Effect of Storage Time on Main Quality Indicators of Cotton

The quality indicators of cotton will change during storage.Taking the 5.89 million t of Xinjiang cotton from 2016 to 2021 as a sample,this paper analyzed the main fiber quality indicator data of warehouse-in and warehouse-out cotton for storage of 1.5,3.0,4.0,5.0,6.0,and 7.0 years.It was found that the color grade of cotton decreased with the extension of storage time.The cotton with storage time of 5.0 years mainly changed from white cotton grade 2 and white cotton grade 3 to light yellow stained cotton grade 1 and yellow stained cotton grade 1.Among them,the increase of light yellow stained cotton grade 1 was the largest,and the change to yellow stained cotton grade 1 was the largest at the storage 6.0-7.0 years.In addition,there were no significant changes in moisture regain,Micronaire value,upper half mean length,length uniformity index and fiber strength.

Long Lead-Time Streamflow Forecasting Using Oceanic-Atmospheric Oscillation Indices

Climatic variability influences the hydrological cycle that subsequently affects the discharge in the stream. The variability in the climate can be represented by the ocean-atmospheric oscillations which provide the forecast opportunity for the streamflow. Prediction of future water availability accurately and reliably is a key step for successful water resource management in the arid regions. Four popular ocean-atmospheric indices were used in this study for annual streamflow volume prediction. They were Pacific Decadal Oscillation (PDO), El-Nino Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO). Multivariate Relevance Vector Machine (MVRVM), a data driven model based on Bayesian learning approach was used as a prediction model. The model was applied to four unimpaired stream gages in Utah that spatially covers the state from north to south. Different models were developed based on the combinations of oscillation indices in the input. A total of 60 years (1950-2009) of data were used for the analysis. The model was trained on 50 years of data (1950-1999) and tested on 10 years of data (2000-2009). The best combination of oscillation indices and the lead-time were identified for each gage which was used to develop the prediction model. The predicted flow had reasonable agreement with the actual annual flow volume. The sensitivity analysis shows that the PDO and ENSO have relatively stronger effect compared to other oscillation indices in Utah. The prediction results from the MVRVM were compared with the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) where MVRVM performed relatively better.

Using a support vector machine method to predict the development indices of very high water cut oilfields

Because the oilfields in eastern China are in the very high water cut development stage, accurate forecast of oilfield development indices is important for exploiting the oilfields efficiently. Regarding the problems of the small number of samples collected for oilfield development indices, a new support vector regression prediction method for development indices is proposed in this paper. This method uses the principle of functional simulation to determine the input-output of a support vector machine prediction system based on historical oilfield development data. It chooses the kernel function of the support vector machine by analyzing time series characteristics of the development index; trains and tests the support vector machine network with historical data to construct the support vector regression prediction model of oilfield development indices; and predicts the development index. The case study shows that the proposed method is feasible, and predicted development indices agree well with the development performance of very high water cut oilfields.

Quality indicators for colonoscopy: Current insights and caveats

Colonoscopy is the diagnostic modality of choice for investigation of symptoms suspected to be related to the colon and for the detection of polyps and colorectal cancer(CRC). Colonoscopy with removal of detected polyps has been shown to reduce the incidence and mortality of subsequent CRC. In many countries, population screening programs for CRC have been initiated, either by selection of patients for colonoscopy with fecal occult blood testing or by offering colonoscopy directly to average-risk individuals. Several endoscopy societies have formulated quality indicators for colonoscopy. These quality indicators are almost always incorporated as process indicators, rather than outcome measures. This review focuses on the quality indicators bowel preparation, cecal intubation rate, withdrawal time, adenoma detection rate, patient comfort, sedation and complication rate, and discusses the scientific evidence supporting them,as well as their potential shortcomings and issues that need to be addressed. For instance, there is still no clear and generally accepted definition of adequatebowel preparation, no robust scientific evidence is available supporting a cecal intubation rate ≥ 90% and the association between withdrawal time and occurrence of interval cancers has not been clarified. Adenoma detection rate is currently the only quality indicator that has been shown to be associated with interval colorectal cancer, but as an indicator it does not differentiate between subjects with one or more adenoma detected.

Effects of UV intensity and water turbidity on microbial indicator Inactivation

The effects of UV intensity and turbidity on selected microbial indicator inactivation were investigated. Results showed that UV disinfection was effective in killing all the selected microbial indicators, the resistance order of the microorganisms was as follows： MS-2 coliphage 〉 Bacillus subtilis 〉 E. coil 〉 Staphylococcus aureus and Candida albicans. UV intensity had influence on the inactivation of all the microorganisms, high UV disinfection efficency was obtained with higher UV intensity. Turbidity had impact on the bacteria inactivation rate, but there was no evidence that turbidity had any negative contribution to MS-2 coliphage. Under the same UV dosage, higher UV intensity could overcome the negative influence of turbidity on UV performance, enhanced microorganism inactivation effect in turbidity water.

