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Based on the data of the Chinese A-share listed firms in China Shanghai and Shenzhen Stock Exchange from 2014 to 2021, this article explores the relationship between common institutional investors and the quality of management earnings forecasts. The study used the multiple linear regression model and empirically found that common institutional investors positively impact the precision of earnings forecasts. This article also uses graph neural networks to predict the precision of earnings forecasts. Our findings have shown that common institutional investors form external supervision over restricting management to release a wide width of earnings forecasts, which helps to improve the risk warning function of earnings forecasts and promote the sustainable development of information disclosure from management in the Chinese capital market. One of the marginal contributions of this paper is that it enriches the literature related to the economic consequences of common institutional shareholding. Then, the neural network method used to predict the quality of management forecasts enhances the research method of institutional investors and the behavior of management earnings forecasts. Thirdly, this paper calls for strengthening information sharing and circulation among institutional investors to reduce information asymmetry between investors and management.

The stock market is an important part of the capital market, and the research on the price fluctuation of the stock market has always been a hot topic for scholars. As a dynamic and complex system, the stock market is affected by various factors. However, with the development of information technology, information presents multisource and heterogeneous characteristics, and the transmission speed and mode of information have changed greatly. The explanation and influence of multi-source and heterogeneous information on stock market price fluctuations need further study. In this paper, a graph fusion and embedding method for multi-source heterogeneous information of Chinese stock market is established. Relational dimension information is introduced to realize the effective fusion of multi-source heterogeneous data information. A multi-attention graph neural network based on nodes and semantics is constructed to mine the implied semantics of fusion graph data and capture the influence of multi-source heterogeneous information on stock market price fluctuations. Experiments show that the proposed multi-source heterogeneous information fusion methods is superior to tensor or vector fusion method, and the constructed multi-attention diagram neural network has a better ability to explain stock market price fluctuations.

The goal of this study was to select a representative cucurbit vegetable crop that contained the highest residue levels of the pesticide azoxystrobinon. To do this, we used open field application of azoxystrobinon in four cucurbit crops (cucumber, zucchini, bitter gourd, and loofah) in Beijing, Shandong, and Anhui. Liquid chromatograph-mass spectrometry/mass spectrometry (LC-MS/MS) with selected reaction monitoring was used to determine azoxystrobinon levels in each of the selected cucurbit vegetables. The azoxystrobinon limit of detection was 0.005 mg kg-1 for all samples. Recoveries of azoxystrobinon ranged from 94.2% to 107.1% at spiked levels of 0.005-0.5 mg kg-1. In field trials, the half-life of azoxystrobinon in each of the four cucurbit crops was within the range of 1.4-3.1 d. Based on these results, we recommend that bitter gourd is selected as a representative cucurbit vegetable for future studies of azoxystrobinon. The obtained residual data were also assessed for their dietary risk and results indicated that there is no chronic dietary risk in any of the four, selected cucurbit vegetables. The recommended maximum residue limit (MRL) of azoxystrobinon in this subgroup was 0.2 mg/kg.

Resilience is the individual's ability to bounce back from trauma. It has been studied for some time in the U.S., but few studies in China have addressed this important construct. In mainland China, relatively little is known about the resilience of patients in clinical settings, especially among patients with breast cancer. In this study, we aimed to evaluate the level of resilience and identify predictors of resilience among mainland Chinese women newly diagnosed with breast cancer.A cross-sectional descriptive study was conducted with 213 mainland Chinese women newly diagnosed with breast cancer between November 2014 and June 2015. Participants were assessed with the Connor-Davidson Resilience Scale (CD-RISC), Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire (MCMQ, including 3 subscales: confrontation, avoidance, and acceptance-resignation), Herth Hope Index (HHI), and demographic and disease-related information. Descriptive statistics, bivariate analyses and multiple stepwise regression were conducted to explore predictors for resilience.The average score for CD-RISC was 60.97, ranging from 37 to 69. Resilience was positively associated with educational level, family income, time span after diagnosis, social support, confrontation, avoidance, and hope. However, resilience was negatively associated with age, body mass index (BMI), and acceptance-resignation. Multiple stepwise regression analysis indicated that hope (β = 0.343, P

