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Differential privacy (DP) has become the de facto standard of privacy protection. For graphs, there are two widely used definitions of differential privacy, namely, edge differential privacy (edge-DP) and node differential privacy (node-DP), and node-DP is preferred when the minimal unit of interest is a node. To preserve node-DP, one can develop different methods to answer each specific graph query, or develop a graph publishing method to answer all graph queries. However, no existing works worked on such graph publishing methods. In this work, we propose two methods for publishing graphs under node-DP. One is the node-level perturbation algorithm which modifies the input graph by randomly inserting and removing nodes. The other one is the edge-level perturbation algorithm which randomly removing edges and inserting nodes. Both methods can achieve a flexible privacy guarantee by adjusting the running parameters. We conduct extensive experiments on both real-world and synthetic graphs to show the effectiveness and efficiency of proposed algorithms.

The demand for apparel/fashion products is usually of heavy weather-related uncertainty, which can be solved by the publicly accessible weather information provided by the government. That is because weather information provides a more accurate demand signal, and the key weather indicators fashion brand, the latter determines the wholesale price but usually postpones the price decision to observe the weather information. Alternatively, the small retailer can outsource procurement to a powerful agent, who fixes the fashion brand's wholesale price. In this article, we investigate an apparel supply chain consisting of two competing small retailers (retailers 1 and 2), a powerful procurement agent, and a famous fashion brand. Given retailer 2's procurement outsourcing, retailer 1 decides whether to outsource procurement to the agent or directly procure products from the fashion brand. We identify cooperation and competition relationships in the retailers’ ordering decisions based on the weather information. The different intensities of the cooperation/competition relationships alter retailer 1's preferences of procurement outsourcing because of the mitigated/intensified quantity competition. Interestingly, we show that, when demand uncertainty is high, retailer 1's procurement outsourcing strategy will switch from Turnkey to Consignment and back to Turnkey, as its demand becomes more sensitive to the weather condition.

With the prevalence of voice devices in our daily life, speech data is accumulated at an unprecedented speed. The vast amount of speech data form an invaluable database for security surveillance and financial risk management. However, the speeches collected from different sources are not necessarily annotated with regard to the speaker identity, making the task of retrieving all the speech records for a given identity extremely challenging. In this paper, we propose a scalable system for Identity-Oriented Speech Retrieval (IO-SR), which seamlessly integrates speaker modeling and deep indexing techniques. Given a speech snippet and a speech database, IO-SR efficiently retrieves all speech snippets that are uttered by the same speaker as the given one. Evaluations on an industrial dataset containing millions of speech snippets show that our system achieves superior performance compared with the state-of-the-arts.

To ensure the security of images outsourced to the malicious cloud without affecting searchability on such outsourced (typically encrypted) images, one could use privacy-preserving Content-Based Image Retrieval (CBIR) primitive. However, conventional privacy-preserving CBIR schemes based on Searchable Symmetric Encryption (SSE) are not capable of supporting efficient fine-grained access control and result verification simultaneously. Therefore, in this paper, we propose a Verifiable Fine-grained encrypted Image Retrieval scheme in the Multi-owner multi-user settings (VFIRM). VFIRM first utilizes a novel polynomial-based access strategy to provide efficient fine-grained access control. Then, it employs the dual secure k-nearest neighbor technique to distribute distinct keys to different data owners and data users, and finally implements an adapted homomorphic MAC technique to check the correctness of search results. Our formal security analysis shows that VFIRM is non-adaptive semantic secure if the clients search key is generated randomly and keeps in secret. Our empirical experiments using two real-world datasets (i.e., Caltech101 and Corel5k) demonstrate the practicality of VFIRM.

Ranked keyword search has gained increasing attention due to its attractive advantages such as flexibility and accessibility. However, most existing ranked keyword search schemes ignore the semantic associations between the documents and queries. To solve this challenging issue in cloud-assisted edge computing, we first design the Semantic-aware Ranked Multi-keyword \textbf{S}earch (SRMS) scheme by adopting the Latent Dirichlet Allocation (LDA) topic model and the Chinese Remainder Theorem (CRT)-based secret sharing mechanism. Considering that the cloud server may be malicious, we implement a basic verification mechanism in SRMS to verify the correctness and completeness of search results and extend this verification mechanism in cloud-assisted edge computing scenarios. Formal security analysis proves that SRMS and extended result verification mechanisms are secure in both the known ciphertext model and the known background model. Extensive experiments using the real-world dataset demonstrate that SRMS is efficient and feasible in practical applications.

Event popularity prediction over social media is crucial for estimating information propagation scope, decision making, and emergency prevention. However, existing approaches only focus on predicting the occurrences of single attribute such as a message, a hashtag or an image, which are not comprehensive enough for representing complex social event propagation. In this paper, we predict the event popularity, where an event is described as a set of messages containing multiple hashtags. We propose a novel hashtag-influence-based event popularity prediction by mining the impact of an influential hashtag set on the event propagation. Specifically, we first propose a hashtag-influence-based cascade model to select the influential hashtags over an event hashtag graph built by the pairwise hashtag similarity and the topic distribution of event-related hashtags. A novel measurement is proposed to identify the hashtag influence of an event over its content and social impacts. A hashtag correlation-based algorithm is proposed to optimize the seed selection in a greedy manner. Then, we propose an event-fitting boosting model to predict the event popularity by embedding the feature importance over events into the XGBOOST model. Moreover, we propose an event-structure-based method, which incrementally updates the prediction model over social streams. We have conducted extensive experiments to prove the effectiveness and efficiency of the proposed approach.

Uncertain data has been emerged as an important problem in database systems due to the imprecise nature of many applications. To handle the uncertainty, probabilistic databases can be used to store uncertain data, and querying facilities are provided to yield answers with confidence. However, the uncertainty may propagate, hence the results from a query or mining process may not be useful. In this paper, we leverage the power of crowdsourcing by designing a set of Human Intelligence Tasks (HITs) to ask a crowd with diverse accuracy rates, to improve the quality of uncertain data. Each HIT is associated with a cost, thus, we need to design solutions to maximize the data quality with minimal number of HITs. There are two obstacles for this non-trivial optimization, which lead to very high computational cost for selecting the optimal set of HITs. First, members of a crowd may return incorrect answers with different probabilities. Second, the HITs decomposed from uncertain data are often correlated. We have addressed these challenges in this paper by designing an effective approximation algorithm and an efficient heuristic solution, even under diverse individual accuracy rates of the crowdsourcing workers.

Different from typical circuit breakers, breakers used to switch AC filters in convertor stations have to operate frequently according to the real-time operation mode and daily load changes. Therefore, the performance of filter breakers decreases very quickly, which leads to frequent accidents. Both preinsertion resistors and controlled switching devices can suppress switching transients. In this paper, a comparative analysis of whether a controlled switching device and preinsertion resistor should be adopted is carried out using PSCAD. The transient is calculated as the combined result of the switching angle and preinsertion resistor value, and the optimal configurations are proposed. After determining the resistor value and whether a controlled switching device should be included, the reference voltage of the arrester should be reevaluated.

