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Rohdea medogensis, a new species from Tibet, China, is described and illustrated. This species is similar to R. verruculosa in sharing characters of the perianth with ringed, fleshy appendage in throat and lobes abaxially with verruculose, but differs mainly by bracts 3 per flower, with several sterile bracts apically; outer bract ca. 4.5 cm long, ca. 3 mm broad; perianth globular; lobes shorter ca. 2.0 mm long, margin lacerated, apical subacut; the top of annular appendage margin lacerated, 2 mm above the top of perianth tube; stigma bend, without lobed; style conspicuous; ovary globose or subglobose, askew; berry and seed ellipsoid, askew.

Background Correct torque of the incisors is beneficial in the assessment of the effects of orthodontic treatment. However, evaluating this process effectively remains a challenge. Improper anterior teeth torque angle can cause bone fenestrations and exposure of the root surface. Methods A three-dimensional finite element model of the maxillary incisor torque controlled by a homemade four-curvature auxiliary arch was established. The four-curvature auxiliary arch placed on the maxillary incisors was divided into four different state groups, among which 2 groups had tooth extraction space retracted traction force set to 1.15 N. Initial displacements and pressure stresses of the periodontal tissue in the maxillary incisors and molars were calculated after torque forces (0.5, 1, 1.5, and 2 N) were applied to the teeth at different stable states. Results The effect of using the four-curvature auxiliary arch on the incisors was significant but did not affect the position of the molars. Given the absence of tooth extraction space, when the four-curvature auxiliary arch was used in conjunction with absolute anchorage, the recommended force value was Conclusion A four-curvature auxiliary arch may treat severely upright anterior teeth and correct cortical fenestrations of the bone and root surface exposure.

Additional file 5: eFigure 2. Cost-effectiveness acceptability curves

Additional file 1. Clinical application case details.

Additional file 4: eFigure 1. Costs per live birth and per patient with and without PGT-A in the base-case

Additional file 1: eTable 1. Characteristics of the Patients in CESE-PGS trial

Additional file 2: eTable 2. Procedures for incorporating cost estimates in IVF

Additional file 2. Finite element raw data.

Additional file 3: eTable 3. Results of probabilistic sensitivity analysis

Transformer-based methods have demonstrated superior performance for monocular 3D object detection recently, which aims at predicting 3D attributes from a single 2D image. Most existing transformer-based methods leverage both visual and depth representations to explore valuable query points on objects, and the quality of the learned query points has a great impact on detection accuracy. Unfortunately, existing unsupervised attention mechanisms in transformers are prone to generate low-quality query features due to inaccurate receptive fields, especially on hard objects. To tackle this problem, this paper proposes a novel Supervised Scale-aware Deformable Attention (SSDA) for monocular 3D object detection. Specifically, SSDA presets several masks with different scales and utilizes depth and visual features to adaptively learn a scale-aware filter for object query augmentation. Imposing the scale awareness, SSDA could well predict the accurate receptive field of an object query to support robust query feature generation. Aside from this, SSDA is assigned with a Weighted Scale Matching (WSM) loss to supervise scale prediction, which presents more confident results as compared to the unsupervised attention mechanisms. Extensive experiments on the KITTI benchmark demonstrate that SSDA significantly improves the detection accuracy, especially on moderate and hard objects, yielding state-of-the-art performance as compared to the existing approaches. Our code will be made publicly available at https://github.com/mikasa3lili/SSD-MonoDETR., Comment: Code will be made publicly available at https://github.com/mikasa3lili/SSD-MonoDETR

Cardiometabolic diseases (CMDs) are associated with depression. However, it is unclear whether coexisting CMDs may increase the risk of depression. We examined associations between cardiometabolic multimorbidity and depressive symptoms among middle-aged and older Chinese.Participants aged ≥45 years were enrolled from the China Health and Retirement Longitudinal Study 2011-2018 (N = 18,002). Cardiometabolic multimorbidity was defined as the coexistence of ≥2 CMDs, including stroke, heart disease, diabetes, hypertension, and dyslipidemia. Depressive symptoms were assessed by the Center for Epidemiological Studies Depression Scale. We used generalized estimating equation models to examine associations between cardiometabolic multimorbidity and depressive symptoms, including the dose effect of disease count and prevalent disease combinations, as well as individual and additive effects of specific CMDs.The prevalence of cardiometabolic multimorbidity was 24.5%. A higher number of CMDs had an additive dose effect on depressive symptoms that persisted consistently in specific CMDs. Stroke only, heart disease only, and diabetes only were each associated with a higher risk of depressive symptoms compared with no CMDs. CMD combinations involving stroke, heart disease, or diabetes were each associated with an increased risk of depressive symptoms compared with the absence of stroke, heart disease, or diabetes.Self-reported chronic conditions.Stroke, heart disease, and diabetes showed individual and additive effects on CMD combinations, whereas hypertension and dyslipidemia only showed associations with depressive symptoms in combinations with other CMDs. These results suggest person-centered healthcare of mental health prevention and treatment for middle-aged and older adults with individual or multiple CMDs.

