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Background: Sleep deprivation (SD) is commonplace in modern society and there are large individual differences in the vulnerability to SD. We aim to identify the structural network differences based on diffusion tensor imaging (DTI) that contribute to the individual different vulnerability to SD. Methods: The number of psychomotor vigilance task (PVT) lapses was used to classify 49 healthy subjects on the basis of whether they were vulnerable or resistant to SD. DTI and graph theory approaches were used to investigate the topologic organization differences of the brain structural connectome between SD‐vulnerable and ‐resistant individuals. We measured the level of global efficiency and clustering in rich club and non‐rich club organizations. Results: We demonstrated that participants vulnerable to SD had less global efficiency, network strength, and local efficiency but longer shortest path length compared with participants resistant to SD. Lower efficiency was mainly distributed in the right insula, bilateral thalamus, bilateral frontal, temporal, and temporal lobes. Furthermore, a disrupted subnetwork was observed that consisted of widespread connections. Moreover, the vulnerable group showed significantly decreased strength of the rich club compared with the resistant group. The strength of rich club connectivity was found to be correlated negatively with PVT performance (r = −0.395, p = 0.005). We further tested the reliability of the results. Conclusion: The findings revealed that individual differences in resistance to SD are related to disrupted topologic efficiency connectome pattern, and our study may provide potential connectome‐based biomarkers for the early detection of the vulnerable degree to SD. [ABSTRACT FROM AUTHOR]

In this paper, a new approach to visual geo‐localization for natural environments is proposed. The digital elevation model (DEM) data in virtual space is rendered and construct a panoramic skyline database is constructed. By combining the skyline database with real‐world image data (used as the "queries" to be localized), visual geo‐localization is treated as a cross‐modal image retrieval problem for panoramic skyline images, creating a unique new visual geo‐localization benchmark for the natural environment. Specifically, the semantic segmentation model named LineNet is proposed, for skyline extractions from query images, which has proven to be robust to a variety of complex natural environments. On the aforementioned benchmarks, the fully automatic method is elaborated for large‐scale cross‐modal localization using panoramic skyline images. Finally, the compound index is delicately designed to reduce the storage space of the positioning global descriptors and improve the retrieval efficiency. Moreover, the proposed method is proven to outperform most state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Rational engineering active sites and vantage defects of catalysts are promising but grand challenging task to enhance photoreduction CO2 to high value‐added C2 products. In this study, we designed an N,S‐codoped Fe‐based MIL‐88B catalyst with well‐defined bipyramidal hexagonal prism morphology via a facile and effective process, which was synthesized by addition of appropriate 1,2‐benzisothiazolin‐3‐one (BIT) and acetic acid to the reaction solution. Under simulated solar irradiation, the designed catalyst exhibits high C2H4 evolution yield of 17.7 μmol g−1⋅h, which has been rarely achieved in photocatalytic CO2 reduction process. The synergistic effect of Fe‐N coordinated sites and reasonable defects in the N,S‐codoped photocatalyst can accelerate the migration of photogenerated carriers, resulting in high electron density, and this in turn helps to facilitate the formation and dimerization of C−C coupling intermediates for C2H4 effectively. [ABSTRACT FROM AUTHOR]

Rational engineering active sites and vantage defects of catalysts are promising but grand challenging task to enhance photoreduction CO2 to high value‐added C2 products. In this study, we designed an N,S‐codoped Fe‐based MIL‐88B catalyst with well‐defined bipyramidal hexagonal prism morphology via a facile and effective process, which was synthesized by addition of appropriate 1,2‐benzisothiazolin‐3‐one (BIT) and acetic acid to the reaction solution. Under simulated solar irradiation, the designed catalyst exhibits high C2H4 evolution yield of 17.7 μmol g−1⋅h, which has been rarely achieved in photocatalytic CO2 reduction process. The synergistic effect of Fe‐N coordinated sites and reasonable defects in the N,S‐codoped photocatalyst can accelerate the migration of photogenerated carriers, resulting in high electron density, and this in turn helps to facilitate the formation and dimerization of C−C coupling intermediates for C2H4 effectively. [ABSTRACT FROM AUTHOR]

