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Organic semiconductors (OSCs) possess diverse chemical structures and tailored optoelectronic properties via simple chemical modifications, so increasing use of them are found in efficient visible-light photocatalysis. However, the weak chemical bonds and the poor charge behavior (e.g., low concentration of free charge carriers, low carrier mobility) intrinsic in them, always incur quite limited stability and efficiency. Therefore, the assembly of them into refined nanostructures or nanocomposites is usually proposed to enhance their optoelectronic properties, as well as the photocatalytic efficiency and reliability. Zero-dimensional (0D) nanoparticles are low in size and hence high specific surface area (SSA); One-dimensional (1D) nanostructures are usually arranged in an orderly long range thus leading to low surface defect density and increased carrier mobility; Two-dimensional (2D) nanostructures are particularly capable of enhancing the photogenerated charge utilization because of their large reaction sites and shortened charge transport length. Furthermore, the building of heterogeneous interfaces in the nanocomposites can effectively facilitate the special charge separation. All these highlight the importance of organic nanostructures in improving the photocatalytic activity and stability. Therefore, organic semiconductor nanostructures (OSNs) have been increasingly used in the photocatalytic water splitting into H2 and O2, CO2 reduction, pollutant decomposition, disinfection, and etc.. In this review, we first examine the important optoelectronic properties of OSNs that govern the photocatalytic processes; we then analyze different classes of OSNs and their mechanistic pathways, with an emphasis on the structure-property relationships; we also introduced various photocatalytic applications of OSNs; we lastly propose the challenges and future outlook in real use.

Cerebral conditioning is defined as the mild harmful stimuli applied to the brain before ischemia (preconditioning), during ischemia (perconditioning), immediately, a few hours or days after reperfusion (postconditioning). Various noxious stimuli can precondition, percondition or postcondition the brain, including ischemia, hypoxia or anesthetics to induce tolerance to lethal ischemia/reperfusion injury. The mechanisms underlying cerebral conditioning range from sensors and transducers including extracellular neurotransmitters and receptors, intracellular signals, transcription factors and epigenetic regulation, to effectors involving physiological protection, stem cells, heat shock proteins, Bcl-2, mitochondria, ubiquitin - proteasome pathway and autophagy pathway. Based on the large number of studies conducted in animal models, researchers explore the clinical application of cerebral conditioning. Remote ischemic conditioning is considered the most applicable and clinically relevant form of cerebral conditioning. The translational research also involves development of the biomarkers of conditioning and optimization of organ transplantation. The present review summarized the recent progress in signaling pathways and clinical applications of cerebral conditioning to explore the possibility to develop a potential therapeutic strategy for the prevention and treatment of ischemic stroke.

Modern engineering systems are usually equipped with a variety of sensors to measure real-time operating conditions. Based on the condition monitoring data from multiple sensor sources, this paper deals with a dynamic predictive maintenance scheduling using deep learning ensemble for system health prognostics. The deep learning ensemble model is composed of deep autoencoder and bidirectional long short-term memory in series, and aims to accurately estimate the system health state and remaining useful life. The deep autoencoder is used to extract the deep representative features hidden in condition monitoring data, whereas the inclusion of the bidirectional long short-term memory allows learning the temporal correlation information of features in both forward and backward time directions. Thus, the combination of the two models forms an effective model. With obtained prognostic information, optimal maintenance decisions are determined by two designed rules. The first rule presets a reliable remaining useful life threshold to dynamically judge whether maintenance is carried out at current inspection time, while the second one selects a degradation state to dynamically determine whether to place a spare part order. The performance of the proposed dynamic predictive maintenance strategy is measured by the maintenance cost per unit operating time (cost rate) using the aero-engine dataset from NASA. Its effectiveness is demonstrated by comparing with recent publications.

Atrial fibrillation (AF) is one of the most common arrhythmias, associated with high morbidity, mortality, and healthcare costs, and it places a significant burden on both individuals and society. Anti-arrhythmic drugs are the most commonly used strategy for treating AF. However, drug therapy faces challenges because of its limited efficacy and potential side effects. Catheter ablation is widely used as an alternative treatment for AF. Nevertheless, because the mechanism of AF is not fully understood, the recurrence rate after ablation remains high. In addition, the outcomes of ablation can vary significantly between medical institutions and patients, especially for persistent AF. Therefore, the issue of which ablation strategy is optimal is still far from settled. Computational modeling has the advantages of repeatable operation, low cost, freedom from risk, and complete control, and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance. This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF, from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation. Finally, we summarize current developments and challenges and provide our perspectives and suggestions for future directions.

Light-emitting diodes (LEDs) based on metal halide perovskite quantum dots (QDs) have achieved impressive external quantum efficiencies; however, the lack of surface protection of QDs, combined with efficiency droop, decreases device operating lifetime at brightnesses of interest. The epitaxial incorporation of QDs within a semiconducting shell provides surface passivation and exciton confinement. Achieving this goal in the case of perovskite QDs remains an unsolved challenge in view of the materials' chemical instability. Here, we report perovskite QDs that remain stable in a thin layer of precursor solution of perovskite, and we use strained QDs as nucleation centers to drive the homogeneous crystallization of a perovskite matrix. Type-I band alignment ensures that the QDs are charge acceptors and radiative emitters. The new materials show suppressed Auger bi-excition recombination and bright luminescence at high excitation (600 W cm-2), whereas control materials exhibit severe bleaching. Primary red LEDs based on the new materials show an external quantum efficiency of 18%, and these retain high performance to brightnesses exceeding 4700 cd m-2. The new materials enable LEDs having an operating half-life of 2400 h at an initial luminance of 100 cd m-2, representing a 100-fold enhancement relative to the best primary red perovskite LEDs.

