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Abstract The Atlantic Niño has attracted considerable attention due to its profound climatic impacts. It has been reported that the strength of Atlantic Niño has been weakening since 2000, but it is not clear whether it would lead to a change in Atlantic Niño prediction skill. Here we find a dramatic decline in Atlantic Niño prediction skill since 2000 by evaluating the predictions of the North American Multi-Model Ensemble. The prediction skill decline is mainly associated with a climatic regime shift, which leads to a weakened El Niño-Southern Oscillation (ENSO) teleconnection to the sea surface temperature anomaly dipole mode over the South Atlantic. A systematic model deficiency may amplify the prediction skill decline. This study offers insights for understanding the Atlantic Niño predictability and for improving the simulation and prediction of Atlantic Niño events.

Abstract High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method’s accuracy showed significant improvements, with determination coefficients (R 2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies.

PurposeThis study aimed to investigate and compare the anterior scleral thickness (AST) among high myopia (HM), primary open-angle glaucoma (POAG), and POAG with HM (HMPOAG) groups.MethodsThirty-two HM eyes, 30 POAG eyes, and 31 HMPOAG eyes were included. The Schlemm’s canal (SC) area, trabecular meshwork (TM) thickness, scleral spur (SS) length, and AST were measured using swept-source optical coherence tomography. AST was measured at 0 mm (AST0), 1 mm (AST1), 2 mm (AST2), and 3 mm (AST3) from SS.ResultsThe HMPOAG group had significantly thinner AST, SS length, and TM thickness than the HM and POAG groups (all p

Urban land use patterns can be more accurately mapped by fusing multimodal data. However, many studies only consider socioeconomic and physical attributes within land parcels, neglecting spatial interaction and uncertainty caused by multimodal data. To address these issues, we constructed a multimodal data fusion model (MDFNet) to extract natural physical, socioeconomic, and spatial connectivity ancillary information from multimodal data. We also established an uncertainty analysis framework based on a generalized additive model and learnable weight module to explain data-driven uncertainty. Shenzhen was chosen as the demonstration area. The results demonstrated the effectiveness of the proposed method, with a test accuracy of 0.882 and a Kappa of 0.858. Uncertainty analysis indicated the contributions in overall task of 0.361, 0.308, and 0.232 for remote sensing, social sensing, and taxi trajectory data, respectively. The study also illuminates the collaborative mechanism of multimodal data in various land use categories, offering an accurate and interpretable method for mapping urban distribution patterns.

Accurately determining if the sample parameters from a natural gas pipeline’s sampling system reflect the fluid characteristics of the main pipe has been a significant industry concern for many years. In this paper, samples of natural gas in a horizontal pipeline are investigated. CFD is used in this work and the turbulence is considered in the simulation. Firstly, the critical diameter for particles affected by gravity within such pipeline is determined. And then, the effects of the operation pressure and velocity of sampling branches on sample parameters, and the influence of particle density on these sample parameters, are analyzed. Finally, four different structures of sample branches for natural gas in a horizontal pipeline are compared. It is found that 100 μm is the critical diameter at which particles are affected by gravity; the operating pressure of the sampling branch has a significant impact on the particle mass concentration. The particle density has little impact on the sampling system. Overall, the design of the sampling branches does not cause significant sampling errors. This study provides guidance for optimal sampling in existing natural gas pipelines and enables effective monitoring of particle impurity content and properties in natural gas.

To investigate the optimal delivery system of quercetin, in this paper, cellulose nanocrystals (CNCs) extracted from rice bran were used to stabilize the Pickering emulsion and Pickering emulsion gels (PEGs) with quercetin. To compare the emulsion properties, stability, antioxidation activity, encapsulation rate, and bioaccessibility of the quercetin, four emulsions of CNC Pickering emulsion (C), CNC Pickering emulsion with quercetin (CQ), CNC Pickering gel emulsion (CG), and CNC Pickering gel emulsions with quercetin (CQG) were prepared. All four emulsions exhibited elastic gel network structure and good stability. The quercetin significantly reduced the particle size, increased the stability, and improved the antioxidant capacity of CQ and CQG. Compared to C and CG, the ABTS+ radical scavenging capacities of CQ and CQG were respectively enhanced by 46.92% and 3.59%. In addition, CQG had a higher encapsulation rate at 94.57% and higher bioaccessibility (16.17) compared to CQ. This study not only indicated that CNC from rice bran could be exploited as an excellent stabilization particle for Pickering emulsions, but also provided a highly stable and bioaccessible delivery system for water-insoluble functional active factors.

