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Background Bronchiectasis is a highly heterogeneous chronic airway disease with marked geographic and ethnic variations. Most influential cohort studies to date have been performed in Europe and USA, which serve as the examples for developing a cohort study in China where there is a high burden of bronchiectasis. The Establishment of China Bronchiectasis Registry and Research Collaboration (BE-China) is designed to: (1) describe the clinical characteristics and natural history of bronchiectasis in China and identify the differences of bronchiectasis between the western countries and China; (2) identify the risk factors associated with disease progression in Chinese population; (3) elucidate the phenotype and endotype of bronchiectasis by integrating the genome, microbiome, proteome, and transcriptome with detailed clinical data; (4) facilitate large randomized controlled trials in China. Methods The BE-China is an ongoing prospective, longitudinal, multi-center, observational cohort study aiming to recruit a minimum of 10,000 patients, which was initiated in January 2020 in China. Comprehensive data, including medical history, aetiological testing, lung function, microbiological profiles, radiological scores, comorbidities, mental status, and quality of life (QoL), will be collected at baseline. Patients will be followed up annually for up to 10 years to record longitudinal data on outcomes, treatment patterns and QoL. Biospecimens, if possible, will be collected and stored at − 80 °C for further research. Up to October 2021, the BE-China has enrolled 3758 patients, and collected 666 blood samples and 196 sputum samples from 91 medical centers. The study protocol has been approved by the Shanghai Pulmonary Hospital ethics committee, and all collaborating centers have received approvals from their local ethics committee. All patients will be required to provide written informed consent to their participation. Conclusions Findings of the BE-China will be crucial to reveal the clinical characteristics and natural history of bronchiectasis and facilitate evidence-based clinical practice in China. Trial registration Registration Number in ClinicalTrials.gov: NCT03643653

Increasing numbers of SARS-CoV-2-positive (SARS-CoV-2pos) subjects are detected at silent SARS-CoV-2 infection stage (SSIS). Yet, SSIS represents a poorly examined time-window wherein unknown immunity patterns may contribute to the fate determination towards persistently asymptomatic or overt disease. Here, we retrieved blood samples from 19 asymptomatic and 12 presymptomatic SARS-CoV-2pos subjects, 47 age/gender-matched patients with mild or moderate COVID-19 and 27 normal subjects, and interrogated them with combined assays of 44-plex CyTOF, RNA-seq and Olink. Notably, both asymptomatic and presymptomatic subjects exhibited numerous readily detectable immunological alterations, while certain parameters including more severely decreased frequencies of CD107alow classical monocytes, intermediate monocytes, non-classical monocytes and CD62Lhi CD8+ Tnaïve cells, reduced plasma STC1 level but an increased frequency of CD4+ NKT cells combined to distinguish the latter. Intercorrelation analyses revealed a particular presymptomatic immunotype mainly manifesting as monocytic overactivation and differentiation blockage, a likely lymphocyte exhaustion and immunosuppression, yielding mechanistic insights into SSIS fate determination, which could potentially improve SARS-CoV-2 management.

