Effectiveness of antibiotic prophylaxis for acute esophageal variceal bleeding in patients with band ligation: A large observational study

BACKGROUND Esophageal variceal bleeding is a severe complication associated with liver cirrhosis and typically necessitates endoscopic hemostasis.The current standard treatment is endoscopic variceal ligation(EVL),and Western guidelines recom-mend antibiotic prophylaxis following hemostasis.However,given the impro-vements in prognosis for variceal bleeding due to advancements in the management of bleeding and treatments of liver cirrhosis and the global concerns regarding the emergence of multidrug-resistant bacteria,there is a need to reassess the use of routine antibiotic prophylaxis after hemostasis.AIM To evaluate the effectiveness of antibiotic prophylaxis in patients treated for EVL.METHODS We conducted a 13-year observational study using the Tokushukai medical database across 46 hospitals.Patients were divided into the prophylaxis group(received antibiotics on admission or the next day)and the non-prophylaxis group(did not receive antibiotics within one day of admission).The primary outcome was composed of 6-wk mortality,4-wk rebleeding,and 4-wk spontaneous bacterial peritonitis(SBP).The secondary outcomes were each individual result and in-hospital mortality.A logistic regression with inverse probability of treatment weighting was used.A subgroup analysis was conducted based on the Child-Pugh classification to determine its influence on the primary outcome measures,while sensitivity analyses for antibiotic type and duration were also performed.RESULTS Among 980 patients,790 were included(prophylaxis:232,non-prophylaxis:558).Most patients were males under the age of 65 years with a median Child-Pugh score of 8.The composite primary outcomes occurred in 11.2%of patients in the prophylaxis group and 9.5%in the non-prophylaxis group.No significant differences in outcomes were observed between the groups(adjusted odds ratio,1.11;95%confidence interval,0.61-1.99;P=0.74).Individual outcomes such as 6-wk mortality,4-wk rebleeding,4-wk onset of SBP,and in-hospital mortality were not significantly different between the groups.The primary outcome did not differ between the Child-Pugh subgroups.Similar results were observed in the sensitivity analyses.CONCLUSION No significant benefit to antibiotic prophylaxis for esophageal variceal bleeding treated with EVL was detected in this study.Global reassessment of routine antibiotic prophylaxis is imperative.

INVERSE POWER METHOD AND WEIGHTED SOBOLEV SPACES

1. Introduction This paper is a continuation of the paper [5]. Now we want to treat the problem

Research on infrared dim and small target detection algorithm based on low-rank tensor recovery

In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detection algorithm of infrared small and dim target is proposed in this paper.Firstly,the original infrared images are changed into a new infrared patch tensor mode through data reconstruction.Then,the infrared small and dim target detection problems are converted to low-rank tensor recovery problems based on tensor nuclear norm in accordance with patch tensor characteristics,and inverse variance weighted entropy is defined for self-adaptive adjustment of sparseness.Finally,the low-rank tensor recovery problem with noise is solved by alternating the direction method to obtain the sparse target image,and the final small target is worked out by a simple partitioning algorithm.The test results in various spacebased downward-looking complex scenes show that such method can restrain complex background well by virtue of rapid arithmetic speed with high detection probability and low false alarm rate.It is a kind of infrared small and dim target detection method with good performance.

IFCEM based recognition method for target with interval-overlapped hybrid attributes

When the attributes of unknown targets are not just numerical attributes,but hybrid attributes containing linguistic attributes,the existing recognition methods are not effective.In addition,it is more difficult to identify the unknown targets densely distributed in the feature space,especially when there is interval overlap between attribute measurements of different target classes.To address these problems,a novel method based on intuitionistic fuzzy comprehensive evaluation model(IFCEM)is proposed.For numerical attributes,targets in the database are divided into individual classes and overlapping classes,and for linguistic attributes,continuous interval-valued linguistic term set(CIVLTS)is used to describe target characteristic.A cloud modelbased method and an area-based method are proposed to obtain intuitionistic fuzzy decision information of query target on numerical attributes and linguistic attributes respectively.An improved inverse weighted kernel fuzzy c-means(IWK-FCM)algorithm is proposed for solution of attribute weight vector.The possibility matrix is applied to determine the identity and category of query target.Finally,a case study composed of parameter sensitivity analysis,recognition accuracy analysis.and comparison with other methods,is taken to verify the superiority of the proposed method.