A new image dehazing algorithm based on adaptive sky region is proposed in this paper, which shows good fidelity in sky region and satisfying visual effect in non‐sky region. For robust sky segmentation, we propose a rough‐to‐fine method that can make a balance between efficiency and accuracy. Considering distribution of haze is inconsistent, we divide the input image into three parts and calculate their atmospheric lights respectively. To solve the problem of invalid dark channel prior, we make an improvement for the transmission estimation. Finally, image fusion is taken as a post processing that can solve the problem of partial darkness and ensure a visual pleasing result. The experimental results for both synthetic and natural hazy images demonstrate that our algorithm performs comparable or even better results than the state‐of‐the‐art methods in terms of various measurement indexes, such as the PSNR, SSIM, and so forth. Besides, the proposed algorithm can be also applied in FPGA platform due to the optimized performance. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Middle East respiratory syndrome (MERS) is caused by MERS‐CoV that infects both human and camel. Camel is supposed to be the natural reservoir for human infection while the sources for most of the primary human infection cases are still not known. We identified two conserved pyrimidine nucleotides that flank UAAU element in MERS‐CoV 5'‐UTR. These conserved pyrimidine nucleotides distinguish MERS‐CoVs into 3 types, that is, UUAAUU, CUAAUU and CUAAUC (referred to as U‐‐‐‐U, C‐‐‐‐U, and C‐‐‐‐C types, respectively). Human MERS‐CoV displays a genetic drift from U‐‐‐‐U, C‐‐‐‐U, to C‐‐‐‐C from 2012 to 2019. Camel virus displays a genetic drift from U‐‐‐‐U to C‐‐‐‐U with a time lag when compared with human virus. The discrepancy in genetic drift seems not to support the notion that camel serves as the only natural reservoir for human infection. [ABSTRACT FROM AUTHOR]

Facial micro‐expression recognition is a natural mechanism of facial behavior with subtle muscle movements and short duration, which is widely considered to be hard to recognize. In this paper, we propose the temporal sampling deformation (TSD) to normalize the temporal lengths and conserve time domain information for micro‐expression sequences. A three‐stream combining 2D and 3D convolutional neural network (TSNN) is also proposed to capture the features of micro‐expressions and classify the expressions as well. The proposed network has two variants TSNN‐IF and TSNN‐LF, which can automatically learn spatial and temporal features at the same time. Single domain experiments and cross‐domain experiments are also performed in the three benchmark datasets (chinese academy of sciences micro‐expression II (CASME II), spontaneous micro‐expression database (SMIC), and spontaneous micro‐facial movement dataset (SAMM)) to verify the effectiveness and validity of the proposed framework. Comprehensive results and ablation studies show that the proposed method can achieve comparable or even better results compared with other state‐of‐the‐art methods for micro‐expression recognition. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Aims: The brain function impairment induced by sleep deprivation (SD) is temporary and can be fully reversed with sufficient sleep. However, in many cases, long‐duration recovery sleep is not feasible. Thus, this study aimed to investigate whether a short nap after SD is sufficient to restore brain function. Methods: The data of 38 subjects, including resting state functional magnetic resonance imaging data collected at three timepoints (before SD, after 30 h of SD, and after a short nap following SD) and psychomotor vigilance task (PVT) data, were collected. Dynamic functional connectivity (DFC) analysis was used to evaluate changes in brain states among three timepoints, and four DFC states were distinguished across the three timepoints. Results: Before SD, state 2 (a resting‐like FC matrix) was dominant (48.26%). However, after 30 h SD, the proportion of state 2 dramatically decreased, and state 3 (still resting‐like, but FCs were weakened) became dominant (40.92%). The increased proportion of state 3 positively correlated with a larger PVT "lapse" time. After a nap, the proportions of states 2 and 3 significantly increased and decreased, respectively, and the change in proportion of state 2 negatively correlated with the change in PVT "lapse" time. Conclusions: Taken together, the results indicated that, after a nap, the cognitive function impairment caused by SD may be reversed to some extent. Additionally, DFC differed among timepoints, which was also associated with the extent of cognitive function impairment after SD (state 3) and the extent of recovery therefrom after a nap (state 2). [ABSTRACT FROM AUTHOR]

Glaucoma refers to a chronic disease of the eye that leads to vision loss that is irreversible, which is called 'silent theft of sight'. Thus, an automatic glaucoma screening pipeline from optic disc (OD) localisation to glaucoma risk prediction is proposed in this study. The proposed pipeline consists of three main phases. Firstly, the OD is localised by morphological processing and sliding window methods. Secondly, a novel neural network which is in U‐shape and convolutional introduces concatenating path and fusion loss function is developed to split OD and optic cup (OC) at the same time. Thirdly, both clinical measurements including optic cup‐to‐disc ratio (CDR), neuroretinal rim related features, and hidden features including statistical moments, entropy and energy are combined to train glaucoma classifiers. According to the results of the experiment, the proposed segmentation network achieves the best performance on both OD and OC segmentation and the proposed CDR calculation method is capable of achieving the performance similar to that of ophthalmologist on CDR measurement. Besides, the authors' glaucoma classification model can obtain the best performance on sensitivity and area under the curve score in comparison with the existing methods. [ABSTRACT FROM AUTHOR]

