Correction of both NBD1 energetics and domain interface is required to restore ΔF508 CFTR folding and function.

The folding and misfolding mechanism of multidomain proteins remains poorly understood. Although thermodynamic instability of the first nucleotide-binding domain (NBD1) of ΔF508 CFTR (cystic fibrosis transmembrane conductance regulator) partly accounts for the mutant channel degradation in the endoplasmic reticulum and is considered as a drug target in cystic fibrosis, the link between NBD1 and CFTR misfolding remains unclear. Here, we show that ΔF508 destabilizes NBD1 both thermodynamically and kinetically, but correction of either defect alone is insufficient to restore ΔF508 CFTR biogenesis. Instead, both ΔF508-NBD1 energetic and the NBD1-MSD2 (membrane-spanning domain 2) interface stabilization are required for wild-type-like folding, processing, and transport function, suggesting a synergistic role of NBD1 energetics and topology in CFTR-coupled domain assembly. Identification of distinct structural deficiencies may explain the limited success of ΔF508 CFTR corrector molecules and suggests structure-based combination corrector therapies. These results may serve as a framework for understanding the mechanism of interface mutation in multidomain membrane proteins.

Light-induced electronic polarization in antiferromagnetic Cr2O3.

In a solid, the electronic subsystem can exhibit incipient order with lower point group symmetry than the crystal lattice. Ultrafast external fields that couple exclusively to electronic order parameters have rarely been investigated, however, despite their potential importance in inducing exotic effects. Here we show that when inversion symmetry is broken by the antiferromagnetic order in Cr2O3, transmitting a linearly polarized light pulse through the crystal gives rise to an in-plane rotational symmetry-breaking (from C3 to C1) via optical rectification. Using interferometric time-resolved second harmonic generation, we show that the ultrafast timescale of the symmetry reduction is indicative of a purely electronic response; the underlying spin and crystal structures remain unaffected. The symmetry-broken state exhibits a dipole moment, and its polar axis can be controlled with the incident light. Our results establish a coherent nonlinear optical protocol by which to break electronic symmetries and produce unconventional electronic effects in solids.

Synergistic π-Conjugation Organic Cathode for Ultra-Stable Aqueous Aluminum Batteries.

Rechargeable aqueous aluminum batteries (AABs) are promising energy storage technologies owing to their high safety and ultra-high energy-to-price ratio. However, either the strong electrostatic forces between high-charge-density Al3+ and host lattice, or sluggish large carrier-ion diffusion toward the conventional inorganic cathodes generates inferior cycling stability and low rate-capacity. To overcome these inherent confinements, a series of promising redox-active organic materials (ROMs) are investigated and a π-conjugated structure ROMs with synergistic C═O and C═N groups is optimized as the new cathode in AABs. Benefiting from the joint utilization of multi-redox centers and rich π-π intermolecular interactions, the optimized ROMs with unique ion coordination storage mechanism facilely accommodate complex active ions with mitigated coulombic repulsion and robust lattice structure, which is further validated via theoretical simulations. Thus, the cathode achieves enhanced rate performance (153.9 mAh g-1 at 2.0 A g-1 ) and one of the best long-term stabilities (125.7 mAh g-1 after 4,000 cycles at 1.0 A g-1 ) in AABs. Via molecular exploitation, this work paves the new direction toward high-performance cathode materials in aqueous multivalent-ion battery systems.

PS-Net: human perception-guided segmentation network for EM cell membrane.

MOTIVATION: Cell membrane segmentation in electron microscopy (EM) images is a crucial step in EM image processing. However, while popular approaches have achieved performance comparable to that of humans on low-resolution EM datasets, they have shown limited success when applied to high-resolution EM datasets. The human visual system, on the other hand, displays consistently excellent performance on both low and high resolutions. To better understand this limitation, we conducted eye movement and perceptual consistency experiments. Our data showed that human observers are more sensitive to the structure of the membrane while tolerating misalignment, contrary to commonly used evaluation criteria. Additionally, our results indicated that the human visual system processes images in both global-local and coarse-to-fine manners. RESULTS: Based on these observations, we propose a computational framework for membrane segmentation that incorporates these characteristics of human perception. This framework includes a novel evaluation metric, the perceptual Hausdorff distance (PHD), and an end-to-end network called the PHD-guided segmentation network (PS-Net) that is trained using adaptively tuned PHD loss functions and a multiscale architecture. Our subjective experiments showed that the PHD metric is more consistent with human perception than other criteria, and our proposed PS-Net outperformed state-of-the-art methods on both low- and high-resolution EM image datasets as well as other natural image datasets. AVAILABILITY AND IMPLEMENTATION: The code and dataset can be found at https://github.com/EmmaSRH/PS-Net.

