Early Identification of the Jiangdingya Landslide of Zhouqu Based on SBAS-InSAR Technology

SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error,time-space decorrelation,atmospheric error,thereby improving the reliability of surface-deformation monitoring.This paper studies the early landslide identification method based on SBAS-InSAR technology.Selecting the Jiangdingya landslide area in Zhouqu County,Gansu Province as the research area,84 ascendingorbit Sentinel-1A SAR images from 2015 to 2019 are collected.In addition,using SBAS-InSAR technology,the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted,and potential landslides are identified.The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas.

Preliminary studies on the early quality identification of A uric ularia auricular

In production industry of Auricularia auricular, the varieties quality is most important impact factor on output. For evaluating the early quality of the edible fungus, 9 varieties of Auricularia auricular (Au9, CF09, CF05, 29, 916, chang10, chang7, Au.Japanese and 8808) were cultured on the medium consists of potato dextrose agar (PDA) and sawdust to test their mycelium growth rate, endurance to high temperature, resistance to mildew, assimilation of nutriment, and resistance to drought. The result showed that the mycelium of Chang 10, CF09, 29 and Au.Japanese varieties had the eminent characteristics such as short lifespan, stronger assimilation of nutriment, and endurance to high temperature and steady growth. These four varieties are determined as superiority varieties of Auricularia auricular in accordance with the research results.

Large-scale toppling slope under water level fluctuation of reservoir:A case of Yunnan Province,China

Landslides induced by reservoir inundation are common in Southwest China,negatively influencing hydropower stations.TheWunonglong hydropower station dam was constructed in the upper reaches of the Lancang River,accordingly causing the water level at the Lajinshengu slope to increase by 30 m.A tension crack with a visible depth of 8 m was observed in the upper sector of the Lajinshengu slope after reservoir impoundment for 170 d.In the following days,numerous cracks appeared on the surface of the slope,and the maximum displacement of the slope reached 3.22 m.Then,a large-scale active deformation body within the Lajinshengu slope formed with an area of 2.62×10^(5)m^(2)and a volume of 1.65×10^(7)m^(3).Detailed field investigations,on-site monitoring,and centrifugal model tests were carried out to analyze the surface features,deformation characteristics,and failure mechanism of the Lajinshengu slope.The results show that the slope is an ancient landslide,divided into two parts(i.e.zone A and zone B)by the gully.Zone B is a traction landslide caused by the displacement of zone A.The longterm inundation weakens the soft rock at the slope foot,intensifying the toppling of bedrock and consequently triggering the sliding of the overburden in zone A.The failure mode of the Lajinshengu slope is a typical case of toppling-sliding failure,and the underlying rock toppling drives the overlying sliding.In addition,early identification methods for toppling deformation covered by overburdened soil were proposed based on monitoring data and deformation signs.

Assessment of early factors for identification or prediction severe acute pancreatitis in pregnancy

BACKGROUND Acute pancreatitis in pregnancy(APIP)is a rare and serious condition,and severe APIP(SAPIP)can lead to pancreatic necrosis,abscess,multiple organ dysfunction,and other adverse maternal and infant outcomes.Therefore,early identification or prediction of SAPIP is important.AIM To assess factors for early identification or prediction of SAPIP.METHODS The clinical data of patients with APIP were retrospectively analyzed.Patients were classified with mild acute pancreatitis or severe acute pancreatitis,and the clinical characteristics and laboratory biochemical indexes were compared between the two groups.Logical regression and receiver operating characteristic curve analyses were performed to assess the efficacy of the factors for identification or prediction of SAPIP.RESULTS A total of 45 APIP patients were enrolled.Compared with the mild acute pancreatitis group,the severe acute pancreatitis group had significantly increased(P<0.01)heart rate(HR),hemoglobin,neutrophil ratio(NEUT%),and neutrophil–lymphocyte ratio(NLR),while lymphocytes were significantly decreased(P<0.01).Logical regression analysis showed that HR,NEUT%,NLR,and lymphocyte count differed significantly(P<0.01)between the groups.These may be factors for early identification or prediction of SAPIP.The area under the curve of HR,NEUT%,NLR,and lymphocyte count in the receiver operating characteristic curve analysis was 0.748,0.732,0.821,and 0.774,respectively.The combined analysis showed that the area under the curve,sensitivity,and specificity were 0.869,90.5%,and 70.8%,respectively.CONCLUSION HR,NEUT%,NLR,and lymphocyte count can be used for early identification or prediction of SAPIP,and the combination of the four factors is expected to improve identification or prediction of SAPIP.