Water Quality Evaluation of Chapurson Valley in Hunza Nagar, Gilgit Baltistan, Pakistan, Based on Statistical Analysis and Water Quality Index

Water borne ailments are of serious public health concern in Gilgit Baltistan’s (GB) region of Pakistan. The pollution load on the glacio-fluvial streams and surface water resources of the Chapurson Valley in the Hunza Nagar area of the GB is increasing as a result of anthropogenic activities and tourism. The present study focuses on the public health quality of drinking water of Chapurson valley. The study addressed the fundamental drinking water quality criteria in order to understand the state of the public health in the valley. To ascertain the current status of physico-chemical, metals, and bacteriological parameters, 25 water samples were collected through deterministic sampling strategy and examined accordingly. The physico-chemical parameters of the water samples collected from the valley were found to meet the World Health Organization (WHO) guidelines of drinking water. The water samples showed a pattern of mean metal concentrations in order of Arsenic (As) > Lead (Pb) > Iron (Fe) > Zinc (Zn) > Copper (Cu) > Magnesium (Mg) > Calcium (Ca). As, Cu, Zn, Ca and Mg concentration were under the WHO guidelines range. However, results showed that Pb and Fe are present at much higher concentrations than recommended WHO guidelines. Similarly, the results of the bacteriological analysis indicate that the water samples are heavily contaminated with the organisms of public health importance (including total coliforms (TCC), total faecal coliforms (TFC) and total fecal streptococci (TFS) are more than 3 MPN/100mL). Three principal components, accounting for 48.44% of the total variance, were revealed using principal component analysis (PCA). Bacteriological parameters were shown to be the main determinants of the water quality as depicted by the PCA analysis. The dendrogram of Cluster analysis using the Ward’s method validated the same traits of the sampling locations that were found to be contaminated during geospatial analysis using the Inverse Distance Weight (IDW) method. Based on these findings, it is most likely that those anthropogenic activities and essentially the tourism results in pollution load from upstream channels. Metals may be released into surface and groundwater from a few underlying sources as a result of weathering and erosion. This study suggests that the valley water resources are more susceptible to bacteriological contamination and as such no water treatment facilities or protective measure have been taken to encounter the pollution load. People are drinking the contaminated water without questioning about the quality. It is recommended that the water resources of the valley should be monitored using standard protocol so as to protect not only the public health but to safe guard sustainable tourism in the valley.

Using WGM2012 to Compute Gravity Anomaly Corrections of Leveling Observations in China

Gravity Anomaly Correction(GAC)is a very important term in leveling data processing.In most cases,it is troublesome for field surveyors to measure gravity when leveling.In this paper,based on the complete Bouguer Gravity Anomaly(BGA)map of WGM2012,the feasibility of replacing in-situ gravity surveying in China is investigated.For leveling application,that is to evaluate the accuracy of WGM2012 in China.Because WGM2012 is organized with a standard rectangle grid,two interpolation methods,bilinear interpolating and Inverse Distance Weighted(IDW)interpolating,are proposed.Four sample areas in China,i.e.,Hanzhong,Chengdu,Linzhi and Shantou,are selected to evaluate the systems bias and precision of WGM2012.Numerical results show the average system bias of WGM2012 BGA in west China is about-100.1 mGal(1 mGal=10^(-5) m/s^(2))and the standard deviation is about 30.7 mGal.Tests in Shantou indicate the system bias in plain areas is about-130.4 mGal and standard deviation is about 6.8 mGal.All these experiments means the accuracy of WGM2012 is limited in high mountain areas of western China,but in plain areas,such as Shantou,WGM2012 BGA map is quite good for most leveling applications after calibrating the system bias.

Predicting portal venous anomalies by left-sided gallbladder or rightsided ligamentum teres hepatis: A large scale, propensity scorematched study

