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HighlightsA facile and effective epitaxial-like growth strategy is applied to fabricate the NiSe2/Ni(OH)2 heterojunction composite.The assembled asymmetric supercapacitor based on the heterojunction composite surpasses most of the reported results. It is the first time that the powdered electrode materials can have such large capacity, high rate, and extreme long cycle life.Constructing heterojunction is a promising way to improve the charge transfer efficiency and can thus promote the electrochemical properties. Herein, a facile and effective epitaxial-like growth strategy is applied to NiSe2 nano-octahedra to fabricate the NiSe2-(100)/Ni(OH)2-(110) heterojunction. The heterojunction composite and Ni(OH)2 (performing high electrochemical activity) is ideal high-rate battery-type supercapacitor electrode. The NiSe2/Ni(OH)2 electrode exhibits a high specific capacity of 909 C g−1 at 1 A g−1 and 597 C g−1 at 20 A g−1. The assembled asymmetric supercapacitor composed of the NiSe2/Ni(OH)2 cathode and p-phenylenediamine-functional reduced graphene oxide anode achieves an ultrahigh specific capacity of 303 C g−1 at 1 A g−1 and a superior energy density of 76.1 Wh kg−1 at 906 W kg−1, as well as an outstanding cycling stability of 82% retention for 8000 cycles at 10 A g−1. To the best of our knowledge, this is the first example of NiSe2/Ni(OH)2 heterojunction exhibiting such remarkable supercapacitor performance. This work not only provides a promising candidate for next-generation energy storage device but also offers a possible universal strategy to fabricate metal selenides/metal hydroxides heterojunctions.

Facile design of economic-effective hydrogen evolution reaction (HER) catalysts with non-noble materials are promising for the production of renewable chemical fuels. Two-dimensional (2D) ultrathin transition metal dichalcogenides (TMDs) materials with large specific surface area and abundant catalytic active sites can significantly enhance their catalytic activities. Herein, we design and synthesize an atomically thin Ni-Se-S based hybrid nanosheet (NiSe 1.2 S 0.8 ) via a simple solvothermal method, the thickness of NiSe 1.2 S 0.8 nanosheets is only about 1.1 nm. Benefiting from the ultrathin nanostructure and rich defects, the optimal NiSe 1.2 S 0.8 exhibits good electrocatalytic activity with the overpotential of 144 mV at −10 mA·cm−2, a small Tafel slope of 59 mV·dec −1 , and outstanding catalytic stability in acid electrolyte for HER. The theoretical results show that hybrid electrocatalyst by S incorporation possesses the optimal adsorption free energy of hydrogen (Δ G H* ). This study provides a simple method to synthesize a highperformance multicomponent electrocatalysts with the ultrathin nanostructures and abundant defects.

To propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), 3D-T1-weighted imaging (3D-T1WI), and demographic characteristics to diagnose mild cognitive impairment (MCI) in patients with unilateral middle cerebral artery (MCA) steno-occlusive disease. The performances of different algorithms on the MCI dataset were evaluated using 5-fold cross-validation. The diagnostic results of the multimodal performance were evaluated using t-distributed stochastic neighbor embedding (t-SNE) analysis. The four-modal analysis method proposed in this study was applied to identify brain regions and connections associated with MCI, thus confirming its validity. Based on the fusion of the topological features of the multimodal FBN and SBN, the accuracy for the diagnosis of MCI in patients with unilateral MCA steno-occlusive disease reached 90.00%. The accuracy, recall, sensitivity, and F1-score were higher than those of the other methods, as was the diagnostic efficacy (AUC = 0.9149). The multimodal FBN and SBN topological feature fusion technique, which incorporates rs-fMRI, DTI, 3D-T1WI, and demographic characteristics, obtains the most discriminative features of MCI in patients with unilateral MCA steno-occlusive disease and can effectively identify disease-related brain areas and connections. Efficient automated diagnosis facilitates the early and accurate detection of MCI and timely intervention and treatment to delay or prevent disease progression.

This study aimed to investigate the diagnostic value of combined glutamate chemical exchange saturation transfer (GluCEST) imaging and γ-aminobutyric acid (GABA)-edited proton magnetic resonance spectroscopy ( 1 H-MRS) in localizing epileptogenic foci and differentiating drug-resistant epilepsy (DR) from drug-responsive epilepsy (DRES) in temporal lobe epilepsy (TLE) using 5T MRI. Twenty-four TLE patients (13 left, 11 right) and 25 age-/gender-matched healthy controls (HCs) underwent GluCEST and MEGA-PRESS MRS at 5T MRI. Directional asymmetry indices (DAIglu_H for hippocampus, DAIglu_A for amygdala) and a novel composite biomarker (DAIglu_GABA) integrating GluCEST asymmetry and GABA/Cr ratios were analyzed. Another asymmetry metric was employed to discriminate the left and right TLE groups [DAIglu_H(epi) for hippocampus, DAIglu_A(epi) for amygdala]. Subgroup comparisons (HC vs. DR vs. DRES) and receiver-operating characteristic (ROC) analyses were performed.

White matter hyperintensity (WMH) is common in healthy adults in their 60s and can be seen as early as in their 30s and 40s. Alterations in the brain structural and functional profiles in adults with WMH have been repeatedly studied but with a focus on late-stage WMH. To date, structural and functional MRI profiles during the very early stage of WMH remain largely unexplored. To address this, we investigated multimodal MRI (structural, diffusion, and resting-state functional MRI) profiles of community-dwelling asymptomatic adults with very early-stage WMH relative to age-, sex-, and education-matched non-WMH controls. The comparative results showed significant age-related and age-independent changes in structural MRI-based morphometric measures and resting-state fMRI-based measures in a set of specific gray matter (GM) regions but no global white matter changes. The observed structural and functional anomalies in specific GM regions in community-dwelling asymptomatic adults with very early-stage WMH provide novel data regarding very early-stage WMH and enhance understanding of the pathogenesis of WMH.