Analysis of CCND3 mutations in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL), accounts for 30-40% of newly diagnosed lymphomas, has an overall cure rate of approximately 60%. Despite previous reports suggesting a negative prognostic association between CCND3 mutations and Burkitt lymphoma, their prognostic implications in DLBCL remain controversial. To investigate this, we evaluated CCND3 mutation status in 2059 DLBCL patient samples from four database (integrated cohort) and additional 167 DLBCL patient samples in our center (JSPH cohort). The mutation was identified in 5.5% (113/2059) of the cases in the integrated cohort, with 86% (97/113) found in exon 5. Furthermore, P284, R271, I290 and Q276 are described as CCND3 mutation hotspots. CCND3 mutation was associated with decreased overall survival (OS) in the integrated cohort (P = 0.0407). Further subgroup analysis revealed that patients diagnosed as EZB subtype DLBCL by LymphGen algorithm with CCND3 mutations had poorer OS than patients diagnosed as EZB subtype without CCND3 mutations (P = 0.0140). Using the next-generation sequencing (NGS) in the JSPH cohort, it was found that both cell cycle and DNA replication pathways were highly upregulated in patients with CCND3 mutations. Our results suggest that CCND3 mutations can serve as a novel prognostic factor in DLBCL pathogenesis. Consequently, the development of personalized therapeutic strategies for DLBCL patients with CCND3 mutations might enhance their prognosis.

Perovskite light-emitting diodes based on spontaneously formed submicrometre-scale structures.

Light-emitting diodes (LEDs), which convert electricity to light, are widely used in modern society-for example, in lighting, flat-panel displays, medical devices and many other situations. Generally, the efficiency of LEDs is limited by nonradiative recombination (whereby charge carriers recombine without releasing photons) and light trapping1-3. In planar LEDs, such as organic LEDs, around 70 to 80 per cent of the light generated from the emitters is trapped in the device4,5, leaving considerable opportunity for improvements in efficiency. Many methods, including the use of diffraction gratings, low-index grids and buckling patterns, have been used to extract the light trapped in LEDs6-9. However, these methods usually involve complicated fabrication processes and can distort the light-output spectrum and directionality6,7. Here we demonstrate efficient and high-brightness electroluminescence from solution-processed perovskites that spontaneously form submicrometre-scale structures, which can efficiently extract light from the device and retain wavelength- and viewing-angle-independent electroluminescence. These perovskites are formed simply by introducing amino-acid additives into the perovskite precursor solutions. Moreover, the additives can effectively passivate perovskite surface defects and reduce nonradiative recombination. Perovskite LEDs with a peak external quantum efficiency of 20.7 per cent (at a current density of 18 milliamperes per square centimetre) and an energy-conversion efficiency of 12 per cent (at a high current density of 100 milliamperes per square centimetre) can be achieved-values that approach those of the best-performing organic LEDs.

Topological spin/structure couplings in layered chiral magnet Cr1/3TaS2: The discovery of spiral magnetic superstructure.

Chiral magnets have recently emerged as hosts for topological spin textures and related transport phenomena, which can find use in next-generation spintronic devices. The coupling between structural chirality and noncollinear magnetism is crucial for the stabilization of complex spin structures such as magnetic skyrmions. Most studies have been focused on the physical properties in homochiral states favored by crystal growth and the absence of long-ranged interactions between domains of opposite chirality. Therefore, effects of the high density of chiral domains and domain boundaries on magnetic states have been rarely explored so far. Herein, we report layered heterochiral Cr1/3TaS2, exhibiting numerous chiral domains forming topological defects and a nanometer-scale helimagnetic order interlocked with the structural chirality. Tuning the chiral domain density, we discovered a macroscopic topological magnetic texture inside each chiral domain that has an appearance of a spiral magnetic superstructure composed of quasiperiodic Néel domain walls. The spirality of this object can have either sign and is decoupled from the structural chirality. In weak, in-plane magnetic fields, it transforms into a nonspiral array of concentric ring domains. Numerical simulations suggest that this magnetic superstructure is stabilized by strains in the heterochiral state favoring noncollinear spins. Our results unveil topological structure/spin couplings in a wide range of different length scales and highly tunable spin textures in heterochiral magnets.