Indicators of sorafenib efficacy in patients with advanced hepatocellular carcinoma

AIM: To determine significant indicators for the efficacy of sorafenib in patients with advanced hepatocellular carcinoma (HCC).

Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators

Forex(foreign exchange)is a special financial market that entails both high risks and high profit opportunities for traders.It is also a very simple market since traders can profit by just predicting the direction of the exchange rate between two currencies.However,incorrect predictions in Forex may cause much higher losses than in other typical financial markets.The direction prediction requirement makes the problem quite different from other typical time-series forecasting problems.In this work,we used a popular deep learning tool called“long short-term memory”(LSTM),which has been shown to be very effective in many time-series forecasting problems,to make direction predictions in Forex.We utilized two different data sets—namely,macroeconomic data and technical indicator data—since in the financial world,fundamental and technical analysis are two main techniques,and they use those two data sets,respectively.Our proposed hybrid model,which combines two separate LSTMs corresponding to these two data sets,was found to be quite successful in experiments using real data.

Operative timing and indications for patients with severe acute pancreatitis: report of 172 cases

Objective: To investigate the operative timing and indi-cations for severe acute pancreatitis(SAP).Methods: Data collected from 172 patients with SAPtreated in our hospital since 1980 were analyzed retro-spectively.Results: In the 94 patients who had undergone early op-eration before June 1992, 57 (62.8%) healed, 35 (37.2%)died, and 16 (17.0%) had no postoperative compli-cations. In the 78 patients who had been treated after July1992 according to the principle of individualization, 66(84.6%) healed, 12 (15.4%) died, and 37 (47.4%)had no postoperative complications. In the 78 patients32 received non-operative treatment but 30 (93.8%)cured, 12 early operation but 7(58.3%)cured, 18 lateoperation but 13 (72.2%) cured, and 16 selected timeoperation but all cured.Conclusions: It is concluded that individualized thera-py is effective and reasonable for treating SAP. Theindications for early, late and selected time operationshould be emphasized.

Methodological challenges to control for immortal time bias in addressing drug effects in type 2 diabetes

There are multiple biases in using observational studies to examine treatment effects such as those from prevalent drug users, immortal time and drug indications. We used renin angiotensin system(RAS) inhibitors and statins as reference drugs with proven efficacies in randomized clinical trials(RCTs) and examined their effectiveness in the prospective Hong Kong Diabetes Registry using adjustment methods proposed in the literature. Using time-dependent exposures to drug treatments yielded greatly inflated hazard ratios(HR) regarding the treatment effects of these drugs for cardiovascular disease(CVD) in type 2 diabetes. These errors were probably due to changing indications to use these drugs during follow up periods, especially at the time of drug commencement making time-dependent analysis extremely problematic. Using time-fixed analysis with exclusion of immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of RAS inhibitors for CVD was comparable to that in RCT. The result supported the use of the Registry for performing pharmacoepidemiological analysis which revealed an attenuated low low-density lipoprotein cholesterol related cancer risk with RAS inhibitors. On the other hand, time-fixed analysis with including immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of statins for CVD was similar to that in the RCT. Our results highlight the complexity and difficulty in removing these biases. We call for validations of the methods to cope with immortal time and drug use indications before applying them to particular research questions, so to avoid making erroneous conclusions.

Improving Clinical Laboratory Quality through Reduction of Tests’ Turnaround Time in Democratic Republic of the Congo: Key Strategies

In Democratic Republic of the Congo (DRC), the laboratory TAT is significantly very long and do not comply with either international standards or the suggestions of customers. However, there is neither a national nor a local strategy to improve the laboratory TAT. The aim of the present study is to develop practical management strategies to shorten clinical laboratory tests’ TAT. This was a qualitative study conducted in Kinshasa. Focus groups and Lean tools were used respectively to generate a wide range of views from a variety of laboratory staff and to eliminate several form of waste in the laboratory flow process. Based on the identified root causes of delay, focus groups participants reported that there is a lot of scope for the improvement of TAT in DRC. Consistent attendance and punctuality are essential. The hospital management should implement the Laboratory Information Systems (LIS) and install Middleware. Total laboratory automation, inventory system for all reagents and supplies used in the laboratory, expansion of the sampling area, sufficient number of high-power machine and a clear job description are indispensable. LIS, 3.5 mL BD vacutainer BarricorTM tube and point-of-care testing (POCT) are necessary for workflow improvement. A reduction of 312 minutes was achieved by eliminating or decreasing non-value-added activities. Applying the suggested key strategies, and particularly the new workflow process, is a basis for improving the laboratory tests’ TAT. The algorithm presented can be easily implemented in other laboratories that face this type of problem.