A novel approach for designing a dual-band bandpass filter (BPF) using defected stub loaded resonator (DSLR) is presented in this paper. The proposed DSLR consists of two fundamental resonant modes and some resonant characteristics have been investigated by EM software of Ansoft HFSS. Then, based on two coupled DSLRs, a dual-band response BPF that operates at 2.4 GHz and 3.5 GHz is designed and implemented for WLAN and WIMAX application. The first passband is constructed by two lower frequencies of the coupled DSLRs and the second passband is produced by two higher ones; the coupling scheme of them is also given. Finally, the dual-band BPF is fabricated and measured; a good agreement between simulation and measurement is obtained, which verifies the validity of the design methodology.

TACE and TKI-based combination therapy shows promise for unresectable hepatocellular carcinoma (uHCC), but inter-patient heterogeneity requires reliable biomarkers for personalized management. We developed a deep learning model to predict objective response and progression-free survival (PFS) in HBV-related uHCC. We retrospectively analyzed 243 patients, partitioned into training (clinical n = 168; radiomics n = 106) and test (n = 75) datasets. Three models were constructed: a Clinical Model (C-Model), a Machine Learning Radiomics Model (ML-Model) utilizing 1,479 CT features, and a Deep Learning Model (DL-Model) based on ResNet-50. Model interpretability was addressed via Grad-CAM. Performance was evaluated using AUC and Kaplan-Meier analysis. In the test dataset, the DL-Model achieved a superior AUC of 0.851 (95% CI: 0.747-0.954), significantly outperforming the C-Model (AUC = 0.586, P < 0.05) and exceeding the ML-Model (AUC = 0.709). Survival analysis showed the DL-Model was the only framework capable of robust prognostic stratification; predicted responders had significantly prolonged PFS (P = 0.011). Grad-CAM analysis revealed a spatial dichotomy: responders exhibited focal, centralized tumor activation, whereas non-responders showed multifocal, peripheral activation patterns. The DL-Model provides a reliable, interpretable tool for predicting tumor response and PFS in uHCC patients receiving TACE and TKI-based therapy. The Grad-CAM visualization offers spatial insights into tumor heterogeneity, facilitating personalized treatment adjustments.

The deployment strategy for wireless sensor networks (WSNs) affects the quality of service (QoS). Adopting a reasonable deployment strategy can improve the QoS of WSNs. In this paper, the problem regarding sensor node deployment for WSNs on three-dimensional (3D) terrain is modeled as a multi-objective optimization problem. The coverage rate of the WSNs, their unbalanced energy consumption, and the number of sensor nodes are used as fitness functions for the optimization problem. We propose a non-dominated sorting genetic algorithm based on a Voronoi diagram (VNSGA) for solving the wireless sensor network deployment issue and improving the QoS of WSNs on 3D terrain. The proposed algorithm applies the Voronoi diagram to obtain the node-sensing radius and communication radius, which are suitable for 3D terrain with respect to calculating the fitness function of the optimization problem. The Pareto optimal solution is obtained by retaining the solution close to the reference point. The experiments compare the proposed algorithm with the Multi-Objective Particle Swarm Algorithm (MOPSO) and the Non-Dominated Sorting Genetic Algorithm III (NSGA-III) on two terrains with different ranges. The experimental results show that the proposed algorithm outperforms the comparison algorithm on both terrains with different range sizes. The proposed algorithm can improve the coverage to 97.95% and reduce the imbalance in energy consumption to 9.13% on large range terrain.

To fully consider the complementary role of different energy sources and reduce the curtailment of renewable energy (RE) in high RE penetration systems, a hierarchical optimization algorithm is proposed to simultaneously optimize the capacity of RE generation and energy storage systems (ESS). Time sequence simulation (TSS) technology is adopted to fully consider the regional RE resource characteristics and make the model more reliable. An optimization model for evaluating ESS capacity is established at a lower level. To overcome the high dimensional complexity of time sequence data, this paper re-formulates this sub-model as a consensus problem, which can be solved by a distributed approach to minimize the system's total investment costs. At the upper level, the model for assessing the proportion of wind and solar capacity is developed by maximizing the RE generation. The golden section Fibonacci tree optimization (GSFTO) algorithm is utilized to improve the efficiency and solution accuracy. The results show that the algorithm and model are feasible and applicable for the identified purposes, which can provide a useful guidance for the development of power generation and the energy storage capacity in high RE penetration systems.

The folded mitochondria inner membrane-cristae is the structural foundation for oxidative phosphorylation (OXPHOS) and energy production. By mechanically simulating mitochondria morphogenesis, we speculate that efficient sculpting of the cristae is organelle non-autonomous. It has long been inferred that folding requires buckling in living systems. However, the tethering force for cristae formation and regulation has not been identified. Combining electron tomography, proteomics strategies, super resolution live cell imaging and mathematical modeling, we reveal that the mitochondria localized actin motor-myosin 19 (Myo19) is critical for maintaining cristae structure, by associating with the SAM-MICOS super complex. We discover that depletion of Myo19 or disruption of its motor activity leads to altered mitochondria membrane potential and decreased OXPHOS. We propose that Myo19 may act as a mechanical tether for effective ridging of the mitochondria cristae, thus sustaining the energy homeostasis essential for various cellular functions. The structure of the mitochondrial inner membrane, or cristae, is important for functional oxidative phosphorylation and energy production. Here, the authors show that loss of myosin 19 impairs cristae structure as well as energy production, connecting motor activity to membrane potential.