Ferrorotational Selectivity in Ilmenites.

Unlike what happens in conventional ferroics, the ferrorotational (FR) domain manipulation and visualization in FR materials are nontrivial as they are invariant under both space-inversion and time-reversal operations. FR domains have recently been observed by using the linear electrogyration (EG) effect and X-ray diffraction (XRD) diffraction mapping. However, ferrorotational selectivity, such as the selective processing of the FR domains and direct visualization of the FR domains, e.g., under an optical microscope, would be the next step to study the FR domains and their possible applications in technology. Unexpectedly, we discovered that the microscopic FR structural distortions in ilmenite crystals can be directly coupled with macroscopic mechanical rotations in such a way that FR domains can be visualized under an optical microscope after innovative rotational polishing, a combined ion milling with a specific rotational polishing, or a twisting-induced fracturing process. Thus, the FR domains could be a unique medium to register the memory of a rotational mechanical process due to a novel selective coupling between its microscopic structural rotations and an external macroscopic rotation. Analogous to the important enantioselectivity in modern chemistry and the pharmaceutical industry, this newly discovered ferrorotational selectivity opens up opportunities for FR manipulation and new FR functionality-based applications.

MYC-induced cytidine metabolism regulates survival and drug resistance via cGas-STING pathway in mantle cell lymphoma.

Lymphocyte proliferation and tumourigenesis are dependent on nucleotide synthesis to support DNA, RNA and phospholipid synthesis. Here, we identified that reprogramming of nucleotide metabolism as an important factor divides mantle cell lymphoma (MCL) into two groups with different transcriptional signalling pathways and varying prognoses. We establish a nucleotide metabolism-related prognostic model that includes six genes with different regression coefficients, which significantly predicts prognosis for MCL patients (p < 0.0001). Of these six genes, de novo CTP synthesis pathway enzyme CTPS1 whose inhibitor (STP938) is already in clinical trials for relapsed/refractory lymphomas (NCT05463263) has the highest regression coefficient. An increase in CTPS1 expression predicts adverse overall survival and progression-free survival with independent prognostic significance in 105 primary MCL samples and GEO database (GSE93291). CRISPR CTPS1 knockout causes DNA damage and proliferation defects in MCL. Additionally, MYC positively regulates CTPS1 expression, and TP53-aberrant and ibrutinib-resistant MCL cells also rely on cytidine metabolism. Furthermore, besides the obvious decreased CTP pool caused by CTPS1 deficiency, CTPS1 inhibition may also induce immune-related responses via activating dsDNA-cGAS-STING pathway, which plays a crucial role in impeding tumour growth in MCL patients.

Combined Morphological and Spectroscopic Diagnostic of HER2 Expression in Breast Cancer Tissues Based on Label-Free Surface-Enhanced Raman Scattering.

Breast cancer is the most commonly diagnosed cancer type worldwide. Overexpression of human epidermal growth factor receptor 2 (HER2) is an important subtype of breast cancer and results in an increased risk of recurrence and metastasis in patients. At present, immunohistochemistry (IHC) is used to detect the expression of HER2 in breast cancer tissues as the golden standard. However, IHC has some shortcomings, such as large subjective impact, long time consumption, expensive reagents, etc. In this paper, a combined morphological and spectroscopic diagnostic method based on label-free surface-enhanced Raman scattering (SERS) for HER2 expression in breast cancer is proposed. It can not only quantitively detect HER2 expression in breast cancer tissues by spectroscopic measurements but also give morphological images reflecting the distribution of HER2 in tissues. The results show that the consistency between this method and IHC is 95% and achieves the annotation of tumor regions on tissue sections. This method is time-consuming, quantifiable, intuitive, scalable, and easy to understand. Combined with deep learning approaches, it is expected to promote the development of clinical detection and diagnosis technology for breast cancer and other cancers.

Heuristic Tree-Partition-Based Parallel Method for Biophysically Detailed Neuron Simulation.