The possible signaling role of prokineticin 2 (PK2) and its receptor, prokineticin receptor 2 (PKR2), on female reproduction was investigated. First, the expression of PKR2 and its co-localization with estrogen receptor (ERα) in the hypothalamus was examined. Sexually dimorphic expression of PKR2 in the preoptic area of the hypothalamus was observed. Compared to the male mice, there was more widespread PKR2 expression in the preoptic area of the hypothalamus in the female mice. The likely co-expression of PKR2 and ERα in the preoptic area of the hypothalamus was observed. The estrous cycles in female PK2-null, and PKR2-null heterozygous mice, as well as in PK2-null and PKR2-null compound heterozygous mice were examined. Loss of one copy of PK2 or PKR2 gene caused elongated and irregular estrous cycle in the female mice. The alterations in the estrous cycle were more pronounced in PK2-null and PKR2-null compound heterozygous mice. Consistent with these observations, administration of a small molecule PK2 receptor antagonist led to temporary blocking of estrous cycle at the proestrous phase in female mice. The administration of PKR2 antagonist was found to blunt the circulating LH levels. Taken together, these studies indicate PK2 signaling is required for the maintenance of normal female estrous cycles.

Infiltration of myeloid cells in the tumor microenvironment is often associated with enhanced angiogenesis and tumor progression, resulting in poor prognosis in many types of cancer. The polypeptide chemokine PK2 (Bv8, PROK2) has been shown to regulate myeloid cell mobilization from the bone marrow, leading to activation of the angiogenic process, as well as accumulation of macrophages and neutrophils in the tumor site. Neutralizing antibodies against PK2 were shown to display potent anti-tumor efficacy, illustrating the potential of PK2-antagonists as therapeutic agents for the treatment of cancer. In this study we demonstrate the anti-tumor activity of a small molecule PK2 antagonist, PKRA7, in the context of glioblastoma and pancreatic cancer xenograft tumor models. For the highly vascularized glioblastoma, PKRA7 was associated with decreased blood vessel density and increased necrotic areas in the tumor mass. Consistent with the anti-angiogenic activity of PKRA7 in vivo, this compound effectively reduced PK2-induced microvascular endothelial cell branching in vitro. For the poorly vascularized pancreatic cancer, the primary anti-tumor effect of PKRA7 appears to be mediated by the blockage of myeloid cell migration/infiltration. At the molecular level, PKRA7 inhibits PK2-induced expression of certain pro-migratory chemokines and chemokine receptors in macrophages. Combining PKRA7 treatment with standard chemotherapeutic agents resulted in enhanced effects in xenograft models for both types of tumor. Taken together, our results indicate that the anti-tumor activity of PKRA7 can be mediated by two distinct mechanisms that are relevant to the pathological features of the specific type of cancer. This small molecule PK2 antagonist holds the promise to be further developed as an effective agent for combinational cancer therapy.

Human activities have greatly influenced the natural nitrogen cycle, causing dramatic degradation of ecosystem function. Net anthropogenic nitrogen input (NANI) is an important factor contributing to the impact of human activities on the regional nitrogen cycle. Here, we analyzed the temporal and spatial variation of NANI in the Pearl River Basin of China between 1986 to 2015, and found that the total amount of NANI significantly increased from 3,362.25 kg N km-2 yr-1 to 8,071.15 kg N km-2 yr-1. Application of nitrogen fertilizers was the largest component of NANI in the Basin, accounting for 55.53% in the total NANI, followed by food/feed net nitrogen input (21.26%), atmospheric nitrogen deposition (12.95%), and crop nitrogen fixation (10.26%). Over the last three decades, nitrogen inputs from atmospheric nitrogen deposition have become the second largest source of NANI due to rapid industrialization and urbanization in the region. Regression analysis showed that the rapid growth of both GDP and population density were the main contributors to the increase of NANI. In addition, the increase in the number of red tides in the Pearl River Estuary was strongly correlated with NANI discharge (R2 = 0.90, p