The GDSL esterase/lipase family contains many functional genes that perform important biological functions in growth and development, morphogenesis, seed oil synthesis, and defense responses in plants. The expression of GDSL esterase/lipase genes can respond to biotic and abiotic stresses. Although GDSL esterase/lipase family genes have been identified and studied in other plants, they have not been identified and their functions remain unclear in tomato. This study is the first to identify 80 GDSL esterase/lipase family genes in tomato, which were named SlGELP1–80. These genes were mapped to their positions on the chromosomes and their physical and chemical properties, gene structure, phylogenetic relationships, collinear relationships, and cis-acting elements were analyzed. The spatiotemporal expression characteristics of the SlGELP genes in tomato were diverse. In addition, RNA-seq analysis indicated that the expression patterns of the SlGELP genes in tomato differed before and after inoculation with Stemphylium lycopersici. qRT-PCR was used to analyze the expression of five SlGELP genes after treatments with S. lycopersici, salicylic acid and jasmonic acid. Finally, this study was the first to identify and analyze GDSL esterase/lipase family genes in tomato via bioinformatics approaches, and these findings provide new insights for improving the study of plant disease resistance.

Logging data of Tazhong clastic rock formation shows that cementing quality of water layer is poor and the efficiency of cement displacement is low. Bohai Drilling Co., Ltd. has adopted a cement slurry system with excellent anti-channeling performance in Tazhong block and strictly controlled the cementing construction procedure, however, the cementing quality problem of water layer still exists. According to the cementing quality analysis, the influence of ions in formation water in Tazhong clastic strata on cement slurry performance was researched in this paper. The results show that ions in formation water has no negative impact on the loss of water and gas channeling resistance of the cement slurry system, however, has some adverse effects on the rheological property, thickening property and hardened strength. Furthermore, cement slurry consistency increasing caused by formation water is the key factor leading to poor cementing quality. Studies show that the carboxylic acid group and the magnesium ion chelate to form a network structure, which binds the free water in the cement slurry and causes the deterioration of the rheology. The magnesium resistance ability of the polymer becomes worse, when the proportion of the carboxylic acid group increases. Therefore, in order to improve rheology of cement slurry, a fluid loss agent with a small number of carboxylic acid group or no carboxylic acid group is required when the slurry or formation water containing a certain amount of magnesium ion. This investigation provides the theoretical guidance of the selection of cementing additives in the areas of which water containing high dosage of magnesium ion.

Myocardial infarction (MI) remains the most common cause of death worldwide. Many MI survivors will suffer from recurrent heart failure (HF), which has been recognized as a determinant of adverse prognosis. Despite the success of improved early survival after MI by primary percutaneous coronary intervention, HF after MI is becoming the major driver of late morbidity, mortality, and healthcare costs. The development of regenerative medicine has brought hope to MI treatment in the past decade. Mesenchymal stem cell (MSC)-derived exosomes have been established as an essential part of stem cell paracrine factors for heart regeneration. However, its regenerative power is hampered by low delivery efficiency to the heart. We designed, fabricated, and tested a minimally invasive exosome spray (EXOS) based on MSC exosomes and biomaterials. In a mouse model of acute myocardial infarction, EXOS improved cardiac function and reduced fibrosis, and promoted endogenous angiomyogenesis in the post-injury heart. We further tested the feasibility and safety of EXOS in a pig model. Our results indicate that EXOS is a promising strategy to deliver therapeutic exosomes for heart repair.

Smart hospitals are important components of smart cities. An intelligent medical system for brain tumor segmentation is required to construct smart hospitals. To achieve intelligent brain tumor segmentation, morphological variety and serious category imbalance must be managed effectively. Conventional deep neural networks have difficulty in predicting high-accuracy segmentation images due to these issues. To solve these problems, we propose using multimodal brain tumor images combined with the UNET and LSTM models to construct a new network structure with a mixed loss function to solve sample imbalance and describe an intelligent segmentation process to identify brain tumors. To verify the practicability of this algorithm, we used the open source Brain Tumor Segmentation Challenge dataset to train and verify the proposed network. We obtained DSCs of 0.91, 0.82, and 0.80; sensitivities of 0.93, 0.85, and 0.82; and specificities of 0.99, 0.99, and 0.98 in three tumor regions, including the whole tumor ( WT ), tumor core ( TC ), and enhanced tumor ( ET ). We also compared the results of the proposed network with those of other brain tumor segmentation methods, and the results showed that the proposed algorithm could segment different tumor lesions more accurately, highlighting its potential application value in the clinical diagnosis of brain tumors.

With the advance of artificial intelligence and communication technology in the smart city, various location-based data of users can be collected via location-based social networks (LBSNs). How to make full use of these data for accurate point-of-interest (POI) recommendation is challenging because POI selection is influenced by various factors. In this article, we propose a network representation learning-enhanced multisource information (MSI) fusion model for POI recommendation in the context of LBSNs. The proposed model jointly considers various factors, including user preference, geographical influence, and social influence for a recommendation. Specifically, the social influence is modeled by performing network representation learning methods on the constructed co-visiting user networks so that the hidden complex social relationships among users can be measured automatically. Moreover, considering the significance of user preference and geographical influence, a fusion model is designed to jointly consider user preference, social influence, and geographical influence for POI recommendation. Our method is evaluated based on two publicly available data sets and extensive experimental results demonstrate that the proposed MSI fusion model outperforms several state-of-the-art algorithms for POI recommendation in terms of precision, recall, and F1.