Vehicular Ad-Hoc Networks (VANETs) play an ever-increasing important role in improving traffic management and enhancing driving safety. However, vehicular communication using a wireless channel faces security and privacy challenges. The Conditional Privacy-Preserving Authentication (CPPA) scheme is suitable for solving the above challenges, but the existing identity-based CPPA schemes suffer from inborn key escrow issues. Motivated by this, we propose a lightweight CPPA scheme based on elliptic curve cryptography to solve the above issues, in which the pseudonym and public/private key pair of the vehicle is generated by itself, so that the proposed scheme avoids the key escrow issue. Furthermore, to achieve efficient vehicular communication, a CPPA scheme is proposed using a fog computing model that supports mobility, low latency, and location awareness. The pseudonym of the vehicle is generated by two hash chains in the proposed scheme, so that the storage overhead can be reduced efficiently under the condition that backward security is guaranteed. Security analysis shows that the scheme is secure under the random oracle and satisfies the security requirements of VANETs. Performance evaluation demonstrates that the proposed scheme outperforms related schemes in terms of computational and communication overhead.

Aristolochic acids (AAs) have long been considered as a potent carcinogen due to its nephrotoxicity. Aristolochic acid I (AAI) reacts with DNA to form covalent aristolactam (AL)–DNA adducts, leading to subsequent A to T transversion mutation, commonly referred as AA mutational signature. Previous research inferred that AAs were widely implicated in liver cancer throughout Asia. In this study, we explored whether AAs exposure was the main cause of liver cancer in the context of HBV infection in mainland China. Totally 1256 liver cancer samples were randomly retrieved from 3 medical centers and a refined bioanalytical method was used to detect AAI–DNA adducts. 5.10% of these samples could be identified as AAI positive exposure. Whole genome sequencing suggested 8.41% of 107 liver cancer patients exhibited the dominant AA mutational signature, indicating a relatively low overall AAI exposure rate. In animal models, long-term administration of AAI barely increased liver tumorigenesis in adult mice, opposite from its tumor-inducing role when subjected to infant mice. Furthermore, AAI induced dose-dependent accumulation of AA–DNA adduct in target organs in adult mice, with the most detected in kidney instead of liver. Taken together, our data indicate that AA exposure was not the major threat of liver cancer in adulthood.

Objectives To map travel policies implemented due to COVID-19 during 2020, and conduct a mixed-methods systematic review of health effects of such policies, and related contextual factors. Design Policy mapping and systematic review. Data sources and Eligibility Criteria for the policy mapping, we searched websites of relevant government bodies and used data from the Oxford COVID-19 Government Response Tracker for a convenient sample of 31 countries across different regions. For the systematic review, we searched Medline (Ovid), PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and COVID-19 specific databases. We included randomized controlled trial, non-randomized studies, modeling studies, and qualitative studies. Two independent reviewers selected studies, abstracted data and assessed risk of bias. Results Most countries adopted a total border closure at the start of the pandemic. For the remainder of the year, partial border closure banning arrivals from some countries or regions was the most widely adopted measure, followed by mandatory quarantine and screening of travelers. The systematic search identified 69 eligible studies, including 50 modeling studies. Both observational and modeling evidence suggest that border closure may reduce the number of COVID-19 cases, disease spread across countries and between regions, and slow the progression of the outbreak. These effects are likely to be enhanced when implemented early, and when combined with measures reducing transmission rates in the community. Quarantine of travelers may decrease the number of COVID-19 cases but its effectiveness depends on compliance and enforcement and is more effective if followed by testing, especially when less than 14 day-quarantine is considered. Screening at departure and/or arrival is unlikely to detect a large proportion of cases or to delay an outbreak. Effectiveness of screening may be improved with increased sensitivity of screening tests, awareness of travelers, asymptomatic screening, and exit screening at country source. While four studies on contextual evidence found that the majority of the public is supportive of travel restrictions, they uncovered concerns about the unintended harms of those policies. Conclusion Most countries adopted full or partial border closure in response to COVID-19 in 2020. Evidence suggests positive effects on controlling the COVID-19 pandemic for border closure (particularly when implemented early), as well as quarantine of travelers (particularly with higher levels of compliance). While these positive effects are enhanced when implemented in combination with other public health measures, they are associated with concerns by the public regarding some unintended effects.

Functional non-HLA antibodies (antibodies to non-human leukocyte antigens) targeting the G protein-coupled receptors angiotensin II type 1 receptor (AT1R) and endothelin-1 type A receptor (ETAR) are implicated in the pathogenesis of transplant vasculopathy. While ERK signaling (a regulator of cell growth) may represent a general cellular response to agonist stimulation, the molecular link between receptor stimulation and development of vascular obliteration has not been fully established. Here we hypothesize involvement of the versatile adaptor proteins, β-arrestins, and the major regulator of cell growth, PI3K/mTOR signaling, in impaired endothelial repair. To test this, human microvascular endothelial cells were treated with AT1R-/ETAR-antibodies isolated from patients with kidney transplant vasculopathy. These antibodies activated both mTOR complexes via AT1R and ETAR in a PI3K-dependent and ERK-independent manner. The mTOR inhibitor, rapamycin, completely abolished activation of mTORC1 and mTORC2 after long term treatment with receptor antibodies. Imaging studies revealed that β2- but not β1-arrestin was recruited to ETAR in response to ET1 and patient antibodies but not with antibodies isolated from healthy individuals. Silencing of β2-arrestin by siRNA transfection significantly reduced ERK1/2 and mTORC2 activation. Non-HLA antibodies impaired endothelial repair by AT1R and ETAR-induced mTORC2 signaling. Thus, we provide evidence that functional AT1R-/ETAR antibodies induce ERK1/2 and mTOR signaling involving β2-arrestin in human microvascular endothelium. Hence, our data may provide a translational rational for mTOR inhibitors in combination with receptor blockers in patients with non-HLA receptor recognizing antibodies.

In order to effectively recognize and identify liquor quality by nuclear magnetic resonance (NMR) spectrum data, we propose a hybrid data processing and recognition algorithm. In this algorithm Kernel principal component analysis (KPCA) was used to remove the correlation and reduce dimension of the NMR spectrum, and then convolutional neural network (CNN) was used for classification and identification of the processed spectrum. The compared experiment result show that the proposed KPCA+CNN method can obtain higher accuracy than CNN and PCA+CNN methods based on the NMR spectrum. The KPCA+CNN algorithm has good application prospect and reference value.