The purpose of this study was to evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) for synovial chondromatosis (SC) of the temporomandibular joint (TMJ). In this study, 1415 patients (2109 joints) with temporomandibular joint disorders were collected between January 2012 and January 2017. All patients had a preoperative MRI examination and were treated by either arthroscopy or open surgery. On reviewing all MRI images, the number of "positive", "suspicious", and "negative" cases was collected afterwards, then the number of reported SC cases in operative data was recorded. The SPSS software was used to process all collected data. The kappa coefficient and ROC curve (AUC-index) with sensitivity and specificity were calculated to evaluate the consistency between MRI and arthroscopy/open surgery. Compared to 156 joints with SC detected by arthroscopy and open surgery, the results of MRI examination showed "positive" in 117 joints, and "negative" in 1938 joints. The number of "true positive", and "true negative" cases was 95, and 1897 respectively. The AUC-index was 0.86 (0.82-0.90) with a kappa coefficient of 0.74 (P < 0.05). In conclusion, the incidence of synovial chondromatosis diagnosed on MRI was in accordance with the arthroscopic and open surgery. Therefore, being a relatively non-invasive tool, MRI could be recommended as an effective diagnostic modality for SC.

Along with the rapid development of Intelligent Transportation Systems, traffic data collection technologies have progressed fast. The emergence of innovative data collection technologies such as remote traffic microwave sensor, Bluetooth sensor, GPS-based floating car method, and automated license plate recognition, has significantly increased the variety and volume of traffic data. Despite the development of these technologies, the missing data issue is still a problem that poses great challenge for data based applications such as traffic forecasting, real-time incident detection, dynamic route guidance, and massive evacuation optimization. A thorough literature review suggests most current imputation models either focus on the temporal nature of the traffic data and fail to consider the spatial information of neighboring locations or assume the data follow a certain distribution. These two issues reduce the imputation accuracy and limit the use of the corresponding imputation methods respectively. As a result, this paper presents a Kriging based data imputation approach that is able to fully utilize the spatiotemporal correlation in the traffic data and that does not assume the data follow any distribution. A set of scenarios with different missing rates are used to evaluate the performance of the proposed method. The performance of the proposed method was compared with that of two other widely used methods, historical average and K-nearest neighborhood. Comparison results indicate that the proposed method has the highest imputation accuracy and is more flexible compared to other methods.

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

BackgroundEpidemiological studies evaluating treatments for infantile hemangiomas have produced inconsistent results. A meta-analysis of published data was conducted to investigate the effectiveness and safety of oral propranolol versus other treatments for infantile hemangiomas.MethodsA meta-analysis was conducted based on literature (published from 1960 to December 1, 2014) found on the PubMed, EMBASE, and OVID search engines. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the outcome measures. Heterogeneity, publication bias and subgroup analysis were performed.ResultsA total of 61 studies involving 5,130 participants met the inclusion criteria. Propranolol was found to be a more effective modality in treating IHs (ORs = 0.92; 95%CI, 0.89-0.95) and had fewer complications compared to the other treatments including systemic steroids (ORs = 0.68; 95% CI, 0.59-0.76); laser ablation (ORs = 0.55; 95% CI, 0.43-0.67); other beta-adrenergic blockers (ORs = 0.56; 95% CI, 0.50-0.61) and surgery (ORs = 0.55; 95% CI, 0.28-0.81). A subgroup analysis of propranolol showed that a dose of 2 mg/kg/day or more yielded better outcomes (ORs = 0.92; 95% CI, 0.88-0.95; ORs = 0.95; 95% CI, 0.89-1.00), and IHs that had not been previously treated had better responses to propranolol treatment (ORs = 0.95; 95% CI, 0.91-0.98).ConclusionsThe meta-analysis demonstrated that propranolol was more effective and safer than other therapies in treating IHs. It provides strong evidence for supporting the use of propranolol as a first-line therapy for IHs.