At present, medical images have played a more and more important role in clinical treatment. Lung images provide an important reference for doctors to make a diagnosis. Especially for surgical patients, a tumor can be accurately removed based on the full cognition about its size, position, and quantity. Therefore, computer-aided diagnosis for the analysis and treatment of a lot of lung tumor images is very important. Aiming at complexity and self-adaption of image segmentation in lung tumors, this article proposed a parallel deep learning algorithm with hybrid attention mechanism for image segmentation. First, lung parenchyma was extracted via preprocessing images. Then, images were input into hybrid attention mechanism and densely connected convolutional networks (DenseNet) module, respectively, where hybrid attention mechanism consisted of a spatial attention mechanism and a channel attention mechanism. Finally, four feasible solutions were proposed for the verification through changing the convolution quantity of dense block in DenseNet. The network structure with the better performance was achieved. The experimental results prove the parallel deep learning algorithm with hybrid attention mechanism performed well in image segmentation of lung tumors, and its accuracy can reach 94.61%.

To provide a quantitative synthesis of studies on the relationship between vision impairment (VI) and cognitive outcomes in older adults.A systematic search was undertaken of relevant databases for original articles published before April 2020. Random effect models were used to obtain pooled estimates of the associations between VI and cognitive outcomes (cognitive impairment and dementia) with subgroup analyses of VI measures, cross-sectional associations of VI with cognitive impairment, and longitudinal associations of baseline VI with incident cognitive impairment and dementia. Potential sources of heterogeneity were explored by meta-regression. Publication bias was evaluated with Egger's test.Sixteen studies including 76,373 participants were included in this meta-analysis, with five cross-sectional studies and eleven longitudinal studies. There was a significantly increased risk of cognitive outcomes with VI identified by subjective measures (odds ratio (OR)=1.63; 95% confidence interval (CI): 1.26-1.99) and objective measures (OR = 1.59; 95% CI: 1.40-1.78). The odds of baseline cognitive impairment were 137% higher in older adults with VI compared with those without VI (OR = 2.37, 95% CI: 1.84-3.03) at baseline. Compared with older adults without VI at baseline, those with baseline VI had a higher relative risk (RR) of incident cognitive impairment (RR = 1.41; 95% CI: 1.31-1.51) and dementia (RR = 1.44, 95% CI: 1.19-1.75).VI was associated with increased risks of cognitive impairment and dementia across cross-sectional and longitudinal studies. Additional research and randomized clinical trials are warranted to examine the implications of treatment for VI, such as wearing glasses and cataract surgery, to avoid cognitive impairment and dementia.