Background Loncastuximab tesirine has shown antitumor activity with an acceptable toxicity profile in patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL) who were relapsed or refractory after ≥2 prior therapies, including activity in patients with high-risk disease characteristics. This analysis examined health-related quality of life (HRQoL), symptoms, and tolerability in patients receiving loncastuximab tesirine for relapsed or refractory DLBCL. Patients and Methods The single-arm, open-label phase II LOTIS-2 study (ADCT-402-201; NCT03589469) enrolled 145 patients aged ≥18 years. Patients received loncastuximab tesirine as a 30-minute intravenous infusion on day 1 of each 3-week treatment cycle. Patient-reported outcomes were measured using EQ-5D and FACT-Lym at baseline, day 1 of each cycle, and the end-of-treatment visit. Results During the course of treatment, EQ VAS overall health score was improved over time. The adjusted improvement was 0.65 per cycle (95% CI, 0.26-1.04; P = .001), and the adjusted mean change from baseline score was 5.00 (95% CI, 1.75-8.25; P = .003) at cycle 9, day 1. FACT-Lym total scores remained stable during treatment. More patients reported improvement compared to baseline in pain, lumps/swelling, and losing weight for a majority of visits. More than 60% of patients reported being "not at all" or "a little bit" bothered by treatment side effects for all treatment visits. Findings in elderly patients were similar to the population as whole. Conclusion The findings on HRQoL, symptoms, and tolerability further support the clinical use of loncastuximab tesirine for the treatment of relapsed or refractory DLBCL. Funding This work was funded by ADC Therapeutics SA. Authors affiliated with ADC Therapeutics SA participated in designing the study; in collecting, analyzing, and interpreting the data; in writing the report; and in the decision to submit the article for publication.

With superb device characteristics, gallium nitride (GaN) power transistors facilitate fast and efficient power conversion and delivery in modern power circuits. To take full advantage of these devices, high switching frequency ( $f_{{SW}})$ operation is highly desirable. However, the lack of GaN compatible high-speed, efficient, and reliable gate drivers has been a formidable design hindrance. In this article, we address three critical design challenges faced in GaN power gate driving, namely bootstrap (BST) level-shifting, switching slew rate (SR) control, and active deadtime $t_{{dead}}$ control. We first propose a BST dynamic level-shifting technique to enable sub-nanosecond $t_{{delay}}$ at high $f_{{SW}}$ . Meanwhile, a dual-SR switching technique is introduced to retain both low switching power and noise. Compared with traditional constant $t_{{dead}}$ controls, the $t_{{dead}}s$ in this design are regulated actively for high efficiency. To validate these techniques, a four-phase GaN-based switching power converter was designed and implemented on a 0.35 μm high-voltage (HV) BCD process. At a $f_{{SW}}$ of 20 MHz and a $V_{{IN}}$ of 20 V, it delivers a maximum power of 8.4 W and a peak efficiency of 84.9%. The gate drivers are fully integrated including all BST capacitors and active BST switches. It achieves regulated rise and fall $t_{{dead}}s$ of 3.2 and 4.7 ns, respectively, for a load range from 50 mA to 1.2 A. The gate switching rise time $t_{R}$ is reduced to 1 ns with a maximum switching SR of 48 V/ns. The converter employs a HV synchronized hysteretic control, which works with the proposed gate drivers seamlessly to demonstrate a dynamic voltage scaling (DVS) Vo up- and down-tracking speeds of 0.33 μs/V and 0.47 μs/V, respectively.

This paper investigates the asymmetric temperature distribution of a modular permanent-magnet (PM) synchronous in-wheel motor under fault conditions, and based on this, proposes a fault-tolerant (FT) strategy named minimum temperature difference strategy (MTDS) to avoid the high temperature appearing at local winding. Firstly, the modular motor system and the fault-tolerant principle are introduced, and the reconfiguring fundamental magneto motive force (MMF) under open-circuit of one phase in one module is deduced. Secondly, the loss and temperature distributions of the motor with normal operation are analyzed by the coupled electromagnetic-thermal method. And the mutual verification between simulation and experiment are adopted to separate the copper losses, iron losses and PM losses from total losses. Furthermore, the asymmetric temperature distributions of the motor operating with part of modules are analyzed in detail. Finally, the influence of the faulty windings on the temperature of healthy windings is investigated, and the fault-tolerant strategy of MTDS is proposed. The asymmetric temperature distributions of the motor under various fault-tolerant strategies are compared. The result shows that the MTDS can significantly reduce the maximum temperature of the windings and make the winding temperature distribution more uniform.

A novel reflectarray (RA) with ultra-low-profile and 2-bit phase quantization beam-steering ability is presented in this paper. To reduce the profile, a Leaky-wave feed is used to excite the RA with enhanced illumination efficiency. Moreover, simultaneous sum and difference patterns are also obtained to provide beam flexibility. The entire thickness of the proposed RA is less than 3% of that of the conventional front-fed RA with the same aperture. To increase the efficiency of the RA, a novel unit cell consisting of a polarizer layer and a reflection layer is developed, which is configured to provide polarization rotation and 2-bit phase shifts by using a hybrid of tunable polarization and discrete resonator. The operation principle, theoretical explanation, and implementation of the proposed antenna are elaborated in this work. To prove the design concept and beam scanning performance, an array with 9×7 unit cells operating at Ka-band is designed and simulated firstly. 2-D beam scanning within the range of ±30° has been verified. Then, a passive prototype with 9×67 unit cells is designed, fabricated and measured. Experimental results show aperture efficiency of 35.1% and illumination efficiency of 43.4%. The developed RA is scalable, and it provides a viable low-cost solution to develop low-profile, high-gain and beam-steering array antennas for satellite applications.

Agricultural disease image recognition has an important role to play in the field of intelligent agriculture. Some advanced machine learning methods associated with the development of artificial intelligence technology in recent years, such as deep learning and transfer learning, have begun to be used for the recognition of agricultural diseases. However, the adoption of these methods continues to face a number of important challenges. This paper looks specifically at deep learning and transfer learning and discusses the recent progress in the use of these advanced technologies for agricultural disease image recognition. Analysis and comparison of these two methods reveals that current agricultural disease data resources make transfer learning the better option. The paper then examines the core issues that require further study for research in this domain to continue to progress, such as the construction of image datasets, the selection of big data auxiliary domains and the optimization of the transfer learning method. Creating image datasets obtained under actual cultivation conditions is found to be especially important for the development of practically viable agricultural disease image recognition systems.

