Heterogeneous temporal representation for diabetic blood glucose prediction

Background and aims: Blood glucose prediction (BGP) has increasingly been adopted for personalized monitoring of blood glucose levels in diabetic patients, providing valuable support for physicians in diagnosis and treatment planning. Despite the remarkable success achieved, applying BGP in multi-patient scenarios remains problematic, largely due to the inherent heterogeneity and uncertain nature of continuous glucose monitoring (CGM) data obtained from diverse patient profiles.Methodology: This study proposes the first graph-based Heterogeneous Temporal Representation (HETER) network for multi-patient Blood Glucose Prediction (BGP). Specifically, HETER employs a flexible subsequence repetition method (SSR) to align the heterogeneous input samples, in contrast to the traditional padding or truncation methods. Then, the relationships between multiple samples are constructed as a graph and learned by HETER to capture global temporal characteristics. Moreover, to address the limitations of conventional graph neural networks in capturing local temporal dependencies and providing linear representations, HETER incorporates both a temporally-enhanced mechanism and a linear residual fusion into its architecture.Results: Comprehensive experiments were conducted to validate the proposed method using real-world data from 112 patients in two hospitals, comparing it with five well-known baseline methods. The experimental results verify the robustness and accuracy of the proposed HETER, which achieves the maximal improvement of 31.42%, 27.18%, and 34.85% in terms of MAE, MAPE, and RMSE, respectively, over the second-best comparable method.Discussions: HETER integrates global and local temporal information from multi-patient samples to alleviate the impact of heterogeneity and uncertainty. This method can also be extended to other clinical tasks, thereby facilitating efficient and accurate capture of crucial pattern information in structured medical data

Impact Analysis of Initial Cracks’ Angle on Fatigue Failure of Flange Shafts

A fatigue test on the failure mode of flange shafts was conducted. The propagation characteristics of the initial crack at the junction between the shaft and the flange as well as its angle effect were studied. This study developed an analysis program of fatigue crack propagation, based on the APDL (ANSYS Parametric Design Language). It obtained the effective angle interval within which the initial crack is able to propagate. The fitting calculation formula was derived and the results showed that: (1) The initial crack at the junction between the shaft and the flange would propagate in the radial and axial directions; the unstable crack propagation would cause an abrupt fracture of the cross-section, failing connection; and the angle of initial crack was uncertain. (2) The crack followed the I-II-III mixed mode, which was dominated by mode I. An initial crack with a larger angle showed more noticeable II-III characteristics; KII and KIII affected the crack’s propagation angle in the radial and axial directions and they also affected the structure’s surface direction. (3) The deepest point A of the crack was located at the junction between the shaft and the flange. Its crack propagation can be divided into three stages: rapid growth (stage 1), steady decline (stage 2, buffer stage), and instability (stage 3). The initial crack angle not only affected the propagation rate at stage 1 but also influenced the fatigue life distribution of the structure during propagation. The larger the initial crack angle was, the smaller the proportion of buffer stage in the total fatigue life would be. Moreover, the propagation of crack with a larger initial angle reached instability faster after stage 1, which would cause an abrupt fracture of the cross-section. This was unfavorable for deciding the crack detection time or carrying out maintenance and reinforcement. (4) The crack propagation at the junction between the shaft and the flange was determined by the size relation between ΔKI and ΔKth, instead of the effective stress intensity factor. The effective stress intensity factor can partly reflect the law of crack propagation, but cannot serve as the only criterion for crack propagation; it must be combined with the effective angle interval, which was negatively correlated with the crack’s shape ratio, to determine whether the crack would propagate

Graphene-encapsulated sulfur (GES) composites with a core-shell structure as superior cathode materials for lithium-sulfur batteries

Relatively uniform sized graphene-encapsulated sulphur (GES) composites with a core (S)-shell (graphene) structure were synthesized in one pot based on a solution-chemical reaction-deposition method. These novel GES particles were characterized by XRD, Raman spectrometry, SEM, TGA, EDS and TEM. The electrochemical tests showed that the present GES composites exhibit high specific capacity, good discharge capacity retention and superior rate capability when they were employed as cathodes in rechargeable Li-S cells. A high sulphur content (83.3 wt%) was obtained in the GES composites. Stable discharge capacities of about 900, 650, 540 and 480 mA h g(-1) were achieved at 0.75, 2.0, 3.0 and 6.0 C, respectively. The good electrochemical performance is attributed to the high electrical conductivity of the graphene, the reasonable particle size of sulphur particles, and the core-shell structures that have synergistic effects on facilitating good transport of electrons from the poorly conducting sulphur, preserving fast transport of lithium ions to the encapsulated sulphur particles, and alleviating the polysulfide shuttle phenomenon. The present finding may provide a significant contribution to the enhancement of cathodes for the lithium-sulphur battery technology

DataSheet1_Heterogeneous temporal representation for diabetic blood glucose prediction.PDF

Background and aims: Blood glucose prediction (BGP) has increasingly been adopted for personalized monitoring of blood glucose levels in diabetic patients, providing valuable support for physicians in diagnosis and treatment planning. Despite the remarkable success achieved, applying BGP in multi-patient scenarios remains problematic, largely due to the inherent heterogeneity and uncertain nature of continuous glucose monitoring (CGM) data obtained from diverse patient profiles.Methodology: This study proposes the first graph-based Heterogeneous Temporal Representation (HETER) network for multi-patient Blood Glucose Prediction (BGP). Specifically, HETER employs a flexible subsequence repetition method (SSR) to align the heterogeneous input samples, in contrast to the traditional padding or truncation methods. Then, the relationships between multiple samples are constructed as a graph and learned by HETER to capture global temporal characteristics. Moreover, to address the limitations of conventional graph neural networks in capturing local temporal dependencies and providing linear representations, HETER incorporates both a temporally-enhanced mechanism and a linear residual fusion into its architecture.Results: Comprehensive experiments were conducted to validate the proposed method using real-world data from 112 patients in two hospitals, comparing it with five well-known baseline methods. The experimental results verify the robustness and accuracy of the proposed HETER, which achieves the maximal improvement of 31.42%, 27.18%, and 34.85% in terms of MAE, MAPE, and RMSE, respectively, over the second-best comparable method.Discussions: HETER integrates global and local temporal information from multi-patient samples to alleviate the impact of heterogeneity and uncertainty. This method can also be extended to other clinical tasks, thereby facilitating efficient and accurate capture of crucial pattern information in structured medical data.</p

Observation of non-superconducting phase changes in nitrogen doped lutetium hydrides

Abstract The recent report of near-ambient superconductivity and associated color changes in pressurized nitrogen doped lutetium hydride has triggered worldwide interest and raised major questions about the nature and underlying physics of these latest claims. Here we report synthesis and characterization of high-purity nitrogen doped lutetium hydride LuH2±x N y . We find that pressure conditions have notable effects on Lu-N and Lu-NH chemical bonding and the color changes likely stem from pressure-induced electron redistribution of nitrogen/vacancies and interaction with the LuH2 framework. No superconducting transition is found in all the phases at temperatures 1.8-300 K and pressures 0-38 GPa. Instead, we identify a notable temperature-induced resistance anomaly of electronic origin in LuH2±x N y , which is most pronounced in the pink phase and may have been erroneously interpreted as a sign of superconducting transition. This work establishes key benchmarks for nitrogen doped lutetium hydrides, allowing an in-depth understanding of its novel pressure-induced phase changes