Bladder cancer (Bca) is the second most common malignant tumor of the genitourinary system in Chinese male population with high potential of recurrence and progression. The overall prognosis has not been improved significantly for the past 30 years due to the lack of early theranostic technique. Currently the early theranostic technique for bladder cancer is mainly through the intravesical approach, but the clinical outcomes are poor due to the limited tumor-targeting efficiency. Therefore, the targeting peptides for bladder cancer provide possibility to advance intravesical theranostic technique. However, no systematic review has covered the wide use of the targeting peptides for intravesical theranostic techniques in bladder cancer. Herein, a summary of original researches introduces all aspects of the targeting peptides for bladder cancer, including the peptide screening, the targeting mechanism and its preclinical application.

Amyloid-β peptide (Aβ) aggregation is the hallmark of Alzheimer’s disease (AD). The imbalance between the production and clearance of Aβ results in the accumulation and aggregation of Aβ in the brain. Thus far, few drugs are available for AD treatment, but exercise has been recognized for its cognition-enhancing properties in AD patients. The underlying mechanisms remain unclear. Our recent study showed that long-term running exercise could activate the lysosomal function in the brains of mice. In this study, we investigated whether exercise could reduce Aβ accumulation by activating lysosomal function in APP/PSEN1 transgenic mice. Started at the age of 5 months, the mice were trained with a running wheel at the speed of 18 r/min, 40 min/d, 6 d/week for 5 months, and were killed at the end of the 10th month, then brain tissue was collected for biochemical analyses. The cognitive ability was assessed in the 9th month. We showed that long-term exercise significantly mitigated cognitive dysfunction in AD mice, accompanied by the enhanced lysosomal function and the clearance of Aβ in the brain. Exercise significantly promoted the nuclear translocation of transcription factor EB (TFEB), and increased the interaction between nuclear TFEB with AMPK-mediated acetyl-CoA synthetase 2, thus enhancing transcription of the genes associated with the biogenesis of lysosomes. Exercise also raised the levels of mature cathepsin D and cathepsin L, suggesting that more Aβ peptides could be degraded in the activated lysosomes. This study demonstrates that exercise may improve the cognitive dysfunction of AD by enhancing lysosomal function.

The all-inorganic nature of CsPbI3 perovskites allows to enhance stability in perovskite devices. Research efforts have led to improved stability of the black phase in CsPbI3 films; however, these strategies-including strain and doping-are based on organic-ligand-capped perovskites, which prevent perovskites from forming the close-packed quantum dot (QD) solids necessary to achieve high charge and thermal transport. We developed an inorganic ligand exchange that leads to CsPbI3 QD films with superior phase stability and increased thermal transport. The atomic-ligand-exchanged QD films, once mechanically coupled, exhibit improved phase stability, and we link this to distributing strain across the film. Operando measurements of the temperature of the LEDs indicate that KI-exchanged QD films exhibit increased thermal transport compared to controls that rely on organic ligands. The LEDs exhibit a maximum EQE of 23 % with an electroluminescence emission centered at 640 nm (FWHM: ≈31 nm). These red LEDs provide an operating half-lifetime of 10 h (luminance of 200 cd m-2 ) and an operating stability that is 6× higher than that of control devices.

Yu Liu,1 Le-Feng Wang,1 Li-Hong Liu,1 Xin-Chun Yang,1 Zheng-Hong Ren,2 Kui-Bao Li,1 Mu-Lei Chen,1 Hong-Shi Wang,1 Jiu-Chang Zhong,1 Li Xu,1 Zhu-Hua Ni,1 Wei-Ming Li,1 Kun Xia,1 Da-Peng Zhang,1 Hao Sun,1 Zong-Sheng Guo,1 Yong-Hui Chi,1 Ji-Fang He,1 Zhi-Yong Zhang,1 Feng Jiang1 1Heart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, People’s Republic of China; 2School of Public Health, Peking University Health Science Center, Beijing, People’s Republic of ChinaCorrespondence: Le-Feng WangHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, No. 8 of Gongtinan Road, Chaoyang District, Beijing, People’s Republic of ChinaTel/Fax +86 10 85231173Email wanglefeng_dr66@163.comObjective: Patients presenting with acute myocardial infarction (AMI) with prior digestive system disease are more likely to suffer from gastrointestinal (GI) bleeding than those without these diseases. However, few articles reported how the different conditions of the digestive tract produced different risks of GI bleeding.Methods: A single-center study on 7464 patients admitted for AMI from December 2010 to June 2019 in the Beijing Chaoyang Heart Center was retrospectively examined. Patients with major GI bleeding (n = 165) were compared with patients without (n = 7299). Univariate and multivariate logistic regression models were constructed to test the association between GI bleeding and prior diseases of the digestive tract, including gastroesophageal reflux disease, chronic gastritis, peptic ulcer, hepatic function damage, diseases of the colon and rectum, and gastroenterological tract tumors.Results: Of the 7464 patients (mean age, 63.4; women, 25.6%; STEMI, 58.6%), 165 (2.2%) experienced major GI bleeding, and 1816 (24.3%) had a history of digestive system disease. The risk of GI bleeding was significantly associated with peptic ulcer (OR = 4.19, 95% CI: 1.86– 9.45) and gastroenterological tumor (OR = 2.74, 95% CI: 1.07– 7.04), indicated by multivariate logistic regression analysis.Conclusion: Preexisting peptic ulcers and gastroenterological tract tumors rather than other digestive system diseases were indicators of gastrointestinal bleeding in patients with AMI who undergo standard antithrombotic treatment during hospitalization.Keywords: gastrointestinal bleeding, digestive system disease, acute myocardial infarction, peptic ulcer, gastroenterological tract tumor

Colloidal quantum dot (CQD) solar cells are solution-processed photovoltaic devices that exhibit promise in harvesting the infrared solar spectrum. Solid-state ligand exchange is the method employe...