Biophysically detailed neuron simulation is a powerful tool to explore the mechanisms behind biological experiments and bridge the gap between various scales in neuroscience research. However, the extremely high computational complexity of detailed neuron simulation restricts the modeling and exploration of detailed network models. The bottleneck is solving the system of linear equations. To accelerate detailed simulation, we propose a heuristic tree-partition-based parallel method (HTP) to parallelize the computation of the Hines algorithm, the kernel for solving linear equations, and leverage the strong parallel capability of the graphic processing unit (GPU) to achieve further speedup. We formulate the problem of how to get a fine parallel process as a tree-partition problem. Next, we present a heuristic partition algorithm to obtain an effective partition to efficiently parallelize the equation-solving process in detailed simulation. With further optimization on GPU, our HTP method achieves 2.2 to 8.5 folds speedup compared to the state-of-the-art GPU method and 36 to 660 folds speedup compared to the typical Hines algorithm.

Low T3 syndrome as a predictor of poor outcomes in patients with follicular lymphoma.

The aim of this study was to investigate the prognostic value of low T3 syndrome in follicular lymphoma (FL). A total of 221 FL patients with detailed serum thyroid hormone levels and other complete clinical data were enrolled. Baseline features associated with low T3 syndrome were analyzed and balanced by propensity score matching. Univariate and multivariate regression analyses were performed to determine independent risk factors for progression-free survival (PFS) and overall survival (OS). A receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated to assess the predictive accuracy of FL international prognostic index FLIPI-1/FLIPI-2 and low T3 syndrome. A total of 22 patients (10.0%) had low T3 syndrome at diagnosis, which was associated with poor PFS and OS in the rituximab era. It is an independent prognostic factor for PFS and OS. Low T3 syndrome and FLIPI-1/FLIPI-2 significantly increased the AUC of PFS and OS compared to FLIPI-1/FLIPI-2 alone. Low T3 is a risk factor for POD24. In conclusion, low T3 syndrome may be a good candidate for predicting the prognosis of CLL in future clinical practice. Our study demonstrates that low T3 syndrome is associated with poorer survival outcomes in FL patients.

Dynamic changes in circulating EBV-DNA load during treatment have prognostic values in EBV+ DLBCL-NOS: a Chinese cohort study.

EBV-positive diffuse large B-cell lymphoma, not otherwise specified (EBV+ DLBCL-NOS), is an EBV-positive clonal B-cell lymphoid proliferation and circulating EBV-DNA is a great indicator for prognosis among EBV associated disease. In this retrospective study, we report 66 EBV+ DLBCL cases among 2137 DLBCL-NOS cases diagnosed from 2013 to 2021 (prevalence of 6.0%). After a median follow-up of 27 months, progression-free survival (PFS) and overall survival (OS) at 2 years were 39.5% ± 6.2% and 53.6% ± 6.4%, respectively. Multivariate analysis showed that only the biomarker of the positivity of post treatment EBV-DNA had a borderline correlation with shorter PFS and OS (PFS: P = 0.053; OS: P = 0.065). Patients were divided into three subgroups according to dynamic changes of EBV-DNA status: EBV-DNA persistently negative group, EBV-DNA persistently positive group, and EBV-DNA transformed from positive to negative group; among the three groups, patients of the persistently positive group had worst PFS and OS (P = 0.0527 and P = 0.0139, respectively). Decline in EBV copies correlated significantly with treatment response as well. In conclusion, circulating EBV-DNA level played a vital role in prognostic and monitoring marker for EBV+ DLBCL-NOS.

Decorin inhibits the formation of hard nodules after microwave ablation by inhibiting the TGF-ß1/SMAD and MAPK signaling pathways: in a Bama miniature pig model of mammary gland hyperplasia.

BACKGROUND: Benign breast lesions are often associated with hard nodule formation after microwave ablation (MWA), which persists for a long time and causes problems in patients. The aim of this study was to evaluate the efficacy of decorin in the treatment of hard nodule formation and its potential mechanism of action. METHODS: Using a Bama miniature pig model of mammary gland hyperplasia, immunohistochemistry, Masson's trichrome and western blotting were firstly applied to compare the extent of fibrosis and activation of key members of the TGF-ß1/SMAD and MAPK signaling pathways of hard nodule in the control and MWA groups, and then the extent of fibrosis and expression of signaling pathways in hard nodule were examined after application of decorin. RESULTS: The results showed that the MWA group had increased levels of TGF-ß1, p-SMAD2/3, p-ERK1/2, and collagen I proteins and increased fibrosis at 2 weeks, 4 weeks, and 3 months after MWA. After decorin treatment, the expression levels of each protein were significantly downregulated, and the degree of fibrosis was reduced at 2 weeks, 4 weeks, and 3 months after MWA compared with the MWA group. CONCLUSION: In conclusion, these results suggest that activation of TGF-ß1 may play an important role in hard nodule formation and that decorin may reduce hard nodule formation after MWA in a model of mammary gland hyperplasia by inhibiting the TGF-ß1/SMAD and MAPK signaling pathways.