Chinese ink painting is a traditional art form that is highly regarded throughout the world for its theory, expression, technicality, and artistry. In this paper, we present a method to convert a photograph into a Chinese ink painting. First, the structure description map (SDM) for a photo is estimated to build the object appearance depiction. To make the converted Chinese painting's color be consistent with traditional color requirement of Chinese ink painting, a color transform algorithm is proposed to put color on the SDM. A qualitative evaluation approach is also proposed to carry out a comparative study with other simulation methods. Conversion results demonstrate that, using the proposed method, one can produce very beautiful Chinese ink painting from a photo with less user interaction and much faster conversion speed compared to other approaches. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The information unavailability of a global navigation satellite system (GNSS) for geo‐localization in many military and tourism applications implies the need to employ other applicable types of information, such as automatic image‐based location recognition. Unlike most existing localization methods that use GNSS information to locate an initial position, this paper proposes an automatic geo‐localization framework that does not require GNSS data. The proposed framework is a two‐stage pipeline that uses a query image and digital elevation model (DEM) data as input. The authors frame automatic geo‐localization without GNSS recordings as a skyline matching problem. By extracting the skyline from the DEM data and query images, the query image can be localized by matching the query skyline feature to the DEM skyline database. It has been demonstrated that this low‐cost approach can perform efficiently in mountainous or hilly areas to produce reliable localization results. The system was tested on 50 testing site points within a large‐scale area (China, 202.6 km2), and an average position error of 43.13 m was detected within 4.5 s. [ABSTRACT FROM AUTHOR]

Membrane separation plays a crucial role in the current increasingly complex energy environment. Membranes prepared by metal–organic framework (MOF) materials usually possess unique advantages in common, such as uniform pore size, ultra‐high porosity, enhanced selectivity and throughput, and excellent adsorption property, which have been contributed to the separation fields. In this comprehensive review, we summarize various designs and synthesized strategies of free‐standing MOF and composite MOF‐based membranes for water treatment. Special emphases are given not only on the effects of MOF on membrane performance, removal efficiencies, and elimination mechanisms, but also on the importance of MOF‐based membranes for the applications of oily and micro‐pollutant removal, adsorption, separation, and catalysis. The challenges and opportunities in the future for the industrial implementation of MOF‐based membranes are also discussed. [ABSTRACT FROM AUTHOR]

Photocatalytic reduction of CO2 has drawn much attention as a promising way that can effectively alleviate the issue of global warming and energy crisis. In this work, we fabricated a series of CdS/NH2‐UiO‐66 composites with varied CdS amounts and tested their capacity for photocatalytic reduction of CO2. The reactions were performed in a solvent‐free system and displayed excellent selectivity for CO production without liquid phase products. When the content of CdS in the composite is up to 40 %, the hybrid catalyst produces 105.41 μmol/g within 6 h, exhibiting remarkable photocatalytic performance, which is much higher than that catalyzed by mechanically mixed CdS and NH2‐UiO‐66. The brilliant catalytic performance of the composite catalyst is attributed to the formation of heterostructure between the well‐dispersed CdS and NH2‐UiO‐66, which promotes the enhancement of electron transfer during photocatalysis. [ABSTRACT FROM AUTHOR]

The interactions between extra‐embryonic tissues and embryonic tissues are crucial to ensure proper early embryo development. However, the understanding of the crosstalk between the embryonic tissues and extra‐embryonic tissues is lacking, mainly due to ethical restrictions, difficulties in obtaining natural human embryos, and lack of appropriate in vitro models. Here by aggregating human embryonic stem cells (hESCs) with human trophoblast stem cells (hTSCs), we revealed the hESCs robustly self‐organized into a unique asymmetric structure which the primitive streak (PS) like cells exclusively distributed at the distal end to the TS‐compartment, and morphologically flattened cells, presumed to be the extra‐embryonic mesoderm cells (EXMC) like cells, were induced at the proximal end to hTSCs. Our study revealed two potential roles of extra‐embryonic trophectoderm in regulating the proper PS formation during gastrulation and EXMCs induction from the human epiblast. [ABSTRACT FROM AUTHOR]