Reliable and accurate aero-engine remaining useful life (RUL) prediction plays a key role in aero-engine prognostics and health management (PHM) system. However, due to the epistemic uncertainties associated with aero-engine systems, prediction errors are unavoidable and sometimes significant in traditional deterministic point prediction methods. To improve the accuracy and credibility of RUL prediction, a novel prediction interval (PI) estimation method is proposed to quantify the uncertainties in RUL prediction. The proposed method involves the data clustering, mathematical statistical analysis and deep learning techniques, and is achieved through offline and online phases. In the offline phase, an enhanced fuzzy c-means algorithm (FCM) is proposed to divide the aero-engine health status into several discrete states. After labeling the health state of each sampling point, PIs are computed for them. This step is achieved by the empirical distributions of errors associated with all instances belonging to the health state under consideration. In the online phase, a bidirectional long short-term memory (Bi-LSTM) network is employed to estimate the boundaries of point prediction, and thus the PI of aero-engine RUL is generated. The aero-engine degradation dataset from NASA is used to validate the proposed RUL PI estimation method. The results obtained indicate that the proposed method is a promising tool for providing reliable aero-engine RUL interval estimates, which can inform maintenance-related decisions.

Colloidal quantum dot (CQD) solar cells composed of ionic halide passivated active layers benefit from improved passivation and high carrier mobility because of short interparticle distance. Howeve...

In this work, the effect of non-drag forces (lift force, turbulent dispersion force, wall lubrication force and virtual mass force) and bubble induced turbulence (BIT) on the CFD-PBM simulation of ...

Bias-stress instability has been a challenging problem and a roadblock for developing stable p-type organic field-effect transistors (OFETs). This device instability is hypothesized because of electron-correlated charge carrier trapping, neutralization, and recombination at semiconductor/dielectric interfaces and in semiconductor channels. Here, in this paper, a strategy is demonstrated to improve the bias-stress stability by constructing a multilayered drain electrode with energy-level modification layers (ELMLs). Several organic small molecules with high lowest unoccupied molecular orbital (LUMO) energy levels are experimented as ELMLs. The energy-level offset between the Fermi level of the drain electrode and the LUMOs of the ELMLs is shown to construct the interfacial barrier, which suppresses electron injection from the drain electrode into the channel, leading to significantly improved bias-stress stability of OFETs. The mechanism of the ELMLs on the bias-stress stability is studied by quantitative modeling analysis of charge carrier dynamics. Of all injection models evaluated, it is found that Fowler-Nordheim tunneling describes best the observed experimental data. Both theory and experimental data show that, by using the ELMLs with higher LUMO levels, the electron injection can be suppressed effectively, and the bias-stress stability of p-type OFETs can thereby be improved significantly.

Colloidal quantum dot (QD) solids are emerging semiconductors that have been actively explored in fundamental studies of charge transport1 and for applications in optoelectronics2. Forming high-quality QD solids—necessary for device fabrication—requires substitution of the long organic ligands used for synthesis with short ligands that provide increased QD coupling and improved charge transport3. However, in perovskite QDs, the polar solvents used to carry out the ligand exchange decompose the highly ionic perovskites4. Here we report perovskite QD resurfacing to achieve a bipolar shell consisting of an inner anion shell, and an outer shell comprised of cations and polar solvent molecules. The outer shell is electrostatically adsorbed to the negatively charged inner shell. This approach produces strongly confined perovskite QD solids that feature improved carrier mobility (≥0.01 cm2 V−1 s−1) and reduced trap density relative to previously reported low-dimensional perovskites. Blue-emitting QD films exhibit photoluminescence quantum yields exceeding 90%. By exploiting the improved mobility, we have been able to fabricate CsPbBr3 QD-based efficient blue and green light-emitting diodes. Blue devices with reduced trap density have an external quantum efficiency of 12.3%; the green devices achieve an external quantum efficiency of 22%. A solution-based ligand-exchange strategy enables the realization of close-packed quantum dot solid films with near-unity photoluminescence quantum yield and high charge carrier mobility.

How to correctly acquire the appropriate features is a primary problem in network protocol recognition field. Aiming to avoid the trouble of artificially extracting features in traditional methods and improve recognition accuracy, a network protocol recognition method based on Convolutional Neural Network (CNN) is proposed. The method utilizes deep learning technique, and it processes network flows automatically. Firstly, normalization is performed on the intercepted network flows and they are mapped into two-dimensional matrix which will be used as the input of CNN. Then, an improved classification model named PtrCNN is built, which can automatically extract the appropriate features of network protocols. Finally, the classification model is trained to recognize the network protocols. The proposed approach is compared with several machine learning methods. Experimental results show that the tailored CNN can not only improve protocol recognition accuracy but also ensure the fast convergence of classification model and reduce the classification time.