Quantitative assessment of thenar to evaluate hand function after stroke by Bayes discriminant.

BACKGROUND: The incidence rate of stroke or cerebrovascular accidents ranks first in China. More than 85% of stroke patients have residual upper limb motor dysfunction, especially hand dysfunction. Normalizing the rehabilitation evaluation process and standard quantitative evaluation method is a complex and key point in rehabilitation therapy. The study aimed to establish a function model based on the Bayes discriminant by measuring the thenar stiffness with shear wave elastography (SWE) to quantitatively evaluate the hand motor function of hemiplegic patients after stroke. METHODS: This study collected 60 patients diagnosed with hemiplegia after stroke from October 2021 to October 2022. Therapists used the Brunnstrom assessment (BA)scale to divide the patients into the stage. All the patients underwent the measurement of SWE examination of abductor pollicis brevis (APB), opponens pollicis (OP), flexor pollicis long tendon (FPLT), and flexor pollicis brevis (FPB) by two sonographers. The SWE change rate of four parts of the thenar area was calculated prospectively with the non-hemiplegic side as the reference, the function equation was established by the Bayes discriminant method, and the evaluation model was fitted according to the acquired training set data. Lastly, the model was verified by self-validation, cross-validation, and external data validation methods. The classification performance was evaluated regarding the area under the ROC curve (AUC), sensitivity, and specificity. RESULTS: The median SWE values of the hemiplegic side of patients were lower than those of the non-hemiplegic side. According to the BA stage and SWER of APB, OP, FPLT, and FPB, our study established the Bayes discriminative model and validated it via self-validation and cross-validation methods. Then, the discriminant equation was used to validate 18 patients prospectively, the diagnostic coincidence rate was about 78.8%, and the misjudgment rate was approximately 21.2%. The AUC of the discriminant model for diagnosing BA stage I-VI was 0.928(95% CI: 0.839-1.0),0.858(95% CI: 0.748-0.969),1.0(95% CI: 1.0-1.0), 0.777(95% CI: 0.599-0.954),0.785(95% CI: 0.593-0.977) and 0.985(95% CI: 0.959-1.0), respectively. CONCLUSION: This Bayes discriminant model built by measuring thenar stiffness was of diagnostic value and can provide an objective basis for evaluating clinical rehabilitation.

Micro-Vision Based High-Precision Space Assembly Approach for Trans-Scale Micro-Device: The CFTA Example.

For assembly of trans-scale micro-device capsule fill tube assemblies (CFTA) for inertial confinement fusion (ICF) targets, a high-precision space assembly approach based on micro-vision is proposed in this paper. The approach consists of three modules: (i) a posture alignment module based on a multi-vision monitoring model that is designed to align two trans-scale micro-parts in 5DOF while one micro-part is in ten microns and the other one is in hundreds of microns; (ii) an insertion depth control module based on a proposed local deformation detection method to control micro-part insertion depth; (iii) a glue mass control module based on simulation research that is designed to control glue mass quantitatively and to bond micro-parts together. A series of experiments were conducted and experimental results reveal that attitude alignment control error is less than ±0.3°, position alignment control error is less than ±5 µm, and insertion depth control error is less than ±5 µm. Deviation of glue spot diameter is controlled at less than 15 µm. A CFTA was assembled based on the proposed approach, the position error in 3D space measured by computerized tomography (CT) is less than 5 µm, and glue spot diameter at the joint is 56 µm. Through volume calculation by the cone calculation formula, the glue mass is about 23 PL when the cone height is half the diameter.

Skill-Learning Method of Dual Peg-in-Hole Compliance Assembly for Micro-Device.

For the dual peg-in-hole compliance assembly task of upper and lower double-hole structural micro-devices, a skill-learning method is proposed. This method combines offline training in a simulation space and online training in a realistic space. In this paper, a dual peg-in-hole model is built according to the results of a force analysis, and contact-point searching methods are provided for calculating the contact force. Then, a skill-learning framework is built based on deep reinforcement learning. Both expert action and incremental action are used in training, and a reward system considers both efficiency and safety; additionally, a dynamic exploration method is provided to improve the training efficiency. In addition, based on experimental data, an online training method is used to optimize the skill-learning model continuously so that the error caused by the deviation in the offline training data from reality can be reduced. The final experiments demonstrate that the method can effectively reduce the contact force while assembling, improve the efficiency and reduce the impact of the change in position and orientation.

