A High-Precision Single Shooting Method for Solving Hypersensitive Optimal Control Problems

Solving hypersensitive optimal control problems is a long-standing challenge for decades in optimization engineering, mainly due to the possible nonexistence of the optimal solution to meet the required error tolerance under double-precision arithmetic and the hypersensitivity of the optimal solution with respect to the initial conditions. In this paper, a new high-precision single shooting method is presented to address the above two difficulties. Multiple-precision arithmetic and Taylor series method are introduced to provide the accurate optimal solution with arbitrary higher significant digits and arbitrary higher integral accuracy, respectively. Besides, a new modified bidirectional single shooting method is developed, which fully utilizes the three-segment structure of the hypersensitive optimal control problems and provides appropriate initial guess that is close to the optimal solutions. Numerical demonstrations in a typical hypersensitive optimal control problem are presented to illustrate the effectiveness of this new method, which indicates that the accurate optimal solution of this challenging problem can be easily solved by this simple single shooting method within several iterations

On the local convergence of the semismooth Newton method for composite optimization

Existing superlinear convergence rate of the semismooth Newton method relies on the nonsingularity of the B-Jacobian. This is a strict condition since it implies that the stationary point to seek is isolated. In this paper, we consider a large class of nonlinear equations derived from first-order type methods for solving composite optimization problems. We first present some equivalent characterizations of the invertibility of the associated B-Jacobian, providing easy-to-check criteria for the traditional condition. Secondly, we prove that the strict complementarity and local error bound condition guarantee a local superlinear convergence rate. The analysis consists of two steps: showing local smoothness based on partial smoothness or closedness of the set of nondifferentiable points of the proximal map, and applying the local error bound condition to the locally smooth nonlinear equations. Concrete examples satisfying the required assumptions are presented. The main novelty of the proposed condition is that it also applies to nonisolated stationary points.Comment: 25 page

Eco-Stoichiometric Alterations in Paddy Soil Ecosystem Driven by Phosphorus Application

Agricultural fertilization may change processes of elemental biogeochemical cycles and alter the ecological function. Ecoenzymatic stoichiometric feature plays a critical role in global soil carbon (C) metabolism, driving element cycles, and mediating atmospheric composition in response to agricultural nutrient management. Despite the importance on crop growth, the role of phosphorous (P) in compliance with eco-stoichiometry on soil C and nitrogen (N) sequestration in the paddy field remains poorly understood in the context of climate change. Here, we collected soil samples from a field experiment after 6 years of chemical P application at a gradient of 0 (P-0), 30 (P-30), 60 (P-60), and 90 (P-90) kg ha⁻¹ in order to evaluate the role of P on stoichiometric properties in terms of soil chemical, microbial biomass, and eco-enzyme activities as well as greenhouse gas (GHG: CO₂, N₂O and CH₄) emissions. Continuous P input increased soil total organic C and N by 1.3–9.2% and 3%–13%, respectively. P input induced C and N limitations as indicated by the decreased ratio of C:P and N:P in the soil and microbial biomass. A synergistic mechanism among the ecoenzymatic stoichiometry, which regulated the ecological function of microbial C and N acquisition and were stoichiometrically related to P input, stimulated soil C and N sequestration in the paddy field. The lower emissions of N₂O and CH₄ under the higher P application (P-60 and P-90) in July and the insignificant difference in N₂O emission in August compared to P-30; however, continuous P input enhanced CO₂ fluxes for both samplings. There is a technical conflict for simultaneously regulating three types of GHGs in terms of the eco-stoichiometry mechanism under P fertilization. Thus, it is recommended that the P input in paddy fields not exceed 60 kg ha⁻¹ may maximize soil C sequestration, minimize P export, and guarantee grain yields

Multi-dimensional data indexing and range query processing via Voronoi diagram for internet of things

In a typical Internet of Things (IoT) deployment such as smart cities and Industry 4.0, the amount of sensory data collected from physical world is significant and wide-ranging. Processing large amount of real-time data from the diverse IoT devices is challenging. For example, in IoT environment, wireless sensor networks (WSN) are typically used for the monitoring and collecting of data in some geographic area. Spatial range queries with location constraints to facilitate data indexing are traditionally employed in such applications, which allows the querying and managing the data based on SQL structure. One particular challenge is to minimize communication cost and storage requirements in multi-dimensional data indexing approaches. In this paper, we present an energy- and time-efficient multidimensional data indexing scheme, which is designed to answer range query. Specifically, we propose data indexing methods which utilize hierarchical indexing structures, using binary space partitioning (BSP), such as kd-tree, quad-tree, k-means clustering, and Voronoi-based methods to provide more efficient routing with less latency. Simulation results demonstrate that the Voronoi Diagram-based algorithm minimizes the average energy consumption and query response time

Highly efficient room-temperature nonvolatile magnetic switching by current in Fe3GaTe2 thin flakes