Since ancient times, China and South Korea have been deeply connected in politics, geography, culture, history and economy. Since the Han dynasty, the Korean peninsula was deeply influenced by Chinese culture in terms of ritual system, politics, economy, art and customs. Although there are intertwined musical elements in Chinese and Korean music, there are also many differences due to geographical, lifestyle, customs and other reasons, which forms different musical cultural systems with distinct national characteristics. After the division of North and South Korea, South Korea was greatly influenced by the western countries, and naturally formed a music style totally different from the traditional Confucian culture in terms of the development of music culture. Since the establishment of diplomatic ties between China and the South Korea in 1992, cultural communications and cooperation have become increasingly active, and the interaction and integration of music have been continuously expanded. Chinese music is also increasingly popular with South Koreans, but the breadth and depth remains to be improved. By studying the history and current situation of Chinese-Korean music integration, this paper finds that Chinese and Korean music in history interacted and integrated with Musical Instruments, instrumental music, music types, music theories and other aspects, which continuously promoted the innovation and development of their respective music art. In modern times, Korean music industrialization development model is mature, the smell of music is very sensitive, which can quickly capture the young people''s preference. And through creating singing and dancing combination and other forms to integrate the idol and music, using the power of the idol to promote the development of music, music culture output also showed a more active attitude, set off a wave of Korean music in China, the development of China''s music industry has had an important impact. Chinese music education should actively learn from the experience of Korean music development, combine the current situation and characteristics of Chinese music, take an open attitude, focus on innovation and exploration, develop closely with the modern market, achieve the goal of sound interaction between music education and music industry, and promote the diversified development of Chinese music.

Na-ion capacitors (NICs) are promising energy storage devices in virtue of their merits in combining the high energy densities of secondary batteries and the high power densities of supercapacitors. However, it is still very challenging to achieve a balanced energy-power performance in NIC device due to the kinetic imbalance between the battery-type anode and the capacitive-type cathode. In this work, an NIC device based on carbon materials for both anode and cathode has been reported. As-prepared (polyimide/graphene oxide)-derived carbon (PIGC) anode material shows excellent rate capability, which can deliver a specific capacity of 110 mAh g−1 at high current densities of 5 A g−1. In addition, the N, B co-doped expanded reduced graphite oxide (NBEG) cathode demonstrates a high specific capacitance of 328 F g−1. Due to the improved rate capability of PIGC anode and specific capacitance of NBEG cathode, the imbalance on the energy and power densities between anode and cathode is well addressed. As-assembled PIGC//NBEG device can deliver an energy density of 55 W h kg−1 even at a high power density of 9500 W kg−1. The energy-power properties of PIGC//NBEG are superior to many state-of-the-art NIC devices that using carbon or non-carbon based electrodes. This work offers not only a promising device configuration with superior energy-power properties, but also a guidance for the design strategies on electrode materials for high-throughput energy storage systems. Keywords: Carbon materials, Doping, Porous structure, Sodium ion capacitors, Energy storage

Light-emitting diodes (LEDs) based on excitonic material systems, in which tightly bound photoexcited electron–hole pairs migrate together rather than as individual charge carriers, offer an attractive route to developing solution-processed, high-performance light emitters. Here, we demonstrate bright, efficient, excitonic infrared LEDs through the incorporation of quantum dots (QDs)1 into a low-dimensional perovskite matrix. We program the surface of the QDs to trigger fast perovskite nucleation to achieve homogeneous incorporation of QDs into the matrix without detrimental QD aggregation, as verified by in situ grazing incidence wide-angle X-ray spectroscopy. We tailor the distribution of the perovskites to drive balanced ultrafast excitonic energy transfer to the QDs. The resulting LEDs operate in the short-wavelength infrared region, an important regime for imaging and sensing applications, and exhibit a high external quantum efficiency of 8.1% at 980 nm at a radiance of up to 7.4 W Sr−1 m−2. Embedding perovskite quantum dots in perovskite leads to bright, efficient 980 nm LEDs with applications in imaging and sensing.

We acknowledge the use of KAUST Core Lab and KAUST Solar Center facilities. This work was supported by KAUST and the Office of Sponsored Research (OSR) under award no. OSR-2017-CRG-3380. F.G. is a Wallenberg Academy Fellow.

Constructing flexible hybrid supercapacitors is a feasible way to achieve devices with high energy density, high power density and flexibility at the same time. Herein, flexible asymmetric hybrid supercapacitors are fabricated with blow spun activated carbon fibers. Owing to the highly effective conductive network, abundant nitrogen doping, optimized pore-structure and surface chemical properties of the carbon fibers, the as-prepared flexible hybrid supercapacitor shows outstanding energy and power performance (98 W h kg−1 (0.3 mW h cm−2) @ 400 W kg−1, 9 W h kg−1 @ 34 kW kg−1), as well as excellent cycle stability with 93% capacitance retention after 4000 cycles.