Managing nitrogen environmental impacts to improve green technical efficiency in Philippines rice cultivation.

The efficient use of nitrogen fertilisers is a global priority to optimise the economic and environmental outcomes of farming. This paper is the first to consider pollution in the form of nitrous oxide emissions and excess nitrogen to analyse technical efficiency (TE) in farming. This is done by extending the two-stage double bootstrap Data Envelopment Analysis to explicitly model nitrogen pollutants as undesirable outputs. We compared green TE (when undesirable pollutants are considered) and conventional TE (without pollutants) using a case study of 33 rice-producing provinces in the Philippines. Provinces in Mindanao, Luzon, and Visayas islands experienced improvements in green TE but stagnant conventional TE from 2006 to 2017. Although transplanting rice seedlings (rather than direct sowing of seeds) improved both green and conventional TE, seed quality was also identified as an important factor for green TE but not for conventional TE. Our analysis has implications for sustainable rice production and such analysis can be extended to other crops. To advance the effective green transformation of rice production, future research should analyse farm-level data to understand farmers' decisions regarding seed quality, crop establishment method and nitrogen fertiliser application to devise comprehensive farm integrated management plans.

Impaired time-distance reconfiguration patterns in Alzheimer's disease: a dynamic functional connectivity study with 809 individuals from 7 sites.

BACKGROUND: The dynamic functional connectivity (dFC) has been used successfully to investigate the dysfunction of Alzheimer's disease (AD) patients. The reconfiguration intensity of nodal dFC, which means the degree of alteration between FCs at different time scales, could provide additional information for understanding the reconfiguration of brain connectivity. RESULTS: In this paper, we introduced a feature named time distance nodal connectivity diversity (tdNCD), and then evaluated the network reconfiguration intensity in every specific brain region in AD using a large multicenter dataset (N = 809 from 7 independent sites). Our results showed that the dysfunction involved in three subnetworks in AD, including the default mode network (DMN), the subcortical network (SCN), and the cerebellum network (CBN). The nodal tdNCD inside the DMN increased in AD compared to normal controls, and the nodal dynamic FC of the SCN and the CBN decreased in AD. Additionally, the classification analysis showed that the classification performance was better when combined tdNCD and FC to classify AD from normal control (ACC = 81%, SEN = 83.4%, SPE = 80.6%, and F1-score = 79.4%) than that only using FC (ACC = 78.2%, SEN = 76.2%, SPE = 76.5%, and F1-score = 77.5%) with a leave-one-site-out cross-validation. Besides, the performance of the three classes classification was improved from 50% (only using FC) to 53.3% (combined FC and tdNCD) (macro F1-score accuracy from 46.8 to 48.9%). More importantly, the classification model showed significant clinically predictive correlations (two classes classification: R = -0.38, P < 0.001; three classes classification: R = -0.404, P < 0.001). More importantly, several commonly used machine learning models confirmed that the tdNCD would provide additional information for classifying AD from normal controls. CONCLUSIONS: The present study demonstrated dynamic reconfiguration of nodal FC abnormities in AD. The tdNCD highlights the potential for further understanding core mechanisms of brain dysfunction in AD. Evaluating the tdNCD FC provides a promising way to understand AD processes better and investigate novel diagnostic brain imaging biomarkers for AD.

Multi-focus image fusion algorithm based on random features embedding and ensemble learning.

Multi-focus image fusion algorithm integrates complementary information from multiple source images to obtain an all-in-focus image. Most published methods will create incorrect points in their decision map which have to be refined and polished with post-processing procedure. Aim to address these problems, we present, for the first time, a novel algorithm based on random features embedding (RFE) and ensemble learning which reduced the calculation workload and improved the accuracy without post-processing. We utilize RFE to approximate a kernel function so that Support Vector Machine (SVM) can be applied to large scale data set. With ensemble learning scheme we then eliminate the abnormal points in the decision map. We reduce the risk of entrap into over-fitting predicament and boost the generalization ability by combining RFE and ensemble learning. The theoretical analysis is in consistence with the experimental results. With low computation cost, the proposed algorithm achieve high visual quality as the state-of-the-art(SOTA).