Rice is one of the most important food crops in the world. Weeds seriously affect the rice yield and grain quality. In recent years, there are tremendous progresses in the research and application of herbicide-resistant genes in rice worldwide. This article reviews the working mechanisms of six herbicides (glyphosate, glufosinate, acetolactate synthase inhibitor herbicides, acetyl-CoA carboxylase inhibitor herbicides, hydroxyhenylpyruvate dioxygenase (HPPD) inhibitor herbicides and dinitroaniline herbicides), the resistance mutations of the corresponding herbicide-target genes, and the herbicide detoxification mechanisms by non-target genes. Examples are provided on herbicide-resistant rice materials obtained by transformation of exogenous resistance genes, by artificial mutagenesis and mutant screening, and by modifying the target genes through gene editing. This paper also introduces the current application of herbicide-resistant rice, points out problems that may be caused by utilization of herbicide resistant rice and solutions to the problems, and discusses the future prospects for the development of herbicide-resistant rice.

Extremely high sensitivity is the long-time pursing goal for the surface plasmon resonance (SPR) sensor, which means the capability to detect analytes with lower concentrations or interactions for smaller biomolecules. It was suggested that a flat dispersion for the plasmon material enables to enhance the sensitivity dramatically. However, the regulation ability of inherent dispersion in natural materials is limited. With the appearance of hyperbolic metamaterials (HMMs), the management of the plasmon materials dispersion becomes possible. In this paper, the HMMs with metal/dielectric multilayer structure are proposed to construct the SPR sensors. Through numerical simulations and theoretical analysis, we find that the flat dispersion in the HMM structure could significantly benefit the sensitivity improvement for HMM-SPR sensors. As a result, the proposed HMM-SPR sensor obtains an ultrahigh sensitivity of 34.00 m/RIU in the experiment, which is one order higher in magnitude than that of the conventional monolayer metallic SPR sensors. Thus, this research shows insight into understanding the dependence of the HMM-SPR sensitivity on dispersion management and provides a practical methodology to develop extremely high-sensitivity SPR sensors based on artificial plasmon materials.

Robotic gastrectomy (RG) shows potential as an alternative to open gastrectomy (OG), the gold standard in the surgical management of gastric cancer (GC). This meta-analysis was conducted to compare the short-term efficacy and safety of RG versus OG for GC.A systematic literature search was conducted on RG with OG for GC in randomized and semi-randomized controlled trials and observational studies. Published materials and conference papers in English and trace references included in the literature were manually searched. The retrieval period was set to end in February 2021. The quality of the included studies was evaluated, and meta-analysis was conducted using the software STATA 15.1. Eleven studies with 6693 patients were included. Major blood loss (weighted mean differences (WMD) = -114.63, 95 % CI, −182.37–46.88, P = 0.001), hospital stay (WMD = -2.21, 95 % CI, −4.32–0.09, P = 0.041), and postoperative complications (odds ratio (OR) = OR = 0.57, 95 % CI, 0.35–0.93, P = 0.025) were fewer in the RS group, and R0 resection (odds ratio (OR) = 6.26, 95 % CI, 2.733–14.35, P = 0.000) occurred more frequently in the RG group than in the OG group. But positive lymph nodes (WMD = −2.09, 95 % CI,-3.73–0.45, P = 0.012) occurred less frequently in the RG group than in the OG group, and operative time was longer in the RG group than in the OG group (WMD = 83.21, 95 % CI, 19.88–146.55, P = 0.010). RG not only provides a technique for the treatment of GC but is also safe and feasible. This finding needs to be verified by multicenter, large-sample randomized controlled trials in the future.

Unexpected geologic heterogeneities in tunnel lines often cause safety issues and economic losses during excavation using tunnel boring machines (TBMs). Therefore, collecting geologic information ahead of the excavation front is important to prevent geologic disasters and ensure excavation safety. To predict the geologic conditions ahead of the TBM-excavated tunnel in the water supply project at the Songhua River in China, the tunnel-seismic-while-drilling (TSWD) method was adjusted and then applied. First, common-source gather data were acquired to record TBM drilling noise (pilot signal and seismic waves); a processing approach (including normalization, crosscorrelation, wavefield separation, and migration) was used to image the major relevant geologic heterogeneities ahead of the excavation front. A synthetic study from a numerical model with a fault verified the feasibility of the modified TSWD method to identify and image geologic interfaces. Then, this method was applied to field data resulting from a TBM tunnel excavation project. The field test of the modified TSWD in the TBM tunnel revealed fractured zones, fault boundaries, and a preexcavated tunnel ahead, providing the required geologic information for TBM tunneling and preventing geologically-caused safety issues.

Background: 5-Hydroxymethylcytosine (5hmC) is an epigenetic DNA modification that is highly abundant in nervous system. It has been reported that 5hmC is significant associated with Alzheimer’s disease (AD). Changes in 5hmC signatures can be detected in circulating cell-free DNA (cfDNA), which has shown potential as a non-invasive liquid biopsy material. However, there is no research about genome-wide profiling of 5hmC in cfDNA and its potential for the diagnosis of AD to date. Methods: We carried out a case-control study and used a highly sensitive and selective high-throughput sequencing of chemical labels to detect the genome-wide profiles of 5hmC in human cfDNA and identified differentially hydroxymethylated regions (DhMRs) in AD patients and the control. Results: We detected a significant difference of 5hmC enrichment in gene bodies which were linked to multiple AD pathogenesis-associated signaling pathways in AD patients compared with cognitively normal controls. AD patients can be well distinguished from cognitively normal controls by differentially hydroxymethylated regions (DhMRs) in cfDNA. Specially, we found 7 distinct genes (RABEP1, CPNE4, DNAJC15, REEP3, ROR1, CAMK1D, and RBFOX1) had prediction diagnostic potential based on their significant correlations with MMSE and MoCA scores. Conclusions: The present results suggest that 5hmC markers derived from plasma cfDNA can be served as an effective, minimally invasive biomarkers for clinical auxiliary diagnosis of late-onset AD. Trial registration: Chinese Clinical Trial Registry, ChiCTR2100042537, registered 13 January 2021-retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=120582.

Background: Drug repositioning is a new research area in drug development. It aims to discover novel therapeutic uses of existing drugs. It could accelerate the process of designing novel drugs for some diseases and considerably decrease the cost. The traditional method to determine novel therapeutic uses of an existing drug is quite laborious. It is alternative to design computational methods to overcome such defect. Objective: This study aims to propose a novel model for the identification of drug–disease associations. Method: Twelve drug networks and three disease networks were built, which were fed into a powerful network-embedding algorithm called Mashup to produce informative drug and disease features. These features were combined to represent each drug–disease association. Classic classification algorithm, random forest, was used to build the model. Results: Tenfold cross-validation results indicated that the MCC, AUROC, and AUPR were 0.7156, 0.9280, and 0.9191, respectively. Conclusion: The proposed model showed good performance. Some tests indicated that a small dimension of drug features and a large dimension of disease features were beneficial for constructing the model. Moreover, the model was quite robust even if some drug or disease properties were not available.