BACKGROUND Right-sided ligamentum teres(RSLT)is often associated with portal venous anomalies(PVA)and is regarded as a concerning feature for hepatobiliary intervention.Most studies consider RSLT to be one of the causes of left-sided gallbladder(LGB),leading to the hypothesis that LGB must always be present with RSLT.However,some cases have shown that right-sided gallbladder(RGB)can also be present in livers with RSLT.AIM To highlight the rare variation that RSLT may not come with LGB and to determine whether ligamentum teres(LT)or gallbladder location is reliable to predict PVA.METHODS This study retrospectively assessed 8552 contrast-enhanced abdominal computed tomography examinations from 2018 to 2021[4483 men,4069 women;mean age,59.5±16.2(SD)years].We defined the surrogate outcome as major PVAs.The cases were divided into 4 subgroups according to gallbladder and LT locations.On one hand,we analyzed PVA prevalence by LT locations using gallbladder location as a controlled variable(n=36).On the other hand,we controlled LT location and computed PVA prevalence by gallbladder locations(n=34).Finally,we investigated LT location as an independent factor of PVA by using propensity score matching(PSM)and inverse probability of treatment weighting(IPTW).RESULTS We found 9 cases of RSLT present with RGB.Among the LGB cases,RSLT is associated with significantly higher PVA prevalence than typical LT[80.0%vs 18.2%,P=0.001;OR=18,95%confidence interval(CI):2.92-110.96].When RSLT is present,we found no statistically significant difference in PVA prevalence for RGB and LGB cases(88.9%vs 80.0%,P>0.99).Both PSM and IPTW yielded balanced cohorts in demographics and gallbladder locations.The RSLT group had a significantly higher PVA prevalence after adjusted by PSM(77.3%vs 4.5%,P<0.001;OR=16.27,95%CI:2.25-117.53)and IPTW(82.5%vs 4.7%,P<0.001).CONCLUSION RSLT doesn't consistently coexist with LGB.RSLT can predict PVA independently while the gallbladder location does not serve as a sufficient predictor.

GIS Mapping, Biomonitoring and Distribution of Heavy Metal Concentrations Using Neem (Azadirachta indica) Bark in Makurdi Town, Benue State, Nigeria

The present work determined the concentration and spatial distribution of heavy metals (As, Hg, Cr, Cd and Pb) in soil samples from Makurdi and its environs using geographic information system (GIS). The specific objective is to produce the spatial distribution maps showing the spatial distribution of toxic heavy metals in the study area. Inverse Distance Weighting (IDW), a GIS technique was used to produce dotted maps showing the spatial distribution of heavy metals in neem bark for better visualization of contamination zones and non-contamination zones. The map reveals few hotspot areas showing areas of high concentrations of the heavy metals investigated which were identified in red colours, the following concentration ranges were obtained;As (4.71 - 6.43 mg/kg), Cd (13.9 - 16.84 mg/kg), Cr (46.3 - 60.84 mg/kg), Hg (3.70 - 5.05 mg/kg) and Pb (24.02 - 31.34 mg/kg). These hotspot areas were found close to business outlets, fuel filling and service stations, farm sites where the application of fertilizers and pesticides were persistent coupled with heavy traffic of vehicles and other machinery which was associated with As, Hg, Cd, Pb and Cr been released into the environment thus, suggesting anthropogenic activities controlling the concentration of these heavy metals in the study areas. The cumulative effect of these heavy metals into the barks of neem could pose as danger, because this plant is used as herbs in folk medicine.

Temporal Variations in Mortality after Liver Transplantation: Retrospective Investigation of Potential Risk Factors Using Propensity Score

Objective: We aim to detect over-time variations in mortality of liver transplant recipients stratified by the period of transplant. Since this is a retrospective investigation, bias reduction caused by possible confounding effects can be achieved by using propensity score weighting in a multivariate logistic regression model. Methods: Medical charts of all adult liver transplant recipients (n = 250) who were transplanted in three periods 2005-2009, 2010-2014 and 2015-2019 were retrospectively reviewed. The following recipient factors were analyzed: recipients and donors’ ages, sex, renal impairment, body mass index (BMI), presence of bacterial or viral infections, MELD (Model for end-stage diseases). Multivariate logistic model adjusted by Propensity Scores (PS) was used to identify the effect of the risk factors on mortality, and death within five years, in the targeted time frame. Patient outcomes are recorded as;(patient status = 1 if dead, or patient status = 0 if alive). Results: Meld score, recipient age, and renal impairments were shown to be predictors of mortality in transplanted patients. Multivariate regression model was used to identify the significance of the specified risk factors, followed by pairwise comparisons between periods. Pairwise comparisons between periods using logistic regression weighted by the inverse propensity score, correcting for the possible confounding effect of measured covariates showed that the death rate is significantly reduced in subsequent periods as compared to the initial period. Conclusions: The clinical implications of these findings are the ability to stratify patients at high risk of posttransplant death by planning more intensive and accurate management for them.

Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach

Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set （5 years （2000-2004）, 17 parameters） obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May （the 1st period） and June-August （the 2nd period）. Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns.