Activation of thioglycosides upon UV irradiation followed by cupric triflate oxidation leads to the in situ formation of an oxacarbenium ion which is able to undergo glycosylation reactions with a wide variety of substrates such as sugars, amino acids, terpenes, and sterols. [ABSTRACT FROM AUTHOR]

Summary: This article studies the parameter identification problem for bilinear state space models with time‐varying time delays. Considering the correlation of time delays, the Markov chain switching mechanism is adopted to model the delay sequence. Based on the observer canonical form, the bilinear state space model is transformed into a regressive form. A bilinear state observer is designed to estimate the state variables. Under the variational Bayesian scheme, the system parameters, discrete delays, and the Markov transition probabilities are identified by using the measurement data. A numerical example and a continuous stirred tank reactor simulation are employed to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Total sleep deprivation (TSD) is common in modern society leading to deterioration of multiple aspects of cognition. Dynamic interaction effect of circadian rhythmicity and homeostatic sleep pressure on sustained attention have been intensively investigated, while how this effect was represented on performance and cerebral responses to working memory, another important element of many neurobehavioral tasks, was not well elucidated. Thirty‐six healthy subjects with intermediate chronotype performed the Sternberg working‐memory task (SWMT) while undergoing functional magnetic resonance imaging every 2 hr from 10:00 p.m. on the first day to 6:00 a.m. on the second day. Using data from three imaging sessions (10:00 p.m., 04:00 a.m., and 06:00 a.m.), we found that the slowest SWMT reaction time and weakest cerebral responses were not at the end of TSD (06:00 a.m.) but during the early morning (04:00 a.m.) hours of the TSD. In addition, during this worst period of TSD, reaction time for the SWMT were found to be negatively correlated with task‐related activation in the angular gyrus and positively correlated with the degree of negative correlation between the control and default networks. Our results revealed a rebound of SWMT reaction time and cerebral responses after the mid‐time point of regular biological sleep night and provided more evidence that different cognitive tasks are differentially affected by sleep loss and circadian rhythmicity. [ABSTRACT FROM AUTHOR]

Abstract: Graphene aerogel microlattices (GAMs) hold great prospects for many multifunctional applications due to their low density, high porosity, designed lattice structures, good elasticity, and tunable electrical conductivity. Previous 3D printing approaches to fabricate GAMs require either high content of additives or complex processes, limiting their wide applications. Here, a facile ion‐induced gelation method is demonstrated to directly print GAMs from graphene oxide (GO) based ink. With trace addition of Ca2+ ions as gelators, aqueous GO sol converts to printable gel ink. Self‐standing 3D structures with programmable microlattices are directly printed just in air at room temperature. The rich hierarchical pores and high electrical conductivity of GAMs bring admirable capacitive performance for supercapacitors. The gravimetric capacitance (Cs) of GAMs is 213 F g−1 at 0.5 A g−1 and 183 F g−1 at 100 A g−1, and retains over 90% after 50 000 cycles. The facile, direct 3D printing of neat graphene oxide can promote wide applications of GAMs from energy storage to tissue engineering scaffolds. [ABSTRACT FROM AUTHOR]

Introduction Understanding the neural basis underlying major depressive disorder ( MDD) is essential for the diagnosis and treatment of this mental disorder. Aberrant activation and functional connectivity of the default mode network ( DMN) have been consistently found in patients with MDD. It is not known whether effective connectivity within the DMN is altered in MDD. Objects The primary object of this study is to investigate the effective connectivity within the DMN during resting state in MDD patients before and after eight weeks of antidepressant treatment. Methods We defined four regions of the DMN (medial frontal cortex, posterior cingulate cortex, left parietal cortex, and right parietal cortex) for each participant using a group independent component analysis. The coupling parameters reflecting the causal interactions among the DMN regions were estimated using spectral dynamic causal modeling ( DCM). Results Twenty-seven MDD patients and 27 healthy controls were included in the statistical analysis. Our results showed declined influences from the left parietal cortex to other DMN regions in the pre-treatment patients as compared with healthy controls. After eight weeks of treatment, the influence from the right parietal cortex to the posterior cingulate cortex significantly decreased. Conclusion These findings suggest that the reduced excitatory causal influence of the left parietal cortex is the key alteration of the DMN in patients with MDD, and the disrupted causal influences that parietal cortex exerts on the posterior cingulate cortex is responsive to antidepressant treatment. [ABSTRACT FROM AUTHOR]