Extracting the flying airplane from the satellite video has received a great deal of attention in remote sensing applications. Nevertheless, the challenge arises in two aspects: the limited spatial resolution of space-borne imaging devices, and the small size of the airplane with low contrast to the background. This paper presents a novel spatially accurate and temporally consistent model for the foreground airplane extraction. Specifically, each frame is decomposed as a linear combination of the airplane and background with a kind of mixture ratios. This enables more accurate spatial representation of the small airplane of low resolution. Then, the airplanes from different frames obey the common mixture ratios based on the sub-pixel motion estimation. This enables the temporally consistent extraction through frames. The effectiveness of our method is demonstrated by the qualitative and quantitative evaluation on both synthetic and real data.

Background/Aims: Anti-phospholipase A2 receptor (PLA2R) autoantibody is the main biomarker of idiopathic membranous nephropathy (IMN). We aimed to find a new cutoff value of anti-PLA2R for patients with IMN and to explore the relevance between this antibody and baseline clinical parameters.Methods: A total of 670 subjects including 374 IMN cases and 296 non-IMN controls were included between January 2017 and January 2020. All clinical parameters were collected at the time of renal biopsy. The levels of anti-PLA2R were detected by a commercial enzyme-linked immunosorbent assay (ELISA) kit. The optimal cutoff value was calculated by a receiver operating characteristic curve and compared in diagnostic efficiency.Results: The optimal cutoff value of anti-PLA2R for IMN was 7.45 RU/mL with the highest Youden index, and the corresponding sensitivity, specificity, positive predictive value and negative predictive value were 80.75%, 97.97%, 98.05% and 80.11%, respectively. Anti-PLA2R levels in IMN patients demonstrated a significant positive correlation with serum creatinine and 24-hour urinary protein, while they showed a negative correlation with serum albumin and estimated glomerular filtration rate.Conclusions: The recommended cutoff value of anti-PLA2R is 7.45 RU/mL using ELISA detection for distinguishing IMN from non-IMN nephropathy. The level of anti-PLA2R is related to baseline renal function in IMN. This new threshold can improve the diagnostic efficiency and facilitate early diagnosis of IMN.

Although lithium-ion batteries (LIBs) have many advantages, they cannot satisfy the demands of numerous large energy storage industries owing to their high cost, low security, and low resource richness. Aqueous zinc-ion batteries (ZIBs) with low cost, high safety, and high synergistic efficiency have attracted an increasing amount of attention and are considered a promising choice to replace LIBs. However, the existing cathode materials for ZIBs have many shortcomings, such as poor electron and zinc ion conductivity and complex energy storage mechanisms. Thus, it is crucial to identify a cathode material with a stable structure, substantial limit, and suitability for ZIBs. In this review, several typical cathode materials for ZIBs employed in recent years and their detailed energy storage mechanisms are summarized, and various methods to enhance the electrochemical properties of ZIBs are briefly introduced. Finally, the existing problems and expected development directions of ZIBs are discussed.

Numerical precipitation prediction plays a crucial role in weather forecasting and has broad applications in public services including aviation management and urban disaster early warning systems. However, Numerical Weather Prediction (NWP) models are often constrained by a systematic bias due to coarse spatial resolution, lack of parametrizations and limitations of observation and conventional meteorological models, including constrained sample size and long-tail distribution. To address these issues, we present a data-driven deep learning model, named the Ordinal Distribution Autoencoder (ODA), which principally includes a Precipitation Confidence Network and a combinatorial network that contains two blocks, i.e., a Denoising Autoencoder block and an Ordinal Distribution Regression block. As an expert-free model for bias correction of precipitation, it can effectively correct numerical precipitation prediction based on meteorological data from the European Centre for Medium- Range Weather Forecasts (ECMWF) and SMS-WARMS, an NWP model used in East China. Experiments in the two NWP models demonstrate that, compared with several classical machine learning algorithms and deep learning models, our proposed ODA generally performs better in bias correction.

The semi-global matching (SGM) algorithm in stereo vision is a well-known depth-estimation method since it can generate dense and robust disparity maps. However, the real-time processing and low power dissipation, the specifications of the Internet-of-Thing (IoT) applications, are challenging for their computational complexity. In this paper, we propose a hardware-oriented SGM algorithm with pixel-level pipeline and region-optimized cost aggregation for high-speed processing and low hardware-resource usage. Firstly, the matching costs in a region are integrated with an optimization strategy to significantly reduce memory usage and improve the processing speed of the cost aggregation. Then, a two-layer parallel two-stage pipeline (TPTP) architecture, which enables pixel-level processing, is designed to calculate two directions (0° and 135°) aggregation to further solve the crucial computational bottleneck of the SGM algorithm. Finally, the architecture is demonstrated on a low-cost XILINX Spartan-7 device and an advanced Stratix-V FPGA device for VGA (640x 480) depth estimation. The experimental results show that the proposed architecture with compact hardware architecture also ensures accuracy. The pixel-level pipeline architecture enables a processing speed of 355 frames per second (fps) at 109MHz on the Spartan-7 FPGA device and 508 fps at 156MHz on the Stratix-V FPGA. Besides, the coprocessor respectively achieves an energy efficiency of 4.74 nJ/pixel with a power dissipation of 517mW and 4.29nJ/pixel with a power dissipation of 669mW on these two FPGAs.

A single-polarization fiber is an important device in many applications ranging from communications to sensors. However, most of the single-polarization fibers focus on linear polarization, and the single-polarization fiber supporting a circular polarization remains a challenge. Here, we propose a novel wavelength-tunable single-circular-polarization (SCP) twisted photonic crystal fiber (PCF). The single left-circular polarization and single right-circular polarization operate around $1.665 ~\mu \text{m}$ and $1.700 ~\mu \text{m}$ , respectively. The resonance can be tuned by adjusting the twist rate of PCF and the refractive index filling. The SCP bandwidth is up to 20 nm, and the polarization extinction ratio is as high as 1.3 dB/cm. This design not only extends the single-polarization fiber to circular polarization but also provides a twisting PCF application.

Background. Transarterial chemoembolization (TACE) combined with sorafenib (TACE-S) or apatinib (TACE-A) is used in the treatment of hepatocellular carcinoma (HCC). However, to date, no study has compared the efficacy and safety of both treatments. The objective of this study was to compare the efficacy and safety of patients with advanced HCC who received either TACE-S or TACE-A. Methods. 193 patients with advanced HCC were included in the study between June 2015 and December 2019. Propensity score matching (PSM) analysis was used in the study to reduce selection bias. Results. Before PSM, the median overall survival (mOS) and median progression-free survival (mPFS) of patients treated with TACE-S were not significantly longer than in patients treated with TACE-A ( P = 0.703 , P = 0.514 ). TACE-A did not increase the mortality risk compared with TACE-S in the first 12 months (HR: 1.255, 95%CI: 0.796–1.978, P = 0.329 ) or after the 12-month mark (HR: 0.832, 95%CI: 0.482–1.436, p = 0.508 ). Similarly, TACE-A did not increase the tumor recurrence risk relative to TACE-S in the first 12 months (HR: 1.054, 95%CI: 0.744–1.493, P = 0.767 ) or after the 12-month mark (HR: 1.730, 95%CI: 0.592–5.049, P = 0.316 ). The subgroups analysis showed that TACE-A did not increase mortality risk or tumor recurrence risk relative to TACE-S. After PSM, similar results were presented. The III and IV stage adverse events in the TACE-A group were similar to those in the TACE-S group before PSM. Conclusions. Patients with advanced hepatocellular carcinoma could get similar survival benefits from treatment with either transarterial chemoembolization plus apatinib or transarterial chemoembolization plus sorafenib.