Shock trains are formed by shock wave boundary layer interaction in isolator to match the pressure between inlet and combustor. However, the complexity of this problem has primarily restricted to rigid isolators without deformation. A little is known regarding the impact of wall vibration, due to structural elasticity, on the flow in isolator. The current study focuses on this problem by comparing changes of 13 parameters regarding separation zone, shock structure, flow asymmetry and isolator performance. Results examine the differences due to one-wall vibration, two-wall vibration and short panel vibration. Analyses indicate that one-wall vibration will cause the upstream movement and length decrease of separation zone, upstream movement and length growth of shock trains, increase of flow asymmetry with large transient side loads and decrease of performance. Moreover, compared to one-wall vibration, two walls vibrating in opposite direction leads to a larger influence on flow structures and isolator performance, while the effect of two-wall vibration in the same direction is relative minor on flow structures and significant on flow asymmetry as well as isolator performance. Furthermore, by placing vibrating panels at different locations, analyses identify that the influence of upstream and midstream vibrations is stronger than downstream vibration in wall vibration. The upstream vibration has a greater impact on flow structures while the midstream vibration has a greater effect on flow asymmetry and isolator performance. The current study emphasizes the importance of future investigations on aeroelastic problem in isolator and provides primary knowledge for flow control by considering flexible or vibrating panel.

Deep-blue light-emitting diodes (LEDs) (emitting at wavelengths of less than 450 nm) are important for solid-state lighting, vivid displays and high-density information storage. Colloidal quantum dots, typically based on heavy metals such as cadmium and lead, are promising candidates for deep-blue LEDs, but these have so far had external quantum efficiencies lower than 1.7%. Here we present deep-blue light-emitting materials and devices based on carbon dots. The carbon dots produce emission with a narrow full-width at half-maximum (about 35 nm) with high photoluminescence quantum yield (70% ± 10%) and a colour coordinate (0.15, 0.05) closely approaching the standard colour Rec. 2020 (0.131, 0.046) specification. Structural and optical characterization, together with computational studies, reveal that amine-based passivation accounts for the efficient and high-colour-purity emission. Deep-blue LEDs based on these carbon dots display high performance with a maximum luminance of 5,240 cd m−2 and an external quantum efficiency of 4%, notably exceeding that of previously reported quantum-tuned solution-processed deep-blue LEDs. Deep-blue high-colour-purity light-emitting materials are developed by using amine-based edge passivation. The light-emitting diodes based on the carbon dots exhibit a maximum luminance of 5,240 cd m–2 and an external quantum efficiency of 4%.

Halide perovskites are a compelling candidate for the next generation of clean-energy-harvesting technologies owing to their low cost, facile fabrication and outstanding semiconductor properties. However, photovoltaic device efficiencies are still below practical limits and long-term stability challenges hinder their practical application. Current evidence suggests that strain in halide perovskites is a key factor in dictating device efficiency and stability. Here we outline the fundamentals of strain within halide perovskites relevant to photovoltaic applications and rationalize approaches to characterize the phenomenon. We examine recent breakthroughs in eliminating the adverse impacts of strain, enhancing both device efficiencies and operational stabilities. Finally, we discuss further challenges and outline future research directions for placing stress and strain studies at the forefront of halide perovskite research. An extensive understanding of strain in halide perovskites is needed, which would allow effective strain management and drive further enhancements in efficiencies and stabilities of perovskite photovoltaics.

Background: Hepatocellular carcinoma (HCC), which is the most common type of primary liver cancer, often presents at advanced stage with a dismal prognosis. Novel tumor biomarkers are needed to aid in HCC early detection and prognostication. Methods: Immunohistochemical staining for RecQ-mediated genome instability protein 2 (RMI2) was performed in 330 surgically resected HCC specimens and 190 adjacent normal tissues. Univariate and multivariate regression analysis were applied to identify prognostic indicators of HCC outcomes. Patient's survival was assessed with the Kaplan–Meier method. Results: RMI2 in HCC tissue was significantly higher than that in adjacent normal tissues, and was positively correlated with HCC histological grade and stage ( P

To reverse the early-stage relapse post-hematopoietic stem cell transplantation, we investigated the safety and efficacy of a new epigenetic regimen (chidamide and decitabine plus thymalfasin simultaneously) on acute myeloid leukemia patients (excluding acute promyelocytic leukemia). Twenty-four patients were enrolled in this observational study during April 2015 to May 2018. The most common adverse event was reversible CTCAE grade 2 thrombocytopenia (20/24). Strikingly, all 24 patients had response to this epigenetic regimen accompanied with decreased measurable residual disease. The overall survival rate is 79.2% (19/24), with a relapse-free survival rate of 79.2% (19/24). During this regimen treatment, Th1 cells and CD3+CD4-CD8+T cells increased, and Th17 cells decreased gradually. The status of high Th1 and low Th17 cells was still observed on the 3rd month after discontinuation of this regimen. Interestingly, the significantly elevated ratio of Th1/Th17 seemed to reflect the treatment-related immune effect, which may be a valuable marker to be monitored in the early-relapse stage for evaluating the efficacy and prognosis.

Background Immune rejection of heart transplantation has been regarded as the biggest challenge encountered by a patient suffering from end-stage heart disease. The transplantation of human amnion-derived mesenchymal stem cells (hAD-MSCs) has exhibited promising application prospects in organ transplantation. However, its persistent unsatisfactory tolerance has limited the widespread application of this technology. We aim to investigate the role of tumor necrosis factor-α-induced protein-8 like-2 (TIPE2)-mediated hAD-MSCs in immune tolerance in heart transplantation and its molecular regulatory mechanisms. Methods This project detected the effect of TIPE2 on immune tolerance by constructing an allogeneic heart transplantation mouse model through which TIPE2-overexpressed hAD-MSCs were injected into recipients. The fluorescence distribution of TIPE2-hAD-MSCs in mice was observed by a small animal in vivo imaging system. Pathological changes of the transplanted heart were detected by hematoxylin and eosin (HE) staining. Flow cytometry was performed to detect the content of cardiac lymphocytes. The expression of immune-induced related factors was measured by quantitative real-time PCR (qRT-PCR) and western blot assays. Results TIPE2-hAD-MSCs protected myocardial tissue structures, reduced the spleen and thymus indexes in recipient mice, minimized the content of cardiac lymphocytes, reduced expressions of ERK, p38, and IFN-γ, and elevated expressions of both IL-10 and TGF-β, markedly improving the survival time and survival rates of recipient mice. Conclusions TIPE2-hAD-MSCs induce immune tolerance and improve the survival rates of allogeneic heart transplantation in mice. This study is expected to offer an ideal source and target of cells for organ transplantation.