Changes in clinical indicators among human immunodeficiency virus patients who failed in antiretroviral therapy during 2004–2016 in Yunnan, China: an observational cohort study

Background:This study aimed to investigate the changes in the clinical indicators and influencing factors of treatment duration among human immunodeficiency virus(HIV)patients in whom antiretroviral therapy(ART)was unsuccessful.Methods:In this retrospective study,a total of 9,418 HIV patients who failed in ART during 2004–2016 were included and divided into two treatment groups—Group 1(treatment time≤3 years,n1=5,218)and Group 2(treatment time>3 years,n2=4,200).Patient follow-up data,including age,cluster of differentiation 4(CD4)count,and viral load,glucose,creatinine,and triglyceride levels,were extracted from electronic health record databases.Covariance analysis for repeated measures was used to analyze the biochemical indicators,and multiple logistic regression modeling was used to compare relevant data extracted from the Group 1 and Group 2 HIV patient cohorts with different treatment time.Results:The median initial CD4 count was 175.0 cells/μl(interquartile range,77.0–282.0),while the initial CD4 counts for Group 1 were lower than those for Group 2(P<0.05).A significant interaction between group and time effects was observed(P<0.05)in total cholesterol(TC).Changes in hemoglobin level among HIV patients were also significantly associated with treatment time(P=0.001).The initial CD4 count(odds ratio[OR]=0.756),female sex(OR=0.713),Zerit(d4T)(OR=1.443),TC(OR=1.285),and aspartate aminotransferase level(OR=1.002)were significantly associated with the survival time of dead patients with HIV(P<0.05).Additionally,the initial CD4 count(OR=1.456),age(OR=1.022),time interval(OR=0.903),patient’s living status(OR=0.597),d4T(OR=2.256),and triglyceride(OR=0.930)and hemoglobin levels(OR=0.997)were significantly associated with the treatment time of HIV patients with drug withdrawal(P<0.05).Conclusion:The initial biochemical parameters can affect the survival and treatment time of HIV patients.With a comprehensive understanding of the physiological and biochemical indicators of patients,we can reduce the probability of drug withdrawal and prolong the survival time of HIV patients.

New Composite Indicator for the Business Tendency Survey

Short-term surveys provide precious information for economic fluctuations analysis. In short-term surveys like the business tendency survey, most of the questions are qualitative and concern the evolution of different economic factors of the business activity. They provide economic information on the present situation and short-term perspectives. Usually, the respondents have to choose between three possible evolutions： increase （improvement, favourable, level higher than the normal）, stability （normal） or decrease （unfavourable, level lower than the normal）. The balance of opinion is defined as the difference between the proportion of respondents expressing a positive opinion and the proportion expressing a negative opinion. To analyze these types of surveys, the methods are well standardized and use both the multidimensional approach and time series （scoring, dynamic factor analysis, etc.） In this paper, the authors propose a new method of calculating a robust composite indicator based on range median statistics, and on a lexicographical order relation of the individual data. A confidence interval is constructed around these statistics. The indicator＇s advantage is simplicity of calculation in comparison with the Mitchell, Smith and Weale （2004） index （MSW）, while its effectiveness seems to be of the same order. It was used on a Ukrainian dataset for the construction sector. This procedure can be applied to the surveys that contain correlated ordered qualitative answers.

用于食品智能包装的时间温度指示器的开发与性能测试研究进展

时间温度指示器(time-temperature indicator, TTI)作为实时监测食品温度历史的有效工具,在确保食品质量安全、减少食品浪费方面具有广阔的前景。当前已形成了物理型、化学型、生物型和复合型等多种类型的TTI用于食品智能包装,产品应用于海鲜、肉制品、乳制品和果蔬等不同类型食品。本文研究总结了近年来国内外TTI的开发及商业化应用情况,重点对纳米型、微生物型、酶型、美拉德型4种TTI的工作原理和研究进展进行了综述,同时梳理分析了TTI与食品的匹配性原则、变温环境下产品适用性、可靠性测试方法以及欧盟、美国和韩国等国外法规对TTI的食品安全要求,最后提出了未来TTI发展面临的一些挑战,以期为行业的进一步发展提供参考依据。

Correspondence Analysis on a Space-Time Data Set for Multiple Environmental Variables

Applications of the multivariate technique called correspondence analysis for environmental studies are relatively new and are limited to spatial multivariate data set. In this paper, a procedure of applying correspondence analysis to a large space-time data set for multiple environmental variables is shown. In particular, nitrogen dioxide and carbon monoxide hourly concentrations measured during January 1999 at several monitored stations in a district of Northern Italy are analyzed. The procedure consists in transforming the continuous variables into categorical ones by the means of appropriate indicator variables, generating special contingency tables and applying correspondence analysis. The use of this classical multivariate technique allows the identification of important relationships among pollution levels and monitoring stations and/or relationships among pollution levels and observation times.