BACKGROUND Sarcopenia and cachexia are two predictors of adverse clinical outcomes, but they are partly overlapping. We aimed to compare the characteristics and prognostic value of cachexia and sarcopenia in patients after gastrectomy. METHODS From 2014 to 2019, a total of 1215 gastric cancer patients were enrolled. Cachexia and sarcopenia were diagnosed according to the most recent consensus definitions. Baseline characteristics and clinical outcomes were compared between the two groups. Risk factors of survival were evaluated by Cox regression analysis. RESULTS Of all patients, 26.5% were diagnosed with cachexia and 19.8% were diagnosed with sarcopenia. Sarcopenia was more prevalent in elderly patients, while cachexia was prone to occur in patients with TMN stage III. Survival curves showed that sarcopenia had adverse effects in patients with TMN stage I and II-III, while cachexia was only associated with poor survival at stages II-III. For the entire cohort, both cachexia and sarcopenia were adverse factors for prognosis. However, for stage I patients, sarcopenia was an independent predictor for overall survival (OS) (HR = 4.939, P < 0.001) and disease-free survival (DFS) (HR = 4.256, P < 0.001), but not cachexia; for stage II-III patients, cachexia was an independent predictor for OS (HR = 1.538, P < 0.001) and DFS (HR = 1.473, P = 0.001), but not sarcopenia. CONCLUSIONS Sarcopenia and cachexia have different clinical characteristics and prognostic values. For patients with early stage gastric cancer, detection for sarcopenia was more meaningful than cachexia. However, the prognostic significance of cachexia exceeded sarcopenia in advanced cancer.

There has been a growing number of oncology drug approvals. Non-interventional postauthorization safety/effectives studies (PASSs/PAESs) aim to provide real-world evidence on the safety/effectiveness of oncology drugs postapproval. To understand the current landscape, a comprehensive search as of March 1, 2021, was conducted in major register/databases. We found that requested studies increased from 1 in 2006-2010 to 47 in 2016-2020. Of 78 total studies identified, 50 focused on safety/risk assessment (64.1%), 6 on effectiveness (7.7%), 3 on drug utilization (3.8%), 1 on disease epidemiology (1.3%), and 18 on effectiveness of additional risk minimization measures (23.1%). For safety/risk assessment studies, 58.9% focused on nonspecific end points (e.g., frequency of adverse events). For effectiveness studies, the leading primary outcome was overall survival. Overall, safety/risk assessment studies concerning nonspecific end points for vascular endothelial growth factor (receptor) inhibitors were most requested. Regarding data sources, though a majority (71.8%) used primary data collection, a growing proportion utilized secondary data sources. Among 23 studies with information available on study design, 10 (43.5%) were single-arm cohort studies, 9 (39.1%) were cross-sectional studies, 3 (13.1%) were comparative cohort studies, and 1 (4.3%) was a nested-case-control study. In conclusion, there was an increasing number of oncology-specific non-interventional PASSs/PAESs, with a majority on safety/risk assessment. Although most utilized primary data collection, there was an increasing use of secondary real-world data sources. Few conducted comparative analyses, and most used single-arm designs. Future efforts are needed to assess how findings of these studies would impact regulatory decisions and improve knowledge of toxicity for clinical/translational development.

For a voltage-source-converter (VSC) based high voltage direct current (HVDC) system using modular multilevel converter (MMC) topology, it is vital to address the emergency DC fault current problem, and superconducting fault current limiter (SFCL) is a very serviceable and competitive solution. This paper proposes a performance evaluation approach for applying SFCL in MMC-HVDC transmission system. Firstly, according to different action stages of SFCL and DC circuit breaker (DCCB), the fault development process of the MMC-HVDC is elaborated. The fault current peak, dissipated energy of DCCB and fault clearance time are probed, and the critical limiting impedance is theoretically deduced. Then, three aspects of electrical stress, thermal stress and fault handling speed are specially considered, and a performance evaluation system with multiple indicators is built to assess SFCL functions. Using MATLAB, the performance assessment of a resistive SFCL and an inductive SFCL in a 320 kV/1.6 kA MMC-HVDC system is done. From comparative analyses, it is concluded that the resistive SFCL overall outperforms the inductive SFCL, and while the critical current-limiting resistance and inductance are gained. The suitability and feasibility of the proposed performance evaluation approach are validated.

This paper proposes an improved flux-coupling-type superconducting fault current limiter (FC-SFCL) with multiple working modes, and investigates the efficacy of the improved FC-SFCL in guarding a medium-voltage wind turbine generation system (WTGS). The improved FC-SFCL is mainly consisting of a coupling inductance with superconducting and conventional coils, two high-speed switches, a shunt resistance and an additional limiting resistance. Under normal circumstances, the improved FC-SFCL shows little impedance to not disturb the system. In terms of fault severities, the two high-speed switches are flexibly and separately controlled to change the current paths, and the improved FC-SFCL can appear two-level limiting impedances to affect the system's transient response. The performance validation of the improved FC-SFCL in a 35 kV class WTGS is done. From the theoretical derivation and simulation assessment, the results well testify the effectiveness of the improved FC-SFCL. The fault currents in the WTGS are timely suppressed to reasonable levels, and the fluctuations in the power and torque of the WTGS are visibly reduced. A beneficial voltage quality improvement is to maintain the grid connection of the WTGS and make it ride through the serious short circuit fault successfully.