Particle aggregation and breakage phenomena are widely found in various industries such as chemical, agricultural and pharmaceutical processes. In this study, a physics-informed neural network is developed for solving both the forward and inverse problems of particle aggregation and breakage processes. In this method, the population balance equation is directly embedded in the loss function of a neural network so that the network can be trained efficiently and fulfil physical constraints. For the forward problems, solutions of population balance equations are obtained through the optimization of the neural network where the predictions well match the analytical solutions. In the inverse modelling, the data-driven discovery of model parameters of population balance equations is investigated. The sensitivity regarding the selection of different neural network structures is also investigated. The developed population balance equations embedded with neural network approach is promising for solving inverse problems of particle aggregation and breakage processes with noisy observation data.

Background Growing evidences showed that gut microbiota is associated with premature ovarian failure (POF). Many case reports had shown that electro-acupuncture was effective in the treatment of POF. However, there was little research on regulating gut microbiome of POF mice by electro-acupuncture. Therefore, this study aimed to verify whether electro-acupuncture could improve ovarian function and regulate gut microbiome in mice with POF. In addition, the therapeutic effects of electro-acupuncture at acupoints and non-acupoints were compared. Methods POF mice were established by injected intraperitoneally with cisplatin (2mg/kg) for 2 weeks. Guanyuan (CV4) and Sanyinjiao (SP6) were selected in the electro-acupuncture at acupoints group (EA group). Non-acupoints which around CV4 and SP6 were selected in the electro-acupuncture at non-acupoints group (EN group). EA group and EN group were treated for 3 weeks. The ovarian function was evaluated by assays of histopathological and molecular. Meanwhile, the gut microbiome of POF mice was detected by 16S rDNA sequencing. Results The results showed that EA could restore the estrous cycle and reduce the number of atresia follicles in POF mice. The levels of serum follicle stimulating hormone and luteinizing hormone were decreased by EA. As well as, the levels of serum estradiol, anti mullerian hormone and β-glucuronidase were increased by EA. The relative expressions of PI3K, AKT and mTOR were increased to promote the proliferation of ovarian cells in EA group. According to the results of 16S rDNA sequencing, we found that the diversity of gut microbiome in mice with POF was changed. However, the abundance and diversity of gut microbiome could be regulated by EA in POF mice. The relative abundance of beneficial bacteria was increased by EA. The KEGG pathway analysis showed that the gut microbiome which associated with estrogen signaling pathway, oocyte maturation and PI3K-AKT signaling pathway were regulated by EA. Conclusions EA could provide protection against cisplatin-induced ovarian damage. The abundance and diversity of probiotics could be increased by EA. Moreover, EA might treat POF via regulating the gut microbiome.

Objectives/hypothesis Tissue-engineered tracheal grafts (TETGs) offer a potential solution for repair of long-segment airway defects. However, preclinical and clinical TETGs have been associated with chronic inflammation and macrophage infiltration. Macrophages express great phenotypic heterogeneity (generally characterized as classically activated [M1] vs. alternatively activated [M2]) and can influence tracheal repair and regeneration. We quantified and characterized infiltrating host macrophages using mouse microsurgical tracheal replacement models. Study design Translational research, animal model. Methods We assessed macrophage infiltration and phenotype in animals implanted with syngeneic tracheal grafts, synthetic TETGs, or partially decellularized tracheal scaffolds (DTSs). Results Macrophage infiltration was observed following tracheal replacement with syngeneic trachea. Both M1 and M2 macrophages were present in native trachea and increased during early tracheal repair (P = .014), with an M1/M2 ratio of 0.48 ± 0.15. In contrast, orthotopic implantation of synthetic TETGs resulted in a shift to M1 predominant macrophage phenotype with an increased M1/M2 ratio of 1.35 ± 0.41 by 6 weeks following implant (P = .035). Modulation of the synthetic scaffold with the addition of polyglycolic acid (PGA) resulted in a reduction of M1/M2 ratio due to an increase in M2 macrophages (P = .006). Using systemic macrophage depletion, the M1/M2 ratio reverted to native values in synthetic TETG recipients and was associated with an increase in graft epithelialization. Macrophage ratios seen in DTSs were similar to native values. Conclusions M1 and M2 macrophages are present during tracheal repair. Poor epithelialization with synthetic TETG is associated with an elevation of the M1/M2 ratio. Macrophage phenotype can be altered with scaffold composition and host-directed systemic therapies. DTSs exhibit M1/M2 ratios similar to those seen in native trachea and syngeneic tracheal replacement. Level of evidence NA Laryngoscope, 2021.