For a long time, food spoilage posed a severe impairment on food safety and public health. Although chemical preservatives are commonly used to inhibit spoilage/ pathogenic microbial growth, the disadvantages of a single target, potential toxicity and high dose of use limit the better use of preservatives. In this research, the combination of natural preservatives: Natamycin (Nat), ε-polylysine (ε-PL), and Chitosan (CS) could achieve an excellent antimicrobial effect including bacteria and fungi, and reduce the usage of a single preservative. Compound preservatives could destroy microbial morphology and damage the integrity of the cell wall/membrane by leakage of protein and alkaline phosphatase (AKP). Besides, high-throughput sequencing revealed that compound preservatives could decrease microbial diversity and richness, especially, Pseudomonas, Acinetobacter, Fusarium, and Aspergillus. Therefore, the combination of 1/8 × MIC CS, 1/4 × MIC ε-PL, and 1/2 × MIC Nat can achieve an excellent antibacterial effect, providing new ideas for food preservation.

Background: Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable. Methods: We further investigated the diagnostic potential of combining two features (epigenetic markers and fragmentomic information) of cell-free DNA for detecting various types of cancers. To do this, we extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and studied them in 396 low-pass 5hmC sequencing data, which included four common cancer types and control samples. Results: In our analysis of 5hmC sequencing data from cancer samples, we observed aberrant ultra-long fragments (220–500 bp) that differed from normal samples in terms of both size and coverage profile. These fragments played a significant role in predicting cancer. Leveraging the ability to detect cfDNA hydroxymethylation and fragmentomic markers simultaneously in low-pass 5hmC sequencing data, we developed an integrated model that incorporated 63 features representing both fragmentomic features and hydroxymethylation signatures. This model achieved high sensitivity and specificity for pan-cancer detection (88.52% and 82.35%, respectively). Conclusion: We showed that fragmentomic information in 5hmC sequencing data is an ideal marker for cancer detection and that it shows high performance in low-pass sequencing data.

In this study, we investigate the changes in the multiyear predictability of the Pacific decadal oscillation (PDO) since 1900. A newly developed method, the model-analog method, is used to hindcast the PDO from 1900 to 2015. Model-analog hindcast provides comparable PDO prediction skills with the traditional assimilation-initialized forecast but with much lower computational costs. Our results show that PDO prediction skills have significantly changed over time. Specifically, the PDO could skillfully be predicted up to 5 years in advance in 1910–1960, but it can only be predicted 2–3 years in advance after 1960. We attribute these changes to the strength of the re-emergence process, where deep oceanic mixed layer temperature anomalies from one winter reappear in the following winters. In the high-prediction-skill period, the stronger re-emergence process provides more predictable information, leading to enhanced multiyear prediction skills. Our study offers new insights into the multiyear predictability of the PDO over a long-time frame and sheds light on the reasons behind the low prediction skill of the PDO.

Abstract In massive multiple‐input multiple‐output (MIMO) systems, most of the existing detection work mainly assumes that the channel is the additive white Gaussian noise (AWGN). However, this assumption is difficult to apply to practical communication scenarios. To this end, this paper proposes a message passing detection (MPD) algorithm with a convolutional neural network (CNN) (denoted as iterative MPD‐CNN structure) under correlated noise channels, which is helpful to solve the issue of detection performance degradation in non‐ideal AWGN channels. Firstly, the MPD algorithm based on the channel hardening phenomenon is used to initially estimate the transmitted signal, and then the CNN is concatenated to remove the estimation error for obtaining more accurate channel noise, which provides a beneficial noise distribution for the MPD algorithm. Finally, the theoretical analysis and simulation results show that the proposed iterative MPD‐CNN structure can improve the detection performance in conditions of correlated noise channels and fewer antennas. Compared with the traditional MPD algorithm, its detection performance is more superior.