Background Few clinical research studies with long‐term follow‐up have revealed whether cardiopulmonary bypass (CPB) increases the risk of postoperative distant metastasis in patients with giant refractory thoracic tumors. The present study evaluated the risk of distant metastasis after surgery utilizing CPB with long‐term follow‐up. Methods Clinical data for patients with giant refractory thoracic tumors who underwent resection with the use of CPB in the Second Affiliated Hospital of Soochow University during the past 11 years were retrospectively reviewed. Results Of the 14 patients with giant refractory thoracic tumors who had undergone surgery under CPB, 10 patients (71.4%) were completely resected. Twelve patients were followed up for 13–127 months with 10 patients were completely resected and two patients could not be completely resected due to severe tissue invasion. Three patients (25%) suffered from distant metastasis, and four patients (33.3%) experienced local recurrence. Only one patient (1/10) with complete resection suffered from distant metastasis, while two patients (2/10) experienced local recurrence. Two patients (2/2) with major resection suffered from both distant metastasis and local recurrence. Median overall survival for patients who have been regularly followed up was 50 months with 1‐, 5‐, and 10‐year survival of 100%, 75%, and 66.7%. No difference was found between the distant metastasis survival and the local recurrence survival. (p = 0.99). Conclusions CPB is an effective strategy for complete resection of the giant refractory thoracic tumors with an acceptable risk of postoperative distant metastasis for some patients., Giant refractory thoracic tumors of various pathological types invade the surrounding tissues and organs with serious consequences. The main risks during the conventional thoracic surgery are the damage to the surrounding important tissues and organs and instability of the respiratory and circulation systems. Cardiopulmonary bypass is an effective strategy for complete resection of giant refractory thoracic tumors without an extremely high risk of postoperative distant metastasis for some patients.

Ultrathin PEDOT:PSS film induces inversion layer within Si to achieve carrier separation, but it as the window-layer directly affects the light absorption. Herein, we show that management of reflectivity and parasitic absorption by adjusting PEDOT:PSS film thickness improves light absorption of active layer. According to the equivalent optical admittance theory and the finite element method, it is found that the reflectivity spectrum is divided into periodic and aperiodic regions by a certain wavelength threshold. When the threshold is close to 300 nm, the smaller reflection and parasitic absorption can be achieved. Meanwhile, with the increase of PEDOT:PSS film thickness, the quasi-Fermi level bending gradually weakens, and the hole concentration gradually keeps stable. This improves the carrier separation efficiency to reduce the carrier recombination, which ensures the improvement of solar cell performance. Finally, the power conversion efficiency (PCE) of 12.35% is obtained by applying the rule obtained from the simulation to the experiment, which is 30% higher than that of the unoptimized PEDOT:PSS/Si hybrid solar cell.

Girls and women constitute nearly 50% of all epilepsy cases. Apart from the disease symptoms, epilepsy and antiseizure medications (ASMs) may also affect the reproductive function, pregnancy and even the health of their offspring. Therefore, it is very important to identify and summarize the problems and risks for women with epilepsy (WWE) of childbearing age, and offer internationally recognized methods through multidisciplinary collaboration. In this review, we summarize the reproduction-related problems with WWE and propose multidisciplinary management by epileptologists, gynecologists and obstetricians, as well as other experts, from preconception to delivery. Large, multicenter registries are needed to advance our knowledge on new ASMs and their effects on WWE and their offspring.

Natural gas hydrate (NGH), as a clean energy with great development potential, has been limited by the lack of efficient and safe exploitation methods for a long time. The CO2 displacement method proposed in recent years has not made substantial progress because of its poor permeability and low efficiency. The NH3 replacement method is proposed in this paper because of its strong permeability. We performed orthogonal molecular dynamics simulation of the replacement of CH4 in hydrate with NH3 and CO2 at different temperatures (245 K, 255 K, 265 K) and pressures (3 MPa, 5 MPa, 10 MPa). It is shown that:(1) Compared with CO2 molecules, NH3 and can penetrate into the hydrate layer effectively, and the resulting pore channels are conducive to the outward diffusion of CH4 molecules. (2) With the progress of the replacement process, the hydrate structure gradually decomposes but not completely, and the residual structure will inhibit the diffusion of CH4 molecules and lead to the agglomeration of CH4 molecules. (3) Within 1000 ps, the number of CH4 molecules replaced by NH3 is more than that of CO2 under the conditions of 245 K and 255 K, and less than that of CO2 under the conditions of 265 K. At the same temperature, the pressure does not affect the final comparison result.

As a recently arisen framework, Label Distribution Learning (LDL) is one of the most appropriate machine learning paradigms to solve the label ambiguity problems. Due to the high cost, it is intractable to directly collect annotated distribution-level data. Therefore, Label Enhancement (LE) is proposed to obtain the label distribution for training LDL model by mining the information hidden in the logical labels. Accordingly, LE is usually taken as the pre-processing of LDL algorithm to learn with logical labels in previous methods. These two-stage learning methods may reduce the performance of LDL. To this end, we propose a unified framework called L 2 which simultaneously conducts Label Enhancement and Label Distribution Learning on samples and logical labels to fully exploit the implicit information for learning optimal LDL model. Specifically, the recovery of label distribution benefits from not only the optimization of the conventional LE objective function but also the feedback of LDL loss. What is more, the recovered distribution labels can be directly applied to the supervision of LDL training in an end-to-end way. Extensive experiments illustrate that L 2 can correctly recover the distribution-level data from the logical labels, and the trained LDL model can perform favorably against state-of-the-art LDL algorithms with the recovered distribution data. 1

Background Heart failure, which is characterized by cardiac remodelling, is one of the most common chronic diseases in the aged. Stimulator of interferon genes (STING) acts as an indispensable molecule modulating immune response and inflammation in many diseases. However, the effects of STING on cardiomyopathy, especially cardiac remodelling are still largely unknown. This study was designed to investigate whether STING could affect cardiac remodelling and to explore the potential mechanisms. Methods In vivo, aortic binding (AB) surgery was performed to construct the mice model of cardiac remodelling. A DNA microinjection system was used to trigger STING overexpression in mice. The STING mRNA and protein expression levels in mice heart were measured, and the cardiac hypertrophy, fibrosis, inflammation and cardiac function were also evaluated. In vitro, cardiomyocytes stimulated by Ang II and cardiac fibroblasts stimulated by TGF-β to performed to further study effects of STING on cardiac hypertrophy and fibroblast. In terms of mechanisms, the level of autophagy was detected in mice challenged with AB. Rapamycin, a canonical autophagy inducer, intraperitoneal injected into mice to study possible potential pathway. Results In vivo, the STING mRNA and protein expression levels in mice heart challenged with AB for 6 weeks were significantly increased. STING overexpression significantly mitigated cardiac hypertrophy, fibrosis and inflammation, apart from improving cardiac function. In vitro, experiments further disclosed that STING overexpression in cardiomyocytes induced by Ang II significantly inhibited the level of cardiomyocyte cross-section area and the ANP mRNA. Meanwhile, TGF-β-induced the increase of α-SMA content and collagen synthesis in cardiac fibroblasts could be also blocked by STING overexpression. In terms of mechanisms, mice challenged with AB showed higher level of autophagy compared with the normal mice. However, STING overexpression could reverse the activation of autophagy triggered by AB. Rapamycin, a canonical autophagy inducer, offset the cardioprotective effects of STING in mice challenged with AB. Finally, further experiments unveiled that STING may inhibit autophagy by phosphorylating ULK1 on serine757. Conclusions STING may prevent cardiac remodelling induced by pressure overload by inhibiting autophagy, which could be a promising therapeutic target in heart failure.