Rohdea medogensis H. Z. Feng & Q. W. LIN, sp. nov. (Figs. 1 & 2) Type:— CHINA. Tibet Autonomous Region: Linzhi, Motuo county, alt. 1837 m, 16 January 2022, Q. W . Lin 2022–0047 (holotype, PE!). Diagnosis:—This species is similar to R. verruculosa (Chen 1987: 69) Tanaka (2003: 332), but differs mainly by bracts 3 per flower, with several sterile bracts apically; outer bract ca. 4.5 cm long, ca. 3 mm broad; perianth globular; lobes shorter ca. 2.0 mm long, margin lacerated, apical subacut; the top of annular appendage margin lacerated, 2 mm above the the top of perianth tube; stigma bend, without lobed; style conspicuous; ovary globose or subglobose, askew; berry and seed ellipsoid, askew. Description:—Chamaephytic herb. Rhizome cylindrical, usually erect, to 2.5 cm in diameter, 5–6 cm long. Roots fibrous, to 6 mm in diameter. Stem (aerial part) short, up to 5 cm long. Leaves equitant, narrowly oblanceolate, narrowly elliptic or lorate, acute to acuminate at apex, tapering gradually to petiole-like base, subcoriaceous, 20–55 cm long, 3–8 cm wide. Peduncle ca. 3 cm long. Spike cylindrical or ellipsoid, with ca. 6 flowers, ca. 5 cm long, with several sterile bracts apically. Bracts 3 per flower, often minutely denticulate at margin, herbaceous or membranous; outer bract 1, borne slightly below flower, exceeding flower, lanceolate or narrowly deltoid, acute, 3–5 cm long, 2– 3 mm broad; inner bract (bracteole) 2, subulate, to 7 mm long, 1.5–2 mm broad, with several sterile bracts apically. Perianth globular, green, turning yellow or orange with age, 8–10 mm across; lobes deltoid-ovate, lacerated, often abaxially with verruculose long margins, 2–3 mm long, 3–4 mm wide; tube cupulate, 2.5–4 mm long, at orifice of tube developing annulus (or annular ledge) appendages, 1–1.5 mm broad. The annulus appendages and tube formed a capsule chamber that encloses the pistil, and there is only a small hole in the center, diam. 1mm, lacerated. The stamens are above the annulus appendages. Anther oblong or ovate, 0.8–1.5 mm long, connectives sometimes corniculate dorsally, cornicle up to 1.5 mm long; filaments incurved, 1–2 mm long, inserted in upper part of perianth tube, decurrent parts lamellate, dilated below, united with adjacent ones in lower part of tube. Pistil ca. 5 mm long; stigma bend and not lobbed; style columnar, conspicuous, 3.5–5.5 mm long; ovary globose or subglobose, askew, 2.5–3.0 mm in diam. Berry ellipsoid, askew, ca. 2.5 cm long, scarlet at maturity. Seed ellipsoid, askew, ca. 1.0 cm in diam. Etymology:—The new species from Motuo (=Medog) country, we therefore give the epithet Rohdea medogensis. Distribution:—This new species is currently known only from Motuo, Linzhi, Tibet, China. Taxonomic relationships:—The comparisons with the known species of Rohdea indicates that R. medogensis is similar to R. verruculosa, R. annulata (Li & Huang in Huang & Li 1990: 51) Yamashita & Tamura (2004: 369) and R. harderi Tanaka, Hannon & Averyanov in Tanaka et al. (2018: 2) by stamens enclosed annulus appendage or stamens situated outer annulus appendage while other species as R. uropetala Handel-Mazzetti (1920: 272), R. lichuanensis (Yang, Wu & Peng in Wang et al. 1991: 40) Yamashita & Tamura (2004: 369) and R. emeiensis (Zhu 1982: 271) Tanaka (2003: 332) possess annulus appendage enclosed stamens or stamens situated inner annulus appendages. The new species more similar to R. verruculosa because of the lobes abaxially with verruculose in these two species. R. medogensis differs from R. verruculosa by the characters of the short spike and peduncle. R. medogensis with several sterile bracts apically and it also has 3 fertile bracts per flower and the outer bract exceeding the flowers. In R. medogensis the perianth globular; lobes deltoid-ovate, very short, apical portion subacute, in R. verruculosa perianth subcampanulate, lobes ovate, apex cuspidate. And the style in R. medogensis was very conspicuous, ovary askew and stigma was bend and not lobed, but in R. verruculosa the style was very short and ovary globose, the stigma was straight and 3-lobed. The floral traits of the two species are compared in Table 1., Published as part of Feng, Hui Zhe, Ren, Yong Zhu Ci, He, Xuan, Han, Qing Xiang & Lin, Qin Wen, 2022, Rohdea medogensis (Asparagaceae), a new species from southeast Tibet, China, pp. 90-94 in Phytotaxa 542 (1) on pages 91-92, DOI: 10.11646/phytotaxa.542.1.8, http://zenodo.org/record/6404650, {"references":["Chen, J. H. (1987) A new species of Tupistra (Liliaceae) from Guizhou. Acta Phytotaxonomica Sinica 25 (1): 69 - 70.","Tanaka, N. (2003) New combinations in Rohdea (Convallariaceae). Novon 13: 329 - 333. https: // doi. org / 10.2307 / 3393269","Huang, J. L. & Li, H. (1990) Study on the taxonomic system of the genus Tupistra. Acta Botanica Yunnanica 12 (S 3): 49 - 61.","Yamashita, J. & Tamura, M. N. (2004) Phylogenetic analyses and chromosome evolution in Convallarieae (Ruscaceae sensu lato), with some taxonomic treatments. Journal of Plant Research 117: 363 - 370. https: // doi. org / 10.1007 / s 10265 - 004 - 0169 - z","Tanaka, N., Hannon, D. P., Harder, D. K., Averyanov, L. V. & Lahmeyer, S. C. (2018) Rohdea harderi (Asparagaceae), a new species from northern Vietnam. Kew Bulletin 73 (3): 31 - 37. https: // doi. org / 10.1007 / s 12225 - 018 - 9756 - 3","Handel-Mazzetti, H. R. E. (1920) Tupistra fimbriata. Anzeiger der Akademie der Wissenschaften in Wien, vol 59. Mathematischenaturwissenchaftliche Klasse, Wien. pp. 253 - 256.","Wang, F., Yang, Y., Wu, J. & Peng, D. (1991) A new species of Tupistra Ker-gawl from Hubei. Journal of Wuhan Botanical Research 9: 40 - 42.","Zhu, Z. Y. (1982) A new species of Tupistra of E'meishan. Acta Botanica Yunnanica 4 (3): 271 - 272."]}

Solar steam generation has attracted interest in water purification and seawater desalination as an efficient solar energy conversion method. However, the complex preparation process and limited efficiency restrict the practical applications of solar-generated steam. Here, we report a three-dimensional wood membrane inside coated with MoS2 (WM-H, with S defects) for efficient seawater desalination. The vertically aligned mesoporous wood channels and their inner microstructures increase the contact interface between water and MoS2 in wood. The formation of S defects allows the surface temperature of the membrane to reach ∼53 °C under 1 sun illumination. The MoS2-coated wood with S defects exhibited an excellent evaporation flux (1.46 kg m−2 h−1, one sun), with a solar thermal conversion efficiency of 82.5%. The adsorption peak values of Na+ on the two sides of MoS2 with defects are 2.17 times and 1.49 times higher than those of MoS2 without defects. The wood-based design provides an inexpensive way to capture solar energy and generate steam.

As a pentacyclic triterpene, MA exhibits effective free radical scavenging capabilities. The purpose of this study was to explore the effects of MA on porcine early-stage embryonic development, oxidation resistance and mitochondrial function. Our results showed that 1 μM was the optimal concentration of MA, which resulted in dramatically increased blastocyst formation rates and improvement of blastocyst quality of in vitro-derived embryos from parthenogenetic activation (PA) and somatic cell nuclear transfer (SCNT). Further analysis indicated that MA supplementation not only significantly decreased the abundance of intracellular reactive oxygen species (ROS) and dramatically increased the abundance of intracellular reductive glutathione (GSH) in porcine early-stage embryos, but also clearly attenuated mitochondrial dysfunction and inhibited apoptosis. Moreover, Western blotting showed that MA supplementation upregulated OCT4 (p < 0.01), SOD1 (p < 0.0001) and CAT (p < 0.05) protein expression in porcine early-stage embryos. Collectively, our data reveal that MA supplementation exerts helpful effects on porcine early embryo development competence via regulation of oxidative stress (OS) and amelioration of mitochondrial function and that MA may be useful for increasing the in vitro production (IVP) efficiency of porcine early-stage embryos.