Abstract Background To investigate the microbiologic spectrum of dacryocystitis in adult and pediatric groups, specifically the microbiologic differences between chronic dacryocystitis with nasolacrimal duct obstruction (NLDO) and acute dacryocystitis in pediatric group. Methods This retrospective study was reviewed for demographic and microbiologic profile of dacryocystitis. The culture results were reported. Results Sixty-four adults and one hundred and five pediatrics with dacryocystitis were included in this study. Of all adults, only chronic dacryocystitis with NLDO was observed. Of all pediatric patients, 89 had chronic dacryocystitis with NLDO and 16 had acute dacryocystitis. Gram positive and negative isolates were numerically equal in adult group (both 36(48.65%)), while gram positive isolates were the major organism in pediatric group (71(58.68%)). Streptococcus pneumonia was the most common isolate in both adult (11(14.86%)) and pediatric (30(24.79%)) dacryocystitis. For both pediatric subgroups, gram positive isolates were the major organism (59(57.84%) for chronic dacryocystitis with NLDO and 12 (63.16%) for acute dacryocystitis). However, the leading isolates in those two subgroups were distinct, with Streptococcus pneumonia (29(28.43%)) being most common in chronic dacryocystitis with NLDO and Staphylococcus aureus (8(42.11%)) being most common in acute dacryocystitis. Conclusions In adult group, gram negative isolates were more common in dacryocystitis than before. In pediatric group, gram positive isolates were still the major infection pathogen. Moreover, the more virulent organisms were more common in acute dacryocystitis than chronic dacryocystitis with NLDO.

PurposeTo investigate choroidal vascularity (CV) and choriocapillaris blood perfusion before and after accommodation in myopia, emmetropia, and hyperopia groups among children.MethodsThis study included 39 myopic eyes from 22 subjects, 17 emmetropic eyes from 11 subjects, and 18 hyperopic eyes from 10 subjects. All subjects were children. Choroidal thickness (CT) and CV, including total choroidal area (TCA), luminal area (LA), and stromal area (SA) were measured using swept-source optical coherence tomography (SS-OCT). Choriocapillaris luminal area (CLA) was measured using SS-OCT-angiography before and after accommodation (near reading with an additional −3 diopter lens).ResultsFor baseline results, except horizontal CV (showing no significant differences between myopia and emmetropia groups), both horizontal and vertical CT and CV were significantly smaller in the myopia group than in the emmetropia or hyperopia groups. In terms of CLA, no significant differences were observed among the myopia, emmetropia, and hyperopia groups. In addition, only myopic eyes showed significant decreases in CT and CV, whereas most CT and CV of emmetropic and hyperopic eyes showed non-significant decreases after accommodation. Furthermore, accommodation induced no significant changes in CLA in the myopia, emmetropia, or hyperopia groups.ConclusionMyopia had thinner baseline choroid and lower baseline choroidal blood perfusion. Furthermore, myopic eyes were more prone to choroidal thinning and blood perfusion decreases after accommodation.

Deep learning has made great progress in image compressive sensing (CS) tasks recently, and several CS models based on it have achieved superior performance. In practice, sensing the entire image requires huge memory and computational effort. Although the block-based CS method can effectively realize image sensing, it will cause block effects that severely decrease the reconstruction performance. To this end, this paper proposes a two-branch convolution residual network for image compressive sensing (denoted as TCR-CS), which mainly consists of a two-branch convolution autoencoder network and a residual network. Specifically, the two-branch convolution autoencoder network senses the entire image through multiple scale convolutional filters to obtain measurements. For better CS reconstruction, the image is preliminarily reconstructed by the deconvolution decoder network, and then the residual network is used to optimize the pre-reconstructed image. Through the end-to-end training, all networks can be jointly optimized. Finally, experimental results demonstrate that the proposed TCR-CS method is superior to existing state-of-the-art CS methods in terms of structural similarity, reconstruction performance and visual quality at different measurement rates.

To describe a rare case of an unusual visual threatening complication of chronic myeloid leukemia (CML). A 21-year-old male visited the hospital complaining of 1-week painless binocular acute visual loss without any other symptoms. The patient was diagnosed with CML. He then received emergent leukapheresis with imatinib treatment, which achieved obvious hematological remission. However, the visual acuity did not recover along with the CML remission and ocular structure relief. CML-related leukostasis could induce severe leukostasis retinopathy. Hematologists and ophthalmologists should pay more attention to this relatively rare and severe complication of CML.

The reason for the decline in frequency of Atlantic major hurricanes since 2005 is still debated. Here the authors combine observations with model simulations to show that this decline is largely due to changes in the Atlantic ocean meridional overturning circulation.

Purpose. To observe the recovery process of postexercise Schlemm’s canal (SC) and intraocular pressure (IOP) in healthy individuals. Methods. Twenty healthy individuals were recruited. SC and IOP were evaluated before exercise, immediately after exercise, and 15, 30, and 60 minutes after exercise. Superior, inferior, nasal, and temporal SC quadrants were evaluated using swept-source optical coherence tomography (SS-OCT). Results. Average SC area (3726.81 ± 1167.06 vs. 4660.57 ± 1284.82 µm2) and perimeter (324.11 ± 58.95 vs. 367.19 ± 73.34 µm) increased, and IOP (14.02 ± 2.33 vs. 11.65 ± 1.90 mmHg) decreased significantly during exercise (all p0.05). There were no significant differences in the observable SC proportion before and after exercise (all p>0.05). Conclusions. The exercise-induced SC expansion and IOP reduction could recover to preexercise values after exercise, and SC recovered to preexercise values ahead of IOP. Moreover, SC might be regulated by the sympathetic nerves and could be an important causative factor of changes in IOP during and after exercise.