Multiple comprehensive in situ bio-optical investigations were conducted from 2005 to 2010 and covered a large variability of total suspended matter (TSM) in Lake Taihu to calibrate and validate a TSM concentration estimation model based on Medium Resolution Imaging Spectrometer (MERIS) data. The estimation model of the TSM concentration in Lake Taihu was developed using top-of-atmosphere (TOA) radiance of MERIS image data at band 9 in combination with a regional empirical atmospheric correction model, which was strongly correlated with the in situ TSM concentration (r(2) = 0.720, p

BACKGROUND: The rice white tip nematode Aphelenchoides besseyi, a devastating nematode whose genome has not been sequenced, is distributed widely throughout almost all the rice-growing regions of the world. The aims of the present study were to define the transcriptome of A. besseyi and to identify parasite-related, mortality-related or host resistance-overcoming genes in this nematode. METHODOLOGY AND PRINCIPAL FINDINGS: Using Solexa/Illumina sequencing, we profiled the transcriptome of mixed-stage populations of A. besseyi. A total of 51,270 transcripts without gaps were produced based on high-quality clean reads. Of all the A. besseyi transcripts, 9,132 KEGG Orthology assignments were annotated. Carbohydrate-active enzymes of glycoside hydrolases (GHs), glycosyltransferases (GTs), carbohydrate esterases (CEs) and carbohydrate-binding modules (CBMs) were identified. The presence of the A. besseyi GH45 cellulase gene was verified by in situ hybridization. Given that 13 unique A. besseyi potential effector genes were identified from 41 candidate effector homologs, further studies of these homologs are merited. Finally, comparative analyses were conducted between A. besseyi contigs and Caenorhabditis elegans genes to look for orthologs of RNAi phenotypes, neuropeptides and peptidases. CONCLUSIONS AND SIGNIFICANCE: The present results provide comprehensive insight into the genetic makeup of A. besseyi. Many of this species' genes are parasite related, nematode mortality-related or necessary to overcome host resistance. The generated transcriptome dataset of A. besseyi reported here lays the foundation for further studies of the molecular mechanisms related to parasitism and facilitates the development of new control strategies for this species.

CDOM biogeochemical cycle is driven by several physical and biological processes such as river input, biogeneration and photobleaching that act as primary sinks and sources of CDOM. Watershed-derived allochthonous (WDA) and phytoplankton-derived autochthonous (PDA) CDOM were exposed to 9 days of natural solar radiation to assess the photobleaching response of different CDOM sources, using absorption and fluorescence (excitation-emission matrix) spectroscopy. Our results showed a marked decrease in total dissolved nitrogen (TDN) concentration under natural sunlight exposure for both WDA and PDA CDOM, indicating photoproduction of ammonium from TDN. In contrast, photobleaching caused a marked increase in total dissolved phosphorus (TDP) concentration for both WDA and PDA CDOM. Thus TDN:TDP ratios decreased significantly both for WDA and PDA CDOM, which partially explained the seasonal dynamic of TDN:TDP ratio in Lake Taihu. Photobleaching rate of CDOM absorption a(254), was 0.032 m/MJ for WDA CDOM and 0.051 m/MJ for PDA CDOM from days 0-9, indicating that phototransformations were initially more rapid for the newly produced CDOM from phytoplankton than for the river CDOM. Extrapolation of these values to the field indicated that 3.9%-5.1% CDOM at the water surface was photobleached and mineralized every day in summer in Lake Taihu. Photobleaching caused the increase of spectral slope, spectral slope ratio and molecular size, indicating the CDOM mean molecular weight decrease which was favorable to further microbial degradation of mineralization. Three fluorescent components were validated in parallel factor analysis models calculated separately for WDA and PDA CDOM. Our study suggests that the humic-like fluorescence materials could be rapidly and easily photobleached for WDA and PDA CDOM, but the protein-like fluorescence materials was not photobleached and even increased from the transformation of the humic-like fluorescence substance to the protein-like fluorescence substance. Photobleaching was an important driver of CDOM and nutrients biogeochemistry in lake water.