Power electronic transformers (PETs) can be used to interconnect different voltages and forms of electrical systems, and enable to offer higher operation efficiency and flexible power flow controllability. This paper focuses on the fault ride-through (FRT) problem of a PET interconnecting medium voltage (MV) and low voltage (LV) power systems, and the solution of a resistive superconducting fault current limiter (SFCL) is proposed. Firstly, theoretical modeling of the PET and the SFCL is addressed, and a suitable control strategy is applied to realize reliable power exchange between the LV and MV systems. Then, in regards to a fault at the PET's output-terminal, the fault developing process is probed, and considering the SFCL's quench behavior, the PET's current variations are clarified. Further, a 3 MW PET with a SFCL is modeled in MATLAB/Simulink, and through changing the fault severity and the SFCL parameter, different simulations are implemented. The results reveal that the SFCL stabilizes the PET from multiple aspects. A visible current-limiting function is achieved, and the voltage dynamic fluctuations at the AC and DC sides of the PET are effectively alleviated. Meanwhile, the power delivery from the LV to the MV system is smoothed, and a successful FRT fulfillment is gained.

DC distribution system (DCDS) has many preferable advantages to integrate renewable energy sources and native-DC loads than AC distribution system (ACDS), and the benefits of higher power density, greater energy conversion and wider supply radius can be obtained. In this paper, a methodology of sizing the techno-economic of a medium-low voltage DCDS is proposed. Firstly, the system framework and its equipment composition are stated. Then, considering the distribution capacity, supply ability, operation loss and reliability, the technical indicators of the demonstrated DCDS are analyzed and quantified. In regards to the DCDS's distribution-level and consumer-level, the calculation models of the annual costs are presented. Further, different scenarios are imitated to verify the efficacy of the proposed sizing approach, and the techno-economic comparison is implemented in the DCDS and ACDS with similar structure configurations. The calculation results reveal that the DCDS shows a visible economic performance at the consumer-level, and for the scenario of accessing high proportion DC loads, it is more cost-effective than the ACDS. Finally, the correctness of the cost models is proven, and this study can offer a reliable reference for building the medium-low voltage DCDS.

The purpose of this study was to evaluate the therapeutic efficacy and safety of endovascular treatment for patients with visceral and renal artery aneurysms (VRAAs). Twelve years of experience with interventional procedures and treatment options in our center were also worth discussing. From January 2009 to December 2020, clinical data of 159 consecutive patients with VRAAs were retrospectively analyzed. Patients' demographic and clinical data were recorded, and the safety and efficacy of endovascular therapy were evaluated. In addition, interventional procedures were also described. A total of 159 patients underwent angiography, and 154 patients were successfully treated with endovascular therapy, with a technical success rate of 96.9%. Of the 154 patients with successful endovascular therapy, 3 patients died within 30 days of treatment, with a 30-day mortality rate of 1.9%, and the remaining patients were clinically successful, with a clinical success rate of 98.1%. Fifty-seven patients underwent emergency interventional treatment due to ruptured aneurysm. There were statistically significant differences in hemoglobin before and after emergency treatment (78.5 ± 22.0 g/dL vs. 93.8 ± 15.0 g/dL, P = 0.00). No other serious complications occurred except death in 3 patients. Endovascular treatment of VRRAs is safe and effective and can significantly improve the symptoms of patients, especially those with ruptured aneurysms.

Celestial navigation is an important means of maritime navigation; it can automatically achieve inertially referenced positioning and orientation after a long period of development. However, the impact of different accuracy of observations and the influence of nonstationary states, such as ship speed change and steering, are not taken into account in existing algorithms. To solve this problem, this paper proposes an adaptively robust maritime celestial navigation algorithm, in which each observation value is given an equivalent weight according to the robust estimation theory, and the dynamic balance between astronomical observation and prediction values of vessel motion is adjusted by applying the adaptive factor. With this system, compared with the frequently used least square method and extended Kalman filter algorithm, not only are the real-time and high-precision navigation parameters, such as position, course, and speed for the vessel, calculated simultaneously, but also the influence of abnormal observation and vessel motion status change could be well suppressed.

STUDY DESIGN This was a systematic review and meta-analysis study. OBJECTIVE The purpose of this study is to evaluate the available evidence on the preservation of posterior midline structures in decompression surgery for lumbar spinal stenosis (LSS). SUMMARY OF BACKGROUND DATA The gold-standard treatment for LSS refractory to conservative management is facet-preserving laminectomy. The question remains whether the midline structures should be preserved in decompression surgery for LSS. MATERIALS AND METHODS We performed a systematic review of the Medline, PubMed, Embase, and Cochrane databases in search of published reports comparing midline structure preservation (MSP) and conventional laminectomy (CL) for LSS. The population was divided into 2 groups: (1) MSP group (intervention) and (2) CL group (control). The various outcome parameters including blood loss, operation time, hospital stay, back and leg pain, functional scores including Oswestry Disability Index (ODI) score, Japanese Orthopedic Association score, and 36-Item Short Form Survey (SF-36) scores, satisfaction, and instability rates were analyzed. Data were extracted and aggregated for meta-analysis. RESULTS Of the published reports, 16 met our inclusion criteria with an aggregated 540 in the intervention and 538 in the control groups, respectively. The aggregated data demonstrated patients undergoing MSP had significantly decreased back pain Visual Analog Scale compared with CL, regardless of time after surgery (P=0.007). The MSP group also showed a significantly lower Oswestry Disability Index score and SF-36 Mental Component Summary score (P=0.005 and 0.03, respectively) and longer 6-month walking distance (P

The visibility and analyzability of MRI and CT images have a great impact on the diagnosis of medical diseases. Therefore, for low-quality MRI and CT images, it is necessary to effectively improve the contrast while suppressing the noise. In this paper, we propose an enhancement and denoising strategy for low-quality medical images based on the sequence decomposition Retinex model and the inverse haze removal approach. To be specific, we first estimate the smoothed illumination and de-noised reflectance in a successive sequence. Then, we apply a color inversion from 0-255 to the estimated illumination, and introduce a haze removal approach based on the dark channel prior to adjust the inverted illumination. Finally, the enhanced image is generated by combining the adjusted illumination and the de-noised reflectance. As a result, improved visibility is obtained from the processed images and inefficient or excessive enhancement is avoided. To verify the reliability of the proposed method, we perform qualitative and quantitative evaluation on five MRI datasets and one CT dataset. Experimental results demonstrate that the proposed method strikes a splendid balance between enhancement and denoising, providing performance superior to that of several state-of-the-art methods.

PEDOT:PSS/Si hybrid solar cells have attracted wide attention due to the fabrication of an inversion layer near the Si surface by a solution method to realize high efficiency. However, Si dangling ...