We investigated in vivo changes in Schlemm's canal and the trabecular meshwork in eyes with primary open angle glaucoma (POAG). Relationships between Schlemm's canal diameter, trabecular meshwork thickness, and intraocular pressure (IOP) were examined. Forty POAG patients and 40 normal individuals underwent 80-MHz Ultrasound Biomicroscopy examinations. The Schlemm's canal and trabecular meshwork were imaged in superior, inferior, nasal and temporal regions. Normal individuals had an observable Schlemm's canal in 80.3% of sections, a meridional canal diameter of 233.0±34.5 μm, a coronal diameter of 44.5±12.6 μm and a trabecular meshwork thickness of 103.9±11.1 μm, in POAG patients, Schlemm's canal was observable in 53.1% of sections, a meridional canal diameter of 195.6±31.3 μm, a coronal diameter of 35.7±8.0 μm, and a trabecular meshwork thickness of 88.3±13.2 μm, which significantly differed from normal (both p 21 mmHg) IOP, respectively (χ = 1.159, p = 0.282). Coronal canal diameter was significantly lower in the elevated IOP group (32.6±4.9 μm) than in the normal IOP group (35.7±8.0 μm, p < 0.001). This was also true of trabecular meshwork thickness (81.9±10.0 μm vs. 97.1±12.0 μm, p < 0.001). In conclusion, eyes with POAG had fewer sections with an observable Schlemm's canal. Canal diameter and trabecular meshwork thickness were also lower than normal in POAG patients. Schlemm's canal coronal diameter and trabecular meshwork thickness were negatively correlated with IOP.

BACKGROUND:Previous studies demonstrated that primary open angle glaucoma (POAG) is associated with abnormal brain structure; however, little is known about the changes in the local synchronization of spontaneous activity. The main objective of this study was to investigate spontaneous brain activity in patients with POAG using regional homogeneity (ReHo) analysis based on resting state functional magnetic resonance imaging (rs-fMRI). METHODOLOGY/PRINCIPAL FINDINGS:Thirty-nine POAG patients and forty-one age- and gender- matched healthy controls were finally included in the study. ReHo values were used to evaluate spontaneous brain activity and whole brain voxel-wise analysis of ReHo was carried out to detect differences by region in spontaneous brain activity between groups. Compared to controls, POAG patients showed increased ReHo in the right dorsal anterior cingulated cortex, the bilateral medial frontal gyrus and the right cerebellar anterior lobe, and decreased ReHo in the bilateral calcarine, bilateral precuneus gryus, bilateral pre/postcentral gyrus, left inferior parietal lobule and left cerebellum posterior lobe. A multiple linear regression analysis was performed to explore the relationships between clinical measures and ReHo by region showed significant group differences in the POAG group. Negative correlations were found between age and the ReHo values of the superior frontal gyrus (r = -0.323, p = 0.045), left calcarine (r = -0.357, p = 0.026) and inferior parietal lobule (r = -0.362, p = 0.024). A negative correlation was found between the ReHo values of the left precuneus and the cumulative mean defect (r = -0.400, p = 0.012). CONCLUSIONS:POAG was associated with abnormal brain spontaneous activity in some brain regions and such changed regional activity may be associated with clinical parameters. Spontaneous brain activity may play a role in POAG initiation and progression.

Abstract In this study, it is considered that the question of adaptive tracking control of nonlinear systems containing unknown time‐varying parameters. To optimize the control effect, a fixed‐time control strategy is adopted, in which the upper bound of the settling time is connected with the designed parameters, but not to the initial conditions. In the design, the unknown time‐varying parameters are treated as the multiplication of known and unknown vectors, and the adaptive laws are constructed to estimate the mean value of the components in the unknown ones, which availably solve the difficulty of unknown control gains. Besides, the application of command filtered technique, which combined with the compensation signals containing the adaptive parameters, effectively avoids the “complexity explosion” problem. Further, Lyapunov stability theory verifies that the tracking error can always be kept within the boundaries of the performance functions, and converges to a designated neighbourhood of the origin within a fixed time, beyond that all signals of the closed‐loop system are bounded. Finally, the simulation results prove the effectiveness of the proposed control scheme.