Taobao is a Chinese online shopping website, headquartered in Hangzhou, and owned by Alibaba. It is the world's biggest e-commerce website and the seventh most visited website according to Alexa. Taobao is the biggest consumer-to-consumer (C2C) e-commerce platform based in China. You can get clothes, accessories, gadgets and even computer hardware at very low prices. However, because the website is 100% in Chinese, this may be a barrier to those who want to shop but can’t make heads or tails navigating through the shopping process. Nowadays, Taobao has developed their business to international level. They start to provide international services to other countries other than China. Although the international services did provide convenience to people around the world, it did cause some inconvenience issues too. We are going to do research on those issues. The issues we found are in the area of language, logistic, scamming issues, purchasing issues and parcel tracking issues. For example, Taobao uses only chinese in their webpages, this makes those potential customers who can’t read the language cannot purchase things in Taobao. By doing this research, we manage to know how these issues affect the total sales of Taobao and how Taobao overcome these issues.

Background Thiopurine-induced leukopenia (TIL) is a life-threatening toxicity and occurs with a high frequency in the Asian population. Although nucleoside diphosphate-linked moiety X-type motif 15 (NUDT15) variants significantly improve the predictive sensitivity of TIL, more than 50% of cases of this toxicity cannot be predicted by this mutation. The potential use of the 6-thioguanine nucleotide (6TGN) level to predict TIL has been explored, but no decisive conclusion has been reached. Can we increase the predictive sensitivity based on 6TGN by subgrouping patients according to their NUDT15 R139C genotypes? Aim To determine the 6TGN cut-off levels after dividing patients into subgroups according to their NUDT15 R139C genotypes. Methods Patients' clinical and epidemiological characteristics were collected from medical records from July 2014 to February 2017. NUDT15 R139C, thiopurine S-methyltransferase, and 6TGN concentrations were measured. Results A total of 411 Crohn's disease patients were included. TIL was observed in 72 individuals with a median 6TGN level of 323.4 pmol/8 × 108 red blood cells (RBC), which was not different from that of patients without TIL (P = 0.071). Then, we compared the 6TGN levels based on NUDT15 R139C. For CC (n = 342) and CT (n = 65) genotypes, the median 6TGN level in patients with TIL was significantly higher than that in patients without (474.8 vs 306.0 pmol/8 × 108 RBC, P = 9.4 × 10-5; 291.7 vs 217.6 pmol/8 × 108 RBC, P = 0.039, respectively). The four TT carriers developed TIL, with a median 6TGN concentration of 135.8 pmol/8 × 108 RBC. The 6TGN cut-off levels were 411.5 and 319.2 pmol/8 × 108 RBC for the CC and CT groups, respectively. Conclusion The predictive sensitivity of TIL based on 6TGN is dramatically increased after subgrouping according to NUDT15 R139C genotypes. Applying 6TGN cut-off levels to adjust thiopurine therapies based on NUDT15 is strongly recommended.

Particle-resolved (PR) high-fidelity simulations, e.g., direct numerical simulation (DNS), have emerged as a powerful tool to precisely capture the full details of complex fluid-particle heat and mass transfer behaviors. The captured information can be used to constitute closures for unresolved conservation equations. However, such simulations are commonly performed under a specific variety of operating conditions. To broaden the range of closure model applicability, this fundamental study develops an enhanced correlation for the gas-particle transport rate in terms of Nusselt (Sherwood) number via collecting data points (e = [0.35, 1], Rep = [0, 550]) from open sources. The collected data are predicted with a mean relative error of 9.3%. The extended correlation is then systematically validated by comparison with experimental data and PR-DNS results. Finally, the correlation is applied to integrate with a macroscopic computational fluid dynamics (CFD) reactor model. Validation results reveal an enhanced improvement in mass and heat transfer predictions. Moreover, the overall thermal and reactive behaviors computed from the coupled reactor model achieve reasonably good accordance with PR-DNS predictions over various process conditions. The developed correlation is hopeful to improve the accuracy of coarse-grained simulation of interphase heat and mass transfer accompanied by heterogeneously catalyzed chemical reaction.

Multicloud access control is important for resource sharing and security interoperability across different clouds, and heterogeneity of access control policy is an important challenge for cloud mashups. XAC-ML is widely used in distributed environment as a declaratively fine-grained, attribute-based access control policy language, but the policy integration of XACML lacks formal description and theory foundation. Multicloud Access Control Policy Integration Framework (MACPIF) is proposed in the paper, which consists of Attribute-based Policy Evaluation Model (ABPEM), Four-value Logic with Completeness (FLC) and Four-value Logic based Policy Integration Operators (FLPIOs). ABPEM evaluates access control policy and extends XACML decision to four-value. According to policy decision set and policy integration characteristics, we construct FLC and define FLPIOs including Intersection, Union, Difference, Implication and Equivalence. We prove that MACPIF can achieve policy monotonicity, functional completeness, canonical suitability and canonical completeness. Analysis results show that this framework can meet the requirements of policy integration in Multicloud.

Historic cities, especially inhabited historic cities, are a special type of cultural heritage. Because of the expanding intension and extension of urban heritage, the rapid urbanization and the various stakeholders, the historic cities become much more complex nowadays. The need of GIS-based information systems for historic cities has never been greater. This paper introduces the research on the framework of the Smart Conservation Management System for the Historic City Fuzhou. It is an effort to explore an informatization way for historic cities. The needs of urban heritage itself, and the needs of different stakeholders should be respected. This system follows the principle of authenticity and integrity conservation, the coordination of conservation and sustainable development, the consideration of stakeholders, ease of use, extensibility, and security. The database should be fit for the construction of knowledge warehouse, be easy to collect and renew information. The module should be able to apply easily in everyday use situations, support smart decision making for the users. It is hoped that the research and the system will be referential for other historic cities.