Background: Left ventricular thrombus (LVT) can complicate ST-Elevation myocardial infarction (STEMI) and is associated with poor outcomes. Conventional triple anticoagulation [Vitamin K Antagonists (VKA) plus dual-antiplatelet therapy (DAPT)] is the first-line therapy for LVT after STEMI. In patients with LVT following STEMI, contemporary data of triple therapy with rivaroxaban are lacking. Methods: We conducted a retrospective cohort study involving 1335 STEMI patients who underwent primary percutaneous coronary intervention (PCI). Among patients who developed LVT after STEMI, we observed differences in efficacy between rivaroxaban plus DAPT therapy and VKA plus DAPT. The time of LVT resolution was also evaluated, as well as net clinical adverse events, and rates of bleeding events. Results: In 1335 patients with STEMI, a total of 77 (5.7%) developed LVT over the follow-up period (median 25.0 months). Of the patients diagnosed with LVT, 31 patients were started on triple therapy with VKA, 33 patients on triple therapy with rivaroxaban. There was a consistent similarity in LVT resolution with rivaroxaban application compared to VKA application during the follow-up period [HR (log-rank test) 1.57(95% CI 0.89–2.77), p = 0.096; Adjusted HR 1.70(95% CI 0.90–3.22), p = 0.104]. Triple therapy with rivaroxaban showed quicker resolution than with VKA (6 months: p = 0.049; 12 months: p = 0.044; 18 months: p = 0.045). Similar risks of ISTH bleeding were not significantly different between the 2 groups [VKA 9.7% vs Rivaroxaban 6.1%, Adjusted HR 0.48 (95% CI 0.73–3.20); p = 0.444)]. Fewer net adverse clinical events (NACE) were observed in the rivaroxaban group [VKA 58.1% vs Rivaroxaban 24.2%; HR (log-rank test) 0.31(95% CI 0.14–0.68), p = 0.003; Adjusted HR 0.23(95% CI 0.09–0.57), p = 0.001]. Conclusion: In the observational study, triple therapy with rivaroxaban has similar and quicker LVT resolution in patients with LVT after STEMI, compared with triple therapy with VKA, and perhaps was associated with a better clinical benefit. Larger sample sizes and randomized controlled trials are needed to confirm this observation.

A structure scheme of a pile-based breakwater with integrated oscillating water column (OWC) energy conversion chamber was proposed, and four structure forms had been designed. Based on the physical test, the variations of the reflected wave height, the transmitted wave height, the air velocity at the outlet of the chamber, the air pressure and the wave height in the air chamber were studied under the conditions of different wave heights, periods, with or without elliptical front wall and the baffles on both sides of the chamber. Moreover, based on the results, the changes and relationship between the wave-eliminating effect and energy conversion effect of the scheme were analyzed. In general, it turns out, the transmission coefficients of the four structure forms are kept below 0.5. Furthermore, the transmission coefficients of the structural forms G2, G3, and G4 were all smaller than 0.4, and it is only 0.1 at its smallest. Thereinto, in general, the structure form G4 has the best wave-eliminating and energy conversion performance. At the same time, when the wave steepness is 0.066, the energy conversion and wave dissipation effect of the four structure forms is the best. The research results could be provided as the reference for the design structure selection of pile-based breakwater with integrated OWC energy conversion chamber.

To improve students' performance effectively, many Chinese universities are establishing systems to predict student's academic performance and sending student's academic early alerts. With student's population of over 600,000, Chinese-foreign cooperation in running schools (CFCRS) has become one of the booming higher education forms in China. Compared with students in the non-cooperatively running programs, CFCRS students' academic performances are weaker on average. To predict the academic-at-risk students and provide efficient supports to the students, a precise and prompt academic prediction is in great need. Therefore, this research aims at representing a more efficient and accurate model to predict academic performance of CFCRS students which will be based on graph convolutional network. In this research, student's similarity is measured on academic performance by Pearson correlation coefficient. An undirected graph in which similar students are connected is conducted. Feature matrix is composed of students' previous grades. In addition, graph convolutional network is trained based on the undirected graph and feature matrix. In the experiment, it shows that this model predicts certain student's performance on certain course from the final exam results in previous semesters, which might improve learning efficiency and teaching quality. With an average accuracy of 81.5%, graph convolutional network outperforms support vector machine and random forest models.

