Environmental Sensitivity Index Mapping for Environmental Sustainable Cleanup along NAOC Pipeline, Asemoku, Delta State, Nigeria

During emergency response to oil spills incident accurate information is required in order to reduce the risk associated with oil spill disasters. This study focuses on Environmental Sensitivity mapping for sustainable environmental clean-up and contingency planning along the 3.0 km of AGIP pipeline at Asemoku in Delta State, Nigeria. Geographic information systems (GIS) techniques were used to create an Environmental Sensitivity Index (ESI) map in the study area. A 2018 Google Earth Satellite imagery of the study area was downloaded, and landuse/cover classification scheme comprising of Vegetation, Farmland, Water Body, Wetland, built up area and Bare Surface was adopted. Existing categorization, ranking and classification