Unit commitment (UC) are essential tools to transmission system operators for finding the most economical and feasible generation schedules and dispatch signals. Constraint screening has been receiving attention as it holds the promise for reducing a number of inactive or redundant constraints in the UC problem, so that the solution process of large scale UC problem can be accelerated by considering the reduced optimization problem. Standard constraint screening approach relies on optimizing over load and generations to find binding line flow constraints, yet the screening is conservative with a large percentage of constraints still reserved for the UC problem. In this paper, we propose a novel machine learning (ML) model to predict the most economical costs given load inputs. Such ML model bridges the cost perspectives of UC decisions to the optimization-based constraint screening model, and can screen out higher proportion of operational constraints. We verify the proposed method's performance on both sample-aware and sample-agnostic setting, and illustrate the proposed scheme can further reduce the computation time on a variety of setup for UC problems.

With the advancement of Internet of Things technology, we are able to collect massive people's trajectory data from various GPS services. These large amounts of trajectory records enable us to better understand human mobility patterns. Meanwhile, we are able to extract social relationships based on these digital records to provide personalized recommendation services, such as points of interests (POI) recommendation and friend recommendation. In this paper, we propose to recommend friends for taxi drivers based on vehicular trajectory records. For this purpose, we propose to construct a vehicular ad hoc network based on co-occurrence phenomenon. Furthermore, we take advantages of the network representation learning technique on the vehicular ad hoc network for learning driver vectors. Finally, potential friends are recommended based on the similarity of driver vectors. Extensive experimental results on two real-world datasets demonstrate that our proposed method has the best performance on friend recommendation compared with several state-of-the-art methods. To the best of our knowledge, this is the first attempt to recommend friends for taxi drivers based on vehicular ad hoc network representation learning.

In recent years, more and more attention has been paid to the traffic safety of drivers. Studies show that the motor vehicle speed will affect the incidence of traffic accidents and traffic accident casualty rate. In this paper, machine learning vision technology is used for real-time recognition of driver emotions, and a lightweight SIC-NET+RC-NET dual-stream recognition model is designed to cope with different scenarios of vehicle speed during driving. SIC-NET is a lightweight CNN network model, which greatly reduces the number of model parameters and computational power requirements, sacrifices part of accuracy, and greatly improves the real-time performance of model recognition. To improve the residual convolutional network model of inception blocks, RC-NET nested multiple micro-convolutional neural networks are used to identity mapping between different inception blocks to enhance the network training effect, expand network width and convolutional depth, and alleviate network degradation. This article stipulates that when the vehicle speed is greater than 60km/h, SIC-NET is used. When the vehicle speed is less than or equal to 60km/h, SIC-NET+RC-NRT is used. The FER2013 dataset was used for testing and validation in this paper. When SIC-NET is used, the model has better real-time performance and can provide a more timely warning when the vehicle speed is higher. When SIC-NET+RC-NET is used, the accuracy of the model in the FER2013 dataset is 69.65%, and the model can better cope with the scenario of a low vehicle speed. The experiment shows that the lightweight dual-flow model has good robustness and identification effect, which solves the problem of using the same model for different vehicle speeds and can effectively ensure the safety of the driver’s life and property.

Aiming at the lack of sufficient meteorological data for runoff prediction in areas with few data, the accuracy of the data is improved by using soft thresholding under the deep attention mechanism, and a deep residual shrinkage long-short memory network prediction model is constructed combined with the watershed characteristic data. The model is validated by using 134 watersheds with spatial correlations in the CAMELS dataset. According to the experimental findings, the model is more accurate than the LSTM model, HIV model, and mHM model in predicting runoff in regions with little data, with an accuracy of 86%.

This study aimed to examine and compare the associations between different multimorbidity measures and mortality among older Chinese adults.Using the Chinese Longitudinal Healthy Longevity Survey 2002-2018, data on fourteen chronic conditions from 13,144 participants aged ≥65 years were collected. Multimorbidity measures included condition counts, multimorbidity patterns (examined by exploratory factor analysis), and multimorbidity trajectories (examined by a group-based trajectory model). Mortality risk associated with different multimorbidity measures was each analyzed using Cox regression. C-statistic, the Integrated Discrimination Improvement (IDI), and the Net Reclassification Index (NRI) were used to compare the performance of different multimorbidity measures.Participants with multimorbidity, regardless of measurements, had a higher risk of death compared with people without multimorbidity. Compared with the mortality prediction model using age and sex, C-statistics showed added discrimination (over 0.77, all P .05) for models with multimorbidity measures. Multimorbidity trajectory showed integrated discrimination and net reclassification improvement for mortality prediction compared to condition count (IDI = 0.042, NRI = 0.033) and multimorbidity pattern (IDI = 0.041, NRI = 0.069).Adding multimorbidity measures significantly improved the performance of a mortality prediction model using age and sex as predictors. Trajectory-based measures of multimorbidity performed better than count- and pattern-based measures for mortality prediction.