Background Secondary hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening hyperinflammatory event and a fatal complication of viral infections. Whether sHLH may also be observed in patients with a cytokine storm induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still uncertain. We aimed to determine the incidence of sHLH in severe COVID-19 patients and evaluate the underlying risk factors. Method Four hundred fifteen severe COVID-19 adult patients were retrospectively assessed for hemophagocytosis score (HScore). A subset of 7 patients were unable to be conclusively scored due to insufficient patient data. Results In 408 patients, 41 (10.04%) had an HScore ≥169 and were characterized as “suspected sHLH positive”. Compared with patients below a HScore threshold of 98, the suspected sHLH positive group had higher D-dimer, total bilirubin, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, serum creatinine, triglycerides, ferritin, interleukin-6, C-reactive protein, procalcitonin, lactate dehydrogenase, creatine kinase isoenzyme, troponin, Sequential Organ Failure Assessment (SOFA) score, while leukocyte, hemoglobin, platelets, lymphocyte, fibrinogen, pre-albumin, albumin levels were significantly lower (all P 1922.58 ng/mL), low platelets (9/L) and high triglycerides (>2.28 mmol/L) were independent risk factors for suspected sHLH in COVID-19 patients. Importantly, COVID-19 patients that were suspected sHLH positive had significantly more multi-organ failure. Additionally, a high HScore (>98) was an independent predictor for mortality in COVID-19. Conclusions HScore should be measured as a prognostic biomarker in COVID-19 patients. In particular, it is important that HScore is assessed in patients with high ferritin, triglycerides and low platelets to improve the detection of suspected sHLH.

Knowledge advantage machine (KaM) is an advanced system for knowledge exploitation. In this paper, we propose a Collaboration Centric Behavior Model, which helps one or more knowledge-workers to discover and link useful knowledge objects dubbed JANs into a semantic knowledge network. The JAN is constructed as a semantic web service to semantically present three categories of service behavior: expected service behavior that presents what requestor expects it to serve; actual service behavior that presents how it offers its service; and quality evaluation that presents whether its service behavior is consistent with requestor’s expectation by checking conformance. On the basis of the KaM architecture, we build a process model to implement to discovery a JAN and link different JANs as a personal knowledge network or a group knowledge network. This is illustrated using an academic research scenario. Experimental results show that the proposed method is feasible and effective.

With the development of social information technology and the increasing of information data in big data era, how to query the required data accurately is becoming more and more important, the purpose of this paper is to establish a model of data mining technology. In this paper, we use the Bayesian network learning model to study the data mining technology. In this paper, a Bayesian network learning model is established, then, the parameters of the recognition and the selection of coefficients are analyzed in detail, after that, the data mining model based on Bayesian computation is deduced, and the reliability of the model is verified by the example of the students. The probability distribution pattern used by Bayes has many advantages in data mining. It further proves the applicability of Bayesian formula, and provides a reference for data mining technology.

The original version of this article unfortunately contained a mistake. There was a typographical error in Figure 1: “Nebulization time ≤ 30 min” (first light blue square) should be replaced by “Nebulization time ≤ 90 min”. The authors apologize for the mistake.

One of the concerns about the use of Bluetooth MAC Scanner (BMS) data, especially from urban arterial, is the bias in the travel time estimates from multiple Bluetooth devices being transported by a vehicle. For instance, if a bus is transporting 20 passengers with Bluetooth equipped mobile phones, then the discovery of these mobile phones by BMS will be considered as 20 different vehicles, and the average travel time along the corridor estimated from the BMS data will be biased with the travel time from the bus. This paper integrates Bus Vehicle Identification system with BMS network to empirically evaluate such bias, if any. The paper also reports an interesting finding on the uniqueness of MAC-IDs.

To obtain accurate search results and advocate the use of human effort in discovering knowledge, we propose a method based on Ant Colony Algorithm (ACA). The proposed method simulates the behavior of ants searching for food. Specific features such as the behavior of ants searching for food, their established search paths, and the ant “neighborhood” profile are investigated. The investigation results reveal that the behavior of people searching for useful information resembles that of ants searching for food. We also use semantic annotation and the decreasing matrix dimension approach to accelerate the food searching process and shorten the distance between the query starting points and the ultimate answers. A user behavior model is constructed based on personal and domain ontologies. Experimental evaluation with the enhanced ACA has two parts: (1) estimating the efficiency of information retrieval with user interests considered and (2) identifying how to weigh usage and rate user data during recommendation.