Pediatric acute heart failure caused by endocardial fibroelastosis mimicking dilated cardiomyopathy:A case report

BACKGROUND Endocardial fibroelastosis(EFE)is a diffuse endocardial collagen and elastin hyperplasia disease of unknown etiology,which may be accompanied by myocardial degenerative changes leading to acute or chronic heart failure.However,acute heart failure(AHF)without obvious associated triggers is rare.Prior to the report of endomyocardial biopsy,the diagnosis and treatment of EFE are highly susceptible to being confounded with other primary cardiomyopathies.Here,we report a case of pediatric AHF caused by EFE mimicking dilated cardiomyopathy(DCM),with the aim of providing a valuable reference for clinicians to early identify and diagnose EFE-induced AHF.CASE SUMMARY A 13-mo-old female child was admitted to hospital with retching.Chest X-ray demonstrated enhanced texture in both lungs and an enlarged heart shadow.Color doppler echocardiography showed an enlarged left heart with ventricular wall hypokinesis and decreased left heart function.Abdominal color ultrasonography revealed a markedly enlarged liver.Pending the result of the endomyocardial biopsy report,the child was treated with a variety of resuscitative measures including nasal cannula for oxygen,intramuscular sedation with chlorpromazine and promethazine,cedilanid for cardiac contractility enhancement,and diuretic treatment with furosemide.Subsequently,the child’s endomyocardial biopsy report result was confirmed as EFE.After the above early interventions,the child’s condition gradually stabilized and improved.One week later,the child was discharged.During a 9-mo follow-up period,the child took intermittent low-dose oral digoxin with no signs of recurrence or exacerbation of the heart failure.CONCLUSION Our report suggests that EFE-induced pediatric AHF may present in children over 1 year of age without any apparent precipitants,and that the associated clinical presentations are grossly similar to that of pediatric DCM.Nonetheless,it is still possible to be diagnosed effectively on the basis of the comprehensive analysis of auxiliary inspection findings before the result of the endomyocardial biopsy is reported.

Development and external validation of models to predict acute respiratory distress syndrome related to severe acute pancreatitis

BACKGROUND Acute respiratory distress syndrome(ARDS)is a major cause of death in patients with severe acute pancreatitis(SAP).Although a series of prediction models have been developed for early identification of such patients,the majority are complicated or lack validation.A simpler and more credible model is required for clinical practice.AIM To develop and validate a predictive model for SAP related ARDS.METHODS Patients diagnosed with AP from four hospitals located at different regions of China were retrospectively grouped into derivation and validation cohorts.Statistically significant variables were identified using the least absolute shrinkage and selection operator regression method.Predictive models with nomograms were further built using multiple logistic regression analysis with these picked predictors.The discriminatory power of new models was compared with some common models.The performance of calibration ability and clinical utility of the predictive models were evaluated.RESULTS Out of 597 patients with AP,139 were diagnosed with SAP(80 in derivation cohort and 59 in validation cohort)and 99 with ARDS(62 in derivation cohort and 37 in validation cohort).Four identical variables were identified as independent risk factors for both SAP and ARDS:heart rate[odds ratio(OR)=1.05;95%CI:1.04-1.07;P<0.001;OR=1.05,95%CI:1.03-1.07,P<0.001],respiratory rate(OR=1.08,95%CI:1.0-1.17,P=0.047;OR=1.10,95%CI:1.02-1.19,P=0.014),serum calcium concentration(OR=0.26,95%CI:0.09-0.73,P=0.011;OR=0.17,95%CI:0.06-0.48,P=0.001)and blood urea nitrogen(OR=1.15,95%CI:1.09-1.23,P<0.001;OR=1.12,95%CI:1.05-1.19,P<0.001).The area under receiver operating characteristic curve was 0.879(95%CI:0.830-0.928)and 0.898(95%CI:0.848-0.949)for SAP prediction in derivation and validation cohorts,respectively.This value was 0.892(95%CI:0.843-0.941)and 0.833(95%CI:0.754-0.912)for ARDS prediction,respectively.The discriminatory power of our models was improved compared with that of other widely used models and the calibration ability and clinical utility of the prediction models performed adequately.CONCLUSION The present study constructed and validated a simple and accurate predictive model for SAPrelated ARDS in patients with AP.

Initiative to Improve the Health Outcomes of Those at Risk of Perinatal Depression: Referral Characteristics and Psychosocial Determinants

In Australia, perinatal depression affects 15% - 20% of pregnant women. Depression does not go away on its own, getting help at early stages shown to be effective in treating antenatal depression. Aim of this study is to assess and describe the screening of women through the antenatal clinic and measure the outcome of services provided (such as counselling, social assistance) for those at risk of depression, in a general hospital setting in an ethnically diverse part of Sydney, Australia. Data from 193 women were obtained through accessing the psychosocial and screening assessments completed at the antenatal clinic between 2007 and 2008. Data regarding patients’ psychosocial characteristics, referrals and interventions were also gathered from hospital records. Data revealed that 60.4% of women screened scored ≥10 on the Edinburgh Postnatal Depression Scale (EDPS) which is indicative of significant depressive symptomatology. Of these women, 39.4% went on to receive a formal diagnosis. Women who indicated that they had planned their pregnancies (47.2%) were significantly less likely to report having major worries and stressors over the last 12 months (p < 0.05) in comparison to those who indicated that their pregnancies were unplanned. Data showed while screening methods are effective, regrettably a high proportion of women, despite presenting with “at risk” symptomatology levels, do not engage in intervention programs. Further research is required to explore the barriers in accessing both screening and intervention services (particularly in a culturally diverse area such as this), and how services can improve processes and patient participation.