The evaluation and optimization of reservoir operation schemes belong to a multi-objective, multi-level and multi-attribute decision-making problem. The reservoir multi-objective dispatching model generates many Pareto feasible solutions, and decision-makers often make decisions difficult. The traditional scheme selection method has the problems that the index weight is greatly affected by subjectivity, the single weight determination method is one-sided, the model calculation is complicated, and the characteristics of the evaluation index cannot be fully extracted. Therefore, this paper proposes a new method for reservoir operation plan optimization based on fuzzy optimization and convolutional neural network. First, establish the evaluation index system of the reservoir operation plan based on the fuzzy optimization theory, select the analytic hierarchy process to determine the subjective weight of the index, the entropy weight method to determine the objective weight, use the game theory to couple the subjective and objective weights, and calculate the comprehensive evaluation value of the plan through fuzzy comprehensive evaluation. Secondly, the evaluation index and comprehensive evaluation value are used as the input and output of the convolutional neural network to establish the optimal model of the reservoir operation plan. The results of the case analysis show that the research method has high accuracy and reliability, and can provide a scientific basis for reservoir operation decision-making.

We built a data-driven prediction model based on Time Series Neural Network regression model to explore the feasibility of utilizing functional connectivity (FC) to predict the continuous fatigue levels during underload task. When participants performed a 120-minute dull driving task, experimental data was recorded. The EEG and eye closure data used in this paper are from SJTU Emotion EEG Dataset, SEED. Unlike other researches, We proposed a functional brain networks method based on Phase Lag Index (PLI) to analyze EEG effectively and incorporate the temporal dependency of PERCLOS into model training. The functional connectivity corresponding to different fatigue degrees during whole experiment were analyzed. Meanwhile, taking the clustering coefficient (C) values, degree(D) and characteristic path length (L) values as input respectively while PERCLOS as output. The results suggest that brain network analysis approaches combined with Neural Network are effective to predicts individual mental fatigue during long time driving and can improve the performance of fatigue detection with a higher prediction correlation coefficient of 0.99 and a lower RMSE value of 0.01 on average.

Gastric cancer (GC) is one of the infection-related cancers. Helicobacter pylori and Epstein-Barr virus (EBV) were established risk factors for GC. Recently, there are several reports showing the inconsistent association between hepatitis B virus (HBV) infection and the development of GC. To explore the relationship between HBV infection and the development of GC, we designed a meta-analysis of previous epidemiological studies, a hospital-based case-control study, followed by an immunohistochemistry (IHC) assay of HBV-exposed GC samples. We found that HBV infection was associated with an increased risk of GC based on the meta-analysis. No significant association between HBV infection and GC was detected according to our hospital-based case-control study. Histological examination showed that the gastric epithelium positive for HBx demonstrated a higher nuclear-cytoplasmic ratio compared to those HBx-negative cells. HBx and HBcAg were expressed more in tumors than those in normal counterparts in HBV-exposed subjects, and PD-L1 was lower in GC tissues from HBV carriers than those in HBV clearances. In conclusion, HBV infection may contribute to a higher risk for GC based on the meta-analysis and to the morphological atypia of gastric epithelium by the histological assessment, and GC patients among HBV carriers showed lower expression of PD-L1 may lose the chance for immune checkpoint blockade therapy.

Sapogenin is the main block of Camellia oleifera saponin, which was purified and structurally modified by the C28 acylation reaction to synthesize 19 new derivatives. The growth and biofilm inhibition of Staphylococcus aureus and Escherichia coli was measured to evaluate their antibacterial effects. A three-dimensional quantitative structure-activity relationship (3D-QSAR) assay indicated that the antibacterial activities were significantly enhanced after sapogenin was modified with an aromatic ring or heterocyclic ring and electron-withdrawing substituents at the meta or para position. Among them, the derivative of sapogenin with a 2-mercapto-4-methyl-5-thiazolyl acetyl group obviously destroyed bacterial biofilm and made bacteria lysis. 3D-QSAR provides practical information for the structural design of sapogenin derivatives with strong antibacterial activity, and the C. oleifera sapogenin derivative 28-O-(2-mercapto-4-methyl-5-thiazolyl)-3β,16α,21β,22α-O-tetrahydroxy-oleantel-2-ene-23-aldehyde (S-16) is an effective candidate as an antibacterial agent for the prevention of bacterial resistance against antibiotics.

The problem of reservoir flood control operation is a multi-objective optimization problem. In order to solve this problem, a new algorithm based on graph convolution neural network and fast non-dominated sorting genetic algorithm II (GCN_NSGA-II) is proposed in this paper. When NSGA-II algorithm is used to solve multi-objective optimization problems, its convergence speed will slow down when the iteration reaches a certain algebra. In order to speed up the convergence speed, we use genetic algorithm to simulate the reproduction process of biological population. There is a relationship between parents and offspring. By means of group coding, the tree structure of the parents and children is transformed into a graph structure, and the GCN is trained and the graph nodes are classified, and the Pareto solution set can be obtained more quickly. In order to further ensure the integrity and uniformity, the NSGA-IIalgorithm is used to adjust it. The performance index IGD is used to measure the algorithm in the process. This algorithm speeds up the convergence speed and ensures the uniformity of Pareto solution set. The effectiveness of the algorithm in this paper is verified on the Xiaolangdi Reservoir flood control and dispatching problem. Compared with the NSGA-II and NSGA-DE algorithms, for the same index value, the number of iterations of the GCN_NSGA-II algorithm is significantly reduced and the convergence speed is significantly accelerated.