The endotoxin tolerance phenotype is characterized with decreased inflammation and increased phagocytosis. We hypothesized that endotoxin tolerance would provide protective effects on experimental sepsis with multiple organ injuries induced by cecal ligation and puncture (CLP). Endotoxin tolerance was induced in male Sprague–Dawley rats with daily intraperitoneal injection of either 0.6 mg/kg of lipopolysaccharide (LPS) or vehicle for four consecutive days before subsequent CLP. Biochemical parameters, histological changes, inflammatory cytokine production, and lung tissue nuclear factor-κB (NF-κB) activation were assessed post-CLP. In a separate experiment, survival rate was monitored for 7 days after CLP. In vehicle-treated animals, CLP caused multiple organ injuries confirmed by the biochemical variables and histological examination. This was accompanied by an early activation of NF-κB in the lung and a substantial increase in plasma levels of tumor necrosis factor-α, interleukin-6, and interleukin-10. In contrast, pretreatment with LPS not only alleviated the development of multiple organ injuries after CLP, but also decreased sepsis-induced activation of pulmonary NF-κB and reduced plasma cytokines production. In addition, LPS pretreatment improved the survival in rats subjected to CLP. The beneficial effects of endotoxin tolerance indicate the potential of immunomodulatory strategies in the management of severe sepsis.

In the past several years, increasing attention has been paid to the utility of a pseudocapsule in transphenoidal surgery for pituitary adenomas. However, prior studies focused more on the histological structure of the pseudocapsule and surgical technique. The objective of this study was to evaluate the overall therapeutic effectiveness of transsphenoidal pseudocapsule-based extracapsular resection for pituitary adenomas.Between January 2004 and October 2007, 78 patients with pituitary adenomas underwent transsphenoidal pseudocapsule-based extracapsular removal surgery (extracapsular resection group, ER group). During the same period, 64 patients underwent transsphenoidal intracapsular resection operations (intracapsular resection group, IR group).Complete resection rates were achieved in 90.6%, 84.6% and 65.5%, 52.6% of modified Hardy types II and III in the ER and IR groups, showing a significant difference (both P 0.05). Statistical significance in the remission rates was also found between the two groups with modified Hardy types II and III, respectively (both P 0.05). Complications occurred in 29.5% of the ER group and 26.6% of the IR group, with no difference between groups (P 0.05). The recurrence rate of the ER group (2.56%) was lower than that of the IR group (14.06%).The transsphenoidal pseudocapsule-based extracapsular resection approach provides a more effective and safe alternative compared to the traditional intracapsular one because of its higher tumor removal and remission rates, and lower recurrence rate.

Aim: To determine if NOD2 is involved in host recognition of Aspergillus fumigatus ( Af ) conidia. Methods: An Af conidia pulmonary infection murine model was established by intranasal inoculation of Af onidia suspensions. Protein levels of NOD2 in lung tissue were determined by immunohistochemistry. A549 and phorbol-12-myristate 13-acetate (PMA)-activated THP-1 cell lines were treated with heat-killed Af conidia, then the presence of NOD2 protein in these cell lines was detected by Western blotting. The ability of muramyl dipeptide (MDP) to induce the secretion of TNF-α after incubation with heat-killed Af conidia was measured by enzyme-linked immunosorbent assay. Results: The expression of NOD2 protein in lung tissue increased after Af conidia infection. Heat-killed Af conidia significantly upregulated NOD2 protein expression in A549 cells and PMA-activated THP-1 cells. Additionally, Af conidia in conjuction with MDP, significantly increased the secretion of TNF-α in A549 cells and PMA-activated THP-1 cells. Conclusion: Af conidia upregulates NOD2 protein expression in vitro / and in vivo . These findings indicate that NOD2 protein may respond to Af conidia.

We present an automatic algorithm to detect, characterize, and classify coronal mass ejections (CMEs) in Large Angle Spectrometric Coronagraph (LASCO) C2 and C3 images. The algorithm includes three steps: (1) production running difference images of LASCO C2 and C3; (2) characterization of properties of CMEs such as intensity, height, angular width of span, and speed, and (3) classification of strong, median, and weak CMEs on the basis of CME characterization. In this work, image enhancement, segmentation, and morphological methods are used to detect and characterize CME regions. In addition, Support Vector Machine (SVM) classifiers are incorporated with the CME properties to distinguish strong CMEs from other weak CMEs. The real-time CME detection and classification results are recorded in a database to be available to the public. Comparing the two available CME catalogs, SOHO/LASCO and CACTus CME catalogs, we have achieved accurate and fast detection of strong CMEs and most of weak CMEs.