BACKGROUND Human milk (HM) is the first choice for preterm infants, but exclusive HM feeding is inadequate for the growth of very preterm infants. The hypothesis of this trial is that infants fed according to an individualized fortification regimen will have higher protein intake and improved weight gain velocity (WGV). METHODS A prospective, randomized, controlled study was conducted. Infants

Organic light-emitting diodes (OLEDs) are attractive for display and lighting applications. However, the demand for high stability in outdoor display and lighting requires further material and device developments and theoretical modeling. Here an analytical function for predicting time-dependent luminance loss in OLEDs is derived based on excitonic defect generation and interaction. Despite the simplicity, this function fits extremely well vast amount of experimental data reported by numerous industrial and academic laboratories for a variety of devices including simple bilayer devices and multilayered devices using singlet, triplet, multiple emitters in variety of host:dopant combinations. The uniqueness of the derived function is expected to allow it to be broadly used for understanding root-cause in degrading devices and for modeling OLED lifetime.

Fiber supercapacitor (FSC) is a promising power source for wearable/stretchable electronics and high capacitive performance of FSCs is highly desirable for practice flexible applications. Here, we report a composite of manganese dioxide (MnO2) and activated carbon fibers (ACFs) with high MnO2 mass loading and microporous structure (abbreviated as MnO2@ACF), which is used as a fiber electrode to produce a FSC with a high capacitive performance and a good flexibility. The MnO2@ACF composite electrode in FSCs delivers an ultrahigh specific capacitance of 410 mF/cm2 at 0.1 mA/cm2, corresponding to a high energy density of 36 µWh/cm2 and high power density of 726 µW/cm2. Such high capacitive performance and simple fabrication method indicates that the MnO2@ACF composite is a very promising electrode material for flexible fiber supercapacitors.

In the field of organic photovoltaics (OPVs), outdoor stability research has lagged behind material development and device engineering. Testing protocols established at the International Summit of OPV Stability (ISOS) have stimulated some stability research, but these studies are almost exclusively limited to already-refined devices made with already-commercialized materials. If OPV materials were tested outdoors during small-scale stages, stability issues could be detected earlier in the development cycle. Chloro–(chloro)n–boron subnaphthalocyanine (Cl–ClnBsubNc) is a material with high OPV performance but has not previously been tested outdoors. An OPV power conversion efficiency of 8.4% has been previously demonstrated for a trilayer stack containing α-sexithiophene, Cl–ClnBsubNc, and chloro–boron subphthalocyanine (Cl–BsubPc). Building on the most advanced ISOS outdoor testing protocols (ISOS-O3), we assess the outdoor stability of small-scale bilayer and trilayer OPVs while establishing an improved s...

In this paper, we present a cell-based delay-locked loop (DLL) with an enhanced continuous tracking range. The main contribution is a novel delay line architecture called ping-pong delay line, making it highly resilient to process and temperature variation. In such a DLL design, two cell-based delay lines are incorporated in a way that they exchange their role of command dynamically like in a ping-pong game, and therefore the joint ping-pong delay line can react to severe environmental changes over a very wide range without disruption to the system's operation. The post-layout simulation using a 90-nm complimentary metal-oxide silicon (CMOS) process technology has demonstrated its advantages. A DLL using such a feature can operate reliably even under an extremely hostile environment when the supply voltage drops from 1 to 0.9 V within a timeframe of 4us.

We propose a dispersion flattened fiber (DFF) front-haul transmission system with high bitrate, polarization multiplexing (PM) and quadrature amplitude modulation (QAM) signal at low input optical power. The modulation format of the system is PM-16QAM, and the bitrate is 256 Gbit/s. The transmission characteristics over DFF link system are experimentally studied, which are compared with those over non-zero dispersion shifted fiber (NZDSF) link and standard single mode fiber (SSMF) link. The experimental results show that the error vector magnitude (EVM) of 256 Gbit/s and PM-16QAM signal over 25 km DFF link is 0.75% better than that over 25 km NZDSF link at least, and the bit error rate (BER) and Q-factor are much better than those of NZDSF. Their EVM and BER are both decreased with the increase of input optical power, and the Q-factor is increased. Those characteristics over 25 km SSMF are the worst at the same case. The larger the dispersion is, the more the constellation points are deviated from their respective centers and the worse the constellation characteristics are. The greater the attenuation of the DFF is, the smaller the input power of the DFF is, the more the constellation points are deviated from their centers and the worse the constellation characteristics are. This study provides a new idea and experimental support for long span front-haul propagation in mobile communication.

Magnesium (Mg) and silver (Ag) alloys are staple electrodes for organic light-emitting diodes (OLEDs). In this study, the Mg:Ag binary phase diagram is used to establish an electrode materials selection guide for both bottom- and top-emitting OLEDs. To achieve low turn-on voltage and high efficiency in bottom-emitting OLEDs, it is found that Mg:Ag cathodes must be selected from AgMg3 Mg phase region which provides the best figure of merits in low work function and high optical reflectance. For top-emitting OLEDs, however, Mg:Ag cathodes in the AgMg3 Mg region show large imaginary refractive index, and thus a stacked Mg:Ag/Ag is found essential to achieve optimal device performance. Furthermore, insertion of a thin LiF layer is found to create an effective charge injection cathode. In order to theoretically compute the devices’ optical characteristics, a database of complex optical constants of various materials including the metals is obtained by using a spectroscopic ellipsometer. This new database is found essential for accurate device optical design and engineering.