as an efficient solution. A real CIRP with multi-type RTIs for fresh strawberries is used to demonstrate the practicality of the ILP. For this case study, we perform extensive sensitivity analysis of the relevant parameters, extracting valuable managerial insights. Finally, experiments are conducted on 170 randomly generated instances. Computational results show that the proposed KS manages to achieve competitive solutions for instances with up to 10 retailers much more efficiently than CLPEX. For instances with up to 40 retailers, the KS algorithm significantly outperforms CPLEX in terms of solution quality, improving the obtained profit by 80.03% on average under the same computational time.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
This paper investigates the adaptive event-triggered control problem for a class of nonlinear systems subject to periodic disturbances. To reduce the communication burden, a reliable relative ...threshold strategy is proposed. Fourier series expansion and radial basis function neural network are combined into a function approximator to model suitable time-varying disturbed function of known periods in strict-feedback systems. By combining the Lyapunov stability theory and the backstepping technique, the proposed adaptive control approach ensures that all the signals in the closed-loop system are bounded, and the tracking error can be regulated to a compact set around zero in finite time. Finally, simulation results are presented to verify the effectiveness of the theoretical results.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
As drones become more common today, the threat of reconnaissance or attack drones to core facilities has increased, and countermeasures against them have become essential. In this study, a drone ...redirection system was proposed to counter illegal intrusion of commercial fixed-wing drones. The drone redirection system was designed as a closed-loop system that automatically redirects the drone to a target position. The main novelty of this study is a proposal for a system that can automatically redirect a commercial fixed-wing drone, which has not been previously explored. We proposed two strategies for redirecting drones. Additionally, simple drone modeling with a path-following algorithm was used to easily model various drones. The drone model was then tuned using flight test data, and the results were compared. Simulations were performed on the designed drone redirection system model to verify the performance of the two proposed strategies for redirecting drones in conjunction with drone fail-detection and innovation check. The performance of the drone redirection system was assessed through flight tests of Remo-M and simulations of Micropilot's hardware-in-the-loop simulator (HWILS). Through simple drone modeling, drone flight tests, and the test results from HWILS, it was proved that the drone redirection system can be applied to various fixed-wing drones.
In this study, an adaptive boundary control is presented for vibration suppression of an axially moving belt system. First, the infinite-dimensional model of the belt system including the dynamics of ...high acceleration/deceleration and distributed disturbance is derived by utilising the extended Hamilton's principle. Subsequently, by using Lyapunov's synthesis method and an adaptive technique, an adaptive boundary control is developed to suppress the belt's vibration and compensate for the system parametric uncertainties. With the proposed control, the stability of the closed-loop system and the uniform boundedness of all closed-loop signals are both ensured. Besides, the S-curve acceleration/deceleration method is adopted to plan the belt's axial speed and the disturbance observer is used to mitigate the effects of unknown boundary disturbance. Finally, the control performance of the closed-loop system is successfully demonstrated through simulations.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
This trial assessed safety and effectiveness of an advanced hybrid closed-loop (AHCL) system with automated basal (Auto Basal) and automated bolus correction (Auto Correction) in adolescents and ...adults with type 1 diabetes (T1D).
This multicenter single-arm study involved an intent-to-treat population of 157 individuals (39 adolescents aged 14-21 years and 118 adults aged ≥22-75 years) with T1D. Study participants used the MiniMed™ AHCL system during a baseline run-in period in which sensor-augmented pump +/- predictive low glucose management or Auto Basal was enabled for ∼14 days. Thereafter, Auto Basal and Auto Correction were enabled for a study phase (∼90 days), with glucose target set to 100 or 120 mg/dL for ∼45 days, followed by the other target for ∼45 days. Study endpoints included safety events and change in mean A1C, time in range (TIR, 70-180 mg/dL) and time below range (TBR, <70 mg/dL). Run-in and study phase values were compared using Wilcoxon signed-rank test or paired
-test.
Overall group time spent in closed loop averaged 94.9% ± 5.4% and involved only 1.2 ± 0.8 exits per week. Compared with run-in, AHCL reduced A1C from 7.5% ± 0.8% to 7.0% ± 0.5% (<0.001, Wilcoxon signed-rank test,
= 155), TIR increased from 68.8% ± 10.5% to 74.5% ± 6.9% (<0.001, Wilcoxon signed-rank test), and TBR reduced from 3.3% ± 2.9% to 2.3% ± 1.7% (<0.001, Wilcoxon signed-rank test). Similar benefits to glycemia were observed for each age group and were more pronounced for the nighttime (12 AM-6 AM). The 100 mg/dL target increased TIR to 75.4% (
= 155), which was further optimized at a lower active insulin time (AIT) setting (i.e., 2 h), without increasing TBR. There were no severe hypoglycemic or diabetic ketoacidosis events during the study phase.
These findings show that the MiniMed AHCL system is safe and allows for achievement of recommended glycemic targets in adolescents and adults with T1D. Adjustments in target and AIT settings may further optimize glycemia and improve user experience. Clinical Trial Registration number: NCT03959423.
This research presents a robust model predictive controller of two microgrids (MGs) interconnected via tie-line (TL) power. Power system operations continue to face new challenges due to the large ...integration of renewable energy generation with an active load demand uncertainty and the management and control of bidirectional power flow between MGs and others uncertainties and system nonlinearities due to the power system operating condition. To handle these uncertainties and system nonlinearities a robust model using predictive control scheme is presented in this paper to achieve the control of the active power between two MGs when considering three disturbances scenario models. In the design process, uncertainties and nonlinearities of the system were taken into account and contributed to the robustness of the closed-loop system. Robust control scheme development considering power system nonlinearities and uncertainties were used to improve the online close-loop robustness. The model helped to achieve a desired active power regulation by coordinating the MGs and active power over-shoot and under-shoot time were reduced outstandingly. A Comparison was made between open-loop and close-loop simulation results, which indicate that the model can handle robustness while settling power deviation of the interconnected system. MATLAB environment was used to solve the optimisation problem.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Precision landing on large and small planetary bodies is a technology of utmost importance for future human and robotic exploration of the solar system. In this context, the ...Zero-Effort-Miss/Zero-Effort-Velocity (ZEM/ZEV) feedback guidance algorithm has been studied extensively and is still a field of active research. The algorithm, although powerful in terms of accuracy and ease of implementation, has some limitations. Therefore with this paper we present an adaptive guidance algorithm based on classical ZEM/ZEV in which machine learning is used to overcome its limitations and create a closed loop guidance algorithm that is sufficiently lightweight to be implemented on board spacecraft and flexible enough to be able to adapt to the given constraint scenario. The adopted methodology is an actor-critic reinforcement learning algorithm that learns the parameters of the above-mentioned guidance architecture according to the given problem constraints.
•A Deep Reinforcement Learning (DRL) framework for structured planetary landing guidance is presented.•The DRL framework is based on a customized actor-critic approach that employs Extreme Learning Machines (ELM).•The algorithm learns the ZEM/ZEV generalized feedback guidance gains as function of the spacecraft state.•The gains are adapted to ensure both quasi-optimality and flight-constraints.•Stability analysis shows the proposed approach is globally stable.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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