The old reservoir areas built in 1950s–1970s left behind many socio-economic problems, because of the administrative backward migration and little migration fund, and all these problems would be tied to land. Based on interviewing with peasant households, combining land use survey and socio-economic statistical index, this paper analyzed land use change and its corresponding driving forces in Linshui reservoir area of Dahonghe Reservoir. Results showed that land use change in the reservoir area was mainly embodied on low-lying land submergence and migration requisition land. The former changed the land use patterns, and the latter mainly reconstructed original land property and made land over-fragmented. Cultivated land per capita was 0.041ha this area, below the cordon of cultivated land per capita enacted by FAO. Currently, there were still 30.25% of peasant households being short of grain in trimester of one year, and there were 35.27% of people living under the poverty line. The conditions of eco-environment in Linshui Reservoir Area were worse, and healthy and sub-healthy eco-environment accounted for less proportion, composed of green belt around the reservoir area and paddy field ecosystem, and economic forest and orchard ecosystem, respectively. The stress of the reservoir project was macroscopic background to analyze the driving factors of land use change, and real underlying diving factor of the land use change in the area was the change of cultural landscape under the stress of reservoir project. The rapid increase of population was the key factor to induce the change of man-land relationship in the reservoir area, the low level of rural economy was the crucial factor to decide how migrants input for production, and the belief of migrants, influencing the land use patterns in a certain extent, was the inducing factor to keep land use stable. The low-lying submergence and infrastructure construction accompanied the reservoir project were leading factors driving land use change in the area, while changes in land use patterns, after the reservoir being built, were the responses of peasant households’ behaviors to land use change.

We present an automatic solar filament detection algorithm based on image enhancement, segmentation, pattern recognition, and mathematical morphology methods. This algorithm cannot only detect filaments, but can also identify spines, footpoints, and filament disappearances. It consists of five steps: (1) The stabilized inverse diffusion equation (SIDE) is used to enhance and sharpen filament contours. (2) A new method for automatic threshold selection is proposed to extract filaments from local background. (3) The support vector machine (SVM) is used to differentiate between sunspots and filaments. (4) Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are used to determine the filament properties. (5) Finally, we propose a filament matching method to detect filament disappearances. We have successfully applied the algorithm to Hα full-disk images obtained at Big Bear Solar Observatory (BBSO). It has the potential to become the foundation of an automatic solar filament detection system, which will enhance our capabilities of forecasting and predicting geo-effective events and space weather.

Measurement of the evolution properties of solar flares through their complete cyclic development is crucial in the studies of Solar Physics. From the analysis of solar Hα images, we used Support Vector Machines (SVMs) to automatically detect flares and applied image segmentation techniques to compute their properties. We also present a solution for automatically tracking the apparent separation motion of two-ribbon flares and measuring their moving direction and speed in the magnetic fields. From these measurements, with certain assumptions, we inferred the reconnection of the electric field as a measure of the rate of the magnetic reconnection in the corona. The automatic procedure is a valuable tool for real-time monitoring of flare evolution.

The focus of automatic solar-flare detection is on the development of efficient feature-based classifiers. The three principal techniques used in this work are multi-layer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM) classifiers. We have experimented and compared these three methods for solar-flare detection on solar Hα images obtained from the Big Bear Solar Observatory in California. The preprocessing step is to obtain nine principal features of the solar flares for the classifiers. Experimental results show that by using SVM we can obtain the best classification rate of the solar flares. We believe our work will lead to real-time solar-flare detection using advanced pattern recognition techniques.

Metal complexes of a new thiosemicarbazone derived from 3-acetylumbelliferone (HL) have been prepared and characterized. The complexes have the general formula ML2 · nH2O where MII = Co, Ni, Cu and Zn; n = 0 and 2. The ligand and its complexes have been studied for their possible antitumour activity against HL-60 human leukemia in vitro.