Based on the requirement of industrial automation, this paper proposes a three-dimensional reconstruction algorithm of the dynamic environment for industrial operation environment perception, which can be applied to many different industrial fields. According to the actual situation of the inner wall of the rolling mill, a method of lidar raw data preprocessing is proposed in this paper. The original lidar data is tagged and the detailed local point cloud information of interest is isolated. Loop detection is introduced into the algorithm to establish a globally consistent point cloud graph. The overall environment modeling algorithm is constructed to realize the real-time dynamic modeling of indoor environment in the actual industrial environment operation. The method has been evaluated by real-time reconstruction of the three-dimensional model of the specified area, which provides prior information for the operation of the robotic manipulator. We compare the performance of three-dimensional with loam, using the actual industrial environment, and show that our algorithm achieves better accuracy with reduced computational expense.

We report on space-selective crystallization of congruent and polar Sr2TiSi2O8 crystals in a stoichiometric SrO-TiO2-SiO2 glass induced by (1030 nm, 300 fs) femtosecond laser irradiation. This allows us to compare with non-congruent laser induced crystallization of polar LiNbO3, in non stoichiometric Li2O-Nb2O5-SiO2 glass and gain information on the mechanism of nanocrystals orientation with the laser polarization that we pointed out previously. Using scanning electron microscopy (SEM), Second-harmonic generation (SHG) and electron backscattered diffraction (EBSD), we studied the laser induced crystallization according to the laser processing parameters (pulse energy, pulse repetition rate, scanning speed). We found 1) a domain where the laser track is filled with crystals not perfectly textured (low energy), 2) a domain where an amorphous volume remain surrounded by a crystallized shell (high energy). This arises from Sr out-diffusion and may gives rise to crystallization of both SrTiO3 and Sr2TiSi2O8 phases at low speed. In the one-phase domain (at higher speed), it is found the possibility to elaborate a tube with a perfect fresnoite texture. Significant difference in size and morphology whereas crystallization threshold remains similar are discussed based on glases thermal propeties. Contrarily to Li2O-Nb2O5-SiO2 (LNS) glass, no domain of oriented nanocrystallization controlled by the laser polarization has been found in SrO-TiO2-SiO2 (STS) glass, which is attributed to the larger crystallization speed in STS glass. No nanogratings have also been found that is likely due to the congruency of the glass.

Recent work by Smagloy et al. (ISIT 2020) shows that the redundancy of a single-deletion $s$-substitution correcting code is asymptotically at least $(s+1)\log n+o(\log n)$, where $n$ is the length of the codes. They also provide a construction of single-deletion and single-substitution codes with redundancy $6\log n+8$. In this paper, we propose a family of systematic single-deletion $s$-substitution correcting codes of length $n$ with asymptotical redundancy at most $(3s+4)\log n+o(\log n)$ and polynomial encoding/decoding complexity, where $s\geq 2$ is a constant. Specifically, the encoding and decoding complexity of the proposed codes are $O(n^{s+3})$ and $O(n^{s+2})$, respectively.

Additional file 1: Definition of asynchrony, and tables and figures.

Regarding the continuous development of high-speed trains and the increase of running speeds, the aerodynamic design of high-speed trains has become significantly important, while reduction of drag and noise comprises a significant challenge in order to optimize aerodynamic design of high-speed trains. The design form factor of a high-speed train is highly influenced by aerodynamic aspects including aerodynamic drag, lift force, and noise. With the high-speed train as the object, the paper aims to take bionic concept as the entry point, selecting the hummingbird as the bionic prototype and extracting bionic elements to establish a bionic train model. Then, the finite volume method was used for numerical simulation and analysis of the aerodynamic performance and aerodynamic noise of the bionic high-speed train. Computational results prove that drag and noise of the bionic head type were lower than those of the original train; drag of the head train of the bionic model was reduced by 2.21% in comparison with the original model, while the whole-train drag was reduced by 3.53%, indicating that drag reduction effects are available and implying that the bionic head type could reduce drag and noise. Noise sources of the bionic train are mainly located at positions with easy airflow separation and violent turbulence motion. Large turbulence energy is in bogie areas and mainly exists at the leeward side of the bogie area. Obviously, the bogie area is the major noise source of the train. Aerodynamic noise of the bionic train in far-field comprises a wide-frequency range. Noises were concentrated within 613 Hz~3150 Hz. When the bionic high-speed train ran at 350 km/h, through comparative analysis of total noise levels at observed points of the high-speed train, it is found that this position with the maximum noise level was 25 m away from the head train nose tip, with the maximum value of 88.4 dB (A). When the bionic train ran at 600 km/h, the maximum sound pressure level at the longitudinal point was 99.7 dB (A) and the average noise level was 96.6 dB (A). When the running speed increased from 350 km/h to 600 km/h, the maximum noise level increased by 11.3 dB (A) and the average noise level increased by 11.6 dB (A). Computation results of aerodynamic noise at the point which is 7.5 m away from the rail center show that the maximum aerodynamic noise level existed at the first-end bogie of the head train, while the noise level was larger at the position closer to the ground.