电力动态碳排放责任因子

新型电力系统建设背景下,需要充分发挥海量用电终端具有的储能和灵活用电资源来解决电力系统的实时调节需求,这一调节目标的实现亟需建立合理的引导指标和激励机制。为此,该文提出利用“电力动态碳排放责任因子”激励用电终端进行自律式调节的方法。首先,给出这种方法的基本原则;然后,具体讨论碳排放责任因子的计算方法,再利用电网的实际运行数据说明这种确定电力动态碳排放责任因子方法的有效性和可持续性;最后,通过案例分析建筑等用电终端的灵活性调节潜力。该文提出的电力动态碳排放责任因子,为新型电力系统实现与海量用户侧灵活可调资源间的实时互动提供了新的思路,未来将进一步完善其政策、理论及实际实施等多方面的工作。

句法复杂度与日语母语者汉语应用文写作质量关系研究

以中高级水平日语母语者所写的汉语应用文(求职信)为研究对象,在句层面和短语层面分别设立3个测量指标,考察不同层面的句法复杂度指标与写作质量的关系。研究发现,句层面的3项话题链指标与写作成绩相关均不显著。在短语层面,复杂名词短语的总数、长度指标与成绩相关不显著,而比率指标与成绩显著相关,能够解释应用文成绩总变异的17.7%,达到中等效应量。这一结论证明了短语层面的复杂名词短语比率是预测应用文写作成绩的有效指标。

船舶交通数据实时传输可靠性评估系统

为保障船舶交通数据实时传输的可靠性,设计船舶交通数据实时传输可靠性评估系统。从网络条件、节点设备、环境因素与网络管理4个主要方面出发选取评估指标,构建船舶交通数据实时传输可靠性评估指标体系;采用基于三角模糊数的模糊层次分析法计算评估指标的权重值;将各评估指标与对应的权重值形成并进行汇总,由此得到最终船舶交通数据实时传输可靠性评估结果。实验结果显示,该系统能够获取准确的评估结果,且由于不同因素造成的船舶交通数据实时传输故障发生概率下降幅度均达到50%以上,由此说明基于该系统的评估结果能够有效保障船舶交通数据实时传输的可靠性。

内镜逆行性阑尾炎治疗在小儿阑尾炎中的应用价值

目的探讨内镜逆行性阑尾炎治疗(ERAT)在小儿阑尾炎的应用价值。方法选取2021年1月至2022年6月赣州市人民医院收治的60例急性单纯性阑尾炎患儿为对象,按照随机数表法分为试验组(n=30)和对照组(n=30)。对照组行抗生素治疗,试验组行ERAT治疗。比较两组相关时间指标、并发症发生率、治疗前后白细胞水平。结果试验组的症状缓解时间、白细胞恢复时间、体温恢复时间、住院时间短于对照组,差异有统计学意义(P<0.05);两组的并发症总发生率比较,差异无统计学意义(P>0.05);试验组治疗后1 d的白细胞水平低于对照组,差异有统计学意义(P<0.05);试验组的复发率低于对照组,差异有统计学意义(P<0.05)。结论内镜逆行性阑尾炎治疗方案在小儿单纯性阑尾炎治疗中的应用对促进患儿症状快速缓解、缩短患儿住院时间等均有显著效果,可有效降低患儿复发率。

中国式现代化视域下的测度、演化与模式

文章基于新发展理念并结合中国式现代化的五大特征,构建了经济现代化、创新现代化、共享现代化、生态现代化、治理现代化五个维度的中国式现代化指标体系,依据各省统计年鉴和百度指数数据使用熵权法测算2012-2021年中国31个省份的中国式现代化水平。采用核密度估计、σ收敛模型、β收敛模型和基于动态时间规整的面板数据K中心点聚类算法,分析了中国式现代化的动态演化特征、收敛机制以及发展的模式。研究结果表明:2012-2021年中国式现代化水平逐步提升;东部地区的中国式现代化水平最高,中部地区的增速最高,西部和东北地区存在中国式现代化水平低且增长乏力的问题;全国各省份的中国式现代化水平绝对收敛速度为0.7%,条件收敛速度为3%,不存在σ收敛;聚类分析发现存在发展型和变革型两类中国式现代化模式:发展型中国式现代化以经济现代化为抓手,在共享现代化和生态现代化上表现优异;变革型中国式现代化勇于变革制度寻求突破创新,侧重于治理现代化和创新现代化。