Effectively tuning magnetic state by using current is essential for novel spintronic devices. Magnetic van der Waals (vdW) materials have shown superior properties for the applications of magnetic information storage based on the efficient spin torque effect. However, for most of known vdW ferromagnets, the ferromagnetic transition temperatures lower than room temperature strongly impede their applications and the room-temperature vdW spintronic device with low energy consumption is still a long-sought goal. Here, we realize the highly efficient room-temperature nonvolatile magnetic switching by current in a single-material device based on vdW ferromagnet Fe3GaTe2. Moreover, the switching current density and power dissipation are about 300 and 60000 times smaller than conventional spin-orbit-torque devices of magnet/heavymetal heterostructures. These findings make an important progress on the applications of magnetic vdW materials in the fields of spintronics and magnetic information storage.Comment: 18 page2, 4 figure

Alterations of ocular surface parameters in patients with obstructive sleep apnea syndrome

PurposeThis study aimed to evaluate changes in ocular surface parameters among obstructive sleep apnea syndrome (OSAS) patients.Methods44 healthy volunteers (88 eyes) and 27 OSAS patients (54 eyes) were recruited in our cross-sectional study. 14 patients were classified as mild&moderate OSAS, and 13 patients were classified as severe OSAS. For evaluating the ocular surface, the following tests were conducted: the height of tear meniscus (TMH), first non-invasive tear break-up time (FNITBUT), mean non-invasive tear break-up time (MNITBUT), the score of Meibomian gland dropout area (Meiboscore), the tear test of anesthesia-free Schirmer I (SIT), corneal fluorescein staining (CFS), partial blinks rate (PBR), the lipid layer thickness (LLT), ocular surface disease index (OSDI). The results obtained from the study were analyzed and compared among the groups.ResultsFNITBUT, MNITBUT, and TMH were lower. OSDI, CFS, Meiboscore and PBR were higher in the OSAS group than those in the control group. The mild&moderate as well as the severe OSAS subgroups had statistically significantly lower TMH, and higher OSDI and PBR than the control group. Meanwhile, we found there were no significant differences between two OSAS subgroups. CFS was higher in the severe OSAS group than the mild&moderate OSAS group. Significantly lower FNITBUT, MNITBUT and higher Meiboscore were observed in the severe OSAS subgroup than in the control group, and MNITBUT was higher in severe OSAS objects than in the mild&moderate OSAS objects. LLT and SIT did not exhibit significant differences among control and OSAS subgroups. FNITBUT and MNITBUT showed significantly negative correlations with BMI, while Meiboscore showed a significant positive correlation with AHI.ConclusionPatients with OSAS have a tendence of dry eyes, whereas control subjects do not. This indicates us that the OSAS patients should pay more attention to ocular surface care

Plasma Clusterin and the CLU Gene rs11136000 Variant Are Associated with Mild Cognitive Impairment in Type 2 Diabetic Patients

Objective: Type 2 diabetes mellitus (T2DM) is related to an elevated risk of mild cognitive impairment (MCI). Plasma clusterin is reported associated with the early pathology of Alzheimer's disease (AD) and longitudinal brain atrophy in subjects with MCI. The rs11136000 single nucleotide polymorphism within the clusterin (CLU) gene is also associated with the risk of AD. We aimed to investigate the associations among plasma clusterin, rs11136000 genotype and T2DM-associated MCI. Methods: A total of 231 T2DM patients, including 126 MCI and 105 cognitively healthy controls were enrolled in this study. Demographic parameters were collected and neuropsychological tests were conducted. Plasma clusterin and CLU rs11136000 genotype were examined.Results: Plasma clusterin was significantly higher in MCI patients than in control group (p=0.007). In subjects with MCI, plasma clusterin level was negatively correlated with Montreal cognitive assessment and auditory verbal learning test_delayed recall scores (p=0.027 and p=0.020, respectively). After adjustment for age, educational attainment, and gender, carriers of rs11136000 TT genotype demonstrated reduced risk for MCI compared with the CC genotype carriers (OR=0.158, χ2=4.113, p=0.043). Multivariable regression model showed that educational attainment, duration of diabetes, HDL-c, and plasma clusterin levels are associated with MCI in T2DM patients.Conclusions: Plasma clusterin was associated with MCI and may reflect a protective response in T2DM patients. TT genotype exhibited a reduced risk of MCI compared to CC genotype. Further investigations should be conducted to determine the role of clusterin in cognitive decline

Coarse-Super-Resolution-Fine Network (CoSF-Net): A Unified End-to-End Neural Network for 4D-MRI with Simultaneous Motion Estimation and Super-Resolution

Four-dimensional magnetic resonance imaging (4D-MRI) is an emerging technique for tumor motion management in image-guided radiation therapy (IGRT). However, current 4D-MRI suffers from low spatial resolution and strong motion artifacts owing to the long acquisition time and patients' respiratory variations; these limitations, if not managed properly, can adversely affect treatment planning and delivery in IGRT. Herein, we developed a novel deep learning framework called the coarse-super-resolution-fine network (CoSF-Net) to achieve simultaneous motion estimation and super-resolution in a unified model. We designed CoSF-Net by fully excavating the inherent properties of 4D-MRI, with consideration of limited and imperfectly matched training datasets. We conducted extensive experiments on multiple real patient datasets to verify the feasibility and robustness of the developed network. Compared with existing networks and three state-of-the-art conventional algorithms, CoSF-Net not only accurately estimated the deformable vector fields between the respiratory phases of 4D-MRI but also simultaneously improved the spatial resolution of 4D-MRI with enhanced anatomic features, yielding 4D-MR images with high spatiotemporal resolution