Background Galcanezumab is a novel monoclonal antibody that target to calcitonin gene-related peptide (CGRP). It has been tested for the preventive treatment of migraine and episodic cluster headache by multiple randomized clinical trials (RCTs) and have been found to reduce headache frequency. Methods We systematically searched PubMed and Embase on Cochrane Central Register of Controlled Trials (CENTRAL) from the earliest date to August 1, 2019. Relative risk (RR) and weighted mean difference (WMD) were used to evaluate clinical outcomes. Results Seven studies were pooled with 3889 patients. Subcutaneous injection of Galcanezumab at 120 mg, 240 mg leads to a statistically significant response rate for the treatment of migraine compared with placebo (120 mg: RR = 1.51; 95% CI, 1.33 to 1.70; P P P = 0.425; 75% response: RR = 1.07; 95% CI, 0.94 to 1.23; P = 0.301; 100% response; RR = 1.06; 95% CI, 0.81 to 1.37; P = 0.682; MHD: RR = − 0.08; 95% CI, − 0.55 to − 0.40; P = 0.748) while related to a lower risk for adverse events for the treatment of migraine (120 mg RR = 1.06; 95% CI, 0.99 to 1.14; P = 0.084; 240 mg: RR = 1.17; 95% CI, 1.09 to 1.25; P P = 0.048). Conclusions Use of galcanezumab is related to a significantly reduced monthly headache frequency compared with placebo for the treatment of migraine and episodic cluster headache, 120 mg has the same treatment efficacy with 240 mg group while related to a lower risk for adverse effects for the treatment of migraine. 300 mg per month galcanezumab is effective for the prevention of episodic cluster headache with no significantly increased adverse events.

With the world development of high-speed railways and increasing speeds, aerodynamic forces and moments acting on trains have been increased further, making trains stay at a “floated” state. Under a strong crosswind, the aerodynamic performance of a train on the embankment is greatly deteriorated; lift force and horizontal force borne by trains will be increased quickly; trains may suffer derailing or overturning more easily compared with the flat ground; train derailing will take place when the case is serious. All of these phenomena have brought risks to people’s life and properties. Hence, the paper establishes an aerodynamic model about a high-speed train passing an air barrier, computes aerodynamic forces and moments, and analyzes pulsating pressures on the train surface as well as those of unsteady flow fields around the train. Computational results indicate that when the train passed the embankment air barrier, the head wave of air pressure full wave is more than the tail wave; the absolute value of negative wave is more than that of the positive wave, which is more obvious in the head train. When the train is passing the air barrier, pressure pulsation values at head train points are more than those at other points, while pressure changes most violently at the train bottom, and pressure values close to the air barrier are more than those points far from the air barrier. Pressure values at the cross section 1 were larger than those of other points. Pressure values at measurement points of the tail train ranked the second place, with the maximum negative pressure of 1253 Pa. Pressure change amplitudes and maximum negative pressure on the train surface are increased quickly, while pressure peak values on the high-speed train surface are in direct ratio to the running speed. With the increased speed of the high-speed train, when it is running in the embankment air barrier, the aerodynamic force and moment borne by each train body are increased sharply, while the head train suffers the most obvious influences of aerodynamic effects.

Atrazine, one of the most widespread herbicides in the world, is considered as an environmental estrogen and has potential carcinogenicity. In this study, atrazine was degraded on boron-fluorine co-doped TiO2 nanotube arrays (B, F-TiO2 NTAs), which had similar morphology with the pristine TiO2 NTAs. The structure and morphology of TiO2 nanotube samples were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and UV-visible diffuse reflectance spectroscopy (DRS). It showed that the decoration of fluorine and boron made both the absorption in the visible region enhanced and the band edge absorption shifted. The efficiency of atrazine degradation by B, F-TiO2 NTAs through photoelectrocatalysis was investigated by current, solution pH, and electrolyte concentration, respectively. The atrazine removal rate reached 76% through photoelectrocatalytic reaction by B, F-TiO2 NTAs, which was 46% higher than that under the photocatalysis process. Moreover, the maximum degradation rate was achieved at pH of 6 in 0.01 M of Na2SO4 electrolyte solution under a current of 0.02 A and visible light for 2 h in the presence of B, F-TiO2 NTAs. These results showed that B, F-TiO2 NTAs exhibit remarkable photoelectrocatalytic activity in degradation of atrazine.

The hierarchical porous heterostructured MIL-125/TiO2 @SiO2 composites are successfully obtained by biogenic-templated method using rice husk both as biomorphic. The products are characterized by X-ray diffraction, N2 -adsorption-desorption analysis, scanning electron microscopy and Fourier transform infrared spectroscopy. The results reveal that MIL-125/TiO2 @SiO2 possesses a hierarchical porous structure in scale from micrometer to nanometer with high Brunauer-Emmett-Teller (BET) surface area (385.7-902.7 m2 g-1 ). The photocatalytic mechanism was discussed in detail. Meanwhile, the activity of MIL-125/TiO2 @SiO2 for the photocatalytic degradation of rhodamine B in aqueous medium is significantly higher than that of P25. The current work provides some concept and methods in the development of MOF-based photocatalysts.