Large-scale deformation monitoring in mining area by D-InSAR and 3D laser scanning technology integration

Large-scale deformation can not be detected by traditional D-InSAR technique because of the limit of its detectable deformation gradient,we propose a method that combines SAR data with point cloud data obtained by 3D laser scanning to improve the gradient of deformation detection.The proposed method takes advantage of high-density of 3D laser scanning point cloud data and its high precision of point positioning after 3D modeling.The specifc process can be described as follows:frst,large-scale deformation points in the interferogram are masked out based on interferometric coherence;second,the interferogram with holes is unwrapped to obtain a deformation map with holes,and last,the holes in the deformation map are flled with point cloud data using inverse distance weighting algorithm,which will achieve seamless connection of monitoring region.We took the embankment dam above working face of a certain mining area in Shandong province as an example to study large-scale deformation in mining area using the proposed method.The results show that the maximum absolute error is 64 mm,relative error of maximum subsidence value is 4.95%,and they are consistent with leveling data of ground observation stations,which confrms the feasibility of this method.The method we presented provides new ways and means for achieving large-scale deformation monitoring by D-InSAR in mining area.

Methods for Force Analysis of Overconstrained Parallel Mechanisms： A Review

The force analysis of overconstrained PMs is relatively complex and difficult, for which the methods have always been a research hotspot. However, few liter- atures analyze the characteristics and application scopes of the various methods, which is not convenient for researchers and engineers to master and adopt them prop- erly. A review of the methods for force analysis of both passive and active overconstrained PMs is presented. The existing force analysis methods for these two kinds of overconstrained PMs are classified according to their main ideas. Each category is briefly demonstrated and evaluated from such aspects as the calculation amount, the compre- hensiveness of considering limbs＇ deformation, and the existence of explicit expressions of the solutions, which provides an important reference for researchers and engi- neers to quickly find a suitable method. The similarities and differences between the statically indeterminate prob- lem of passive overconstrained PMs and that of active overconstrained PMs are discussed, and a universal method for these two kinds of overconstrained PMs is pointed out. The existing deficiencies and development directions of the force analysis methods for overconstrained systems are indicated based on the overview.

CBPS-Based Inference in Nonlinear Regression Models with Missing Data

In this article, to improve the doubly robust estimator, the nonlinear regression models with missing responses are studied. Based on the covariate balancing propensity score (CBPS), estimators for the regression coefficients and the population mean are obtained. It is proved that the proposed estimators are asymptotically normal. In simulation studies, the proposed estimators show improved performance relative to usual augmented inverse probability weighted estimators.

Testing conditional independence with data missing at random

It is known that conditional independence is a quite basic assumption in many fields of statistics. How to test its validity is of great importance and has been extensively studied by the literature. Nevertheless, all of the existing methods focus on the case that data are fully observed, but none of them seems having taken into account of the scenario when missing data are present. Motivated by this, this paper develops two testing statistics to handle such a situation relying on the idea of inverse probability weighted and augmented inverse probability weighted techniques. The asymptotic distributions of the proposed statistics are also derived under the null hypothesis. The simulation studies indicate that both testing statistics perform well in terms of size and power.

Analysis on Change Characteristics of PCD and PCP in Beijiang River Basin

Based on the daily precipitation data between 1965 and 2009 from 18 rainfall stations in Guangdong Beijiang River basin and the definitions of Precipitation Concentration Degree(PCD) and Precipitation Concentration Period(PCP),the inhomogeneous distribution characteristics of interannual precipitation were analyzed by introducing the spatial distribution of annual mean values,variable coefficients,correlation coefficients between annual precipitation,change trends and composite analysis. The results showed that(1) PCD mainly decreased from south to north in spatial distribution; PCP was earlier in most of north-central basin,but relatively later in southern basin.(2) Annual precipitation would increase if PCD decreased in most of river basin,and annual precipitation would decrease as PCP lagged in southern basin,but the change trend was the opposite in northern basin.(3) PCD and PCP mainly showed insignificant upward trend in the entire basin by Mann-Kendall test.

Analysis of Intra-annual Heterogeneous Characteristics of Precipitation in Shaoguan City

Based on the daily precipitation data between 1965 and 2009 from 8 rainfall stations in Shaoguan City,the indexes of precipitation concentration degree（ PCD） and precipitation concentration period（ PCP） were calculated. And then inverse distance weighted（ IDW） interpolation method was used to analyze the heterogeneous distribution characteristics of inter-annual precipitation by introducing the spatial distribution of annual mean values,variable coefficients,correlation coefficients with annual precipitation,change trends and composite analysis. The results showed that PCD was mainly decreasing from southeast to northwest in spatial distribution,long-term average annual values of PCP were distributed in the first ten days of June at most region. Annual precipitation increased as PCD increased in southern region,but the change trend was the opposite in northern region. Annual precipitation increased as PCP lagged in most region. PCD and PCP mainly appeared upward trend. Composite analysis of PCD in more-precipitation years was similar to less-precipitation years in spatial distribution,but the PCD in less-precipitation years was higher.Seen from the mean in the whole region,PCP in more-precipitation years lagged about 20 days behind those in less-precipitation years. The research can provide basis for the production of agriculture and industry as well as disaster prevention and reduction.

Spatial variability of soil chemical properties of Moso bamboo forests of China

This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a geostatistics model.Interpolation maps of SOM,SOC,and pH were developed using ordinary kriging(OK)and inverse distance weighted(IDW)methods.The pH,SOC,and SOM of the two soil layers ranged from 4.6 to 4.7,from 1.5 to 2.7 g kg^(-1)and from 20.3 to 22.4 g kg^(-1),respectively.The coefficient of variation for SOM and SOC was 29.9-43.3%while a weak variability was found for pH.Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R^(2)varying from 0.95 to 0.90.The nugget/sill values of pH are less than 25%,which indicates a strong spatial correlation,while the nugget/sill values of SOC and SOM fall under moderate spatial correlation.Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM,SOC,and pH was inconsistent due to external and internal factors across the plots.Regarding the cross-validation results,the ordinary kriging method performed better than inverse distance weighted method for selected soil properties.This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties.

Trends and Geostatistical Interpolation of Spatio-Temporal Variability of Precipitation in Northern Cameroon

This paper examines the spatial and temporal variability of the mean annual precipitation in the Northern Cameroon on the context of climate change during the time period 1950-2013. The study used homogeneous monthly and annual precipitations database of twenty-five stations located in the Northern Cameroon and Southern Chad Republic. Geostatisticals interpolation methods (Kriging and Inverse Distance Weighting method) associated with Digital Elevation Model were used to establish the spatial distribution of annuals precipitations. The non-parametric Mann- Kendall test and Sen’s slope method were performed to determine respectively trend and magnitude. The result indicates a spatial distribution of precipitation mainly determined by the topography and the geography of the study area. The trend analysis shows a decrease of annual average precipitation across the Northern Cameroon at a rate of ?0.568 mm/year over the time period 1950-2013. The magnitude of decreasing trends ranged between 0.11 and 3.92 mm/year. Statistically significant decreasing trends at the 95% level of confidence were noted at 10% while 5% of stations showed statistically significant increasing. However, 60% of stations indicate a decreasing trend. Monthly analysis of rainfall shows a decreasing trend during June and September while July and August present an increasing trend.

Mapping Distribution of Precipitation, Temperature and Evaporation in Seydisuyu Basin with the Help of Distance Related Estimation Methods

In this research, distributions of precipitation, temperature and evaporation in Seydisuyu basin were analyzed with the help of inverse distance weighted (IDW) method. Because real meteorological data of the basin (precipitation, temperature and evaporation) do not have normal distribution, precipitation, temperature and evaporation distribution maps are drawn after normalization process. The number of meteorological stations, in other words the number of samples, is low, so only IDW method is used in this research. In addition to the research, reliability of the results obtained with the help of inverse distance weighting method was examined with accuracy analysis. The purpose of this study, the spatial distribution of meteorological data on a basin or areas is to demonstrate the applicability of the statistical basis.

Spatio-Temporal Air Pollutant Characterization for Urban Areas

Urban pollution has now become increasingly recognized as an important determinant of air pollution in developed countries. The effect of urban air pollution in developing countries, on the other hand, has not been adequately addressed in the data Spatio-temporal time series. Thus, this study was intended to characterize the effect of urbanization on air pollution for an urbanized Klang Valley, Malaysia using Spatio-temporal data from 2008 to 2017. The Air Pollution Index (API) data and local pollutant concentration were employed to establish the links between urban air pollution. The analysis will be supported by determining the source of pollutants during the study period using Principal Component Analysis (PCA). The study identified that Carbon monoxide (CO), Nitrogen Dioxide (NO2), and Ozone (O3) are the major air pollution that has contributed to degrading air quality in the Klang Valley due to the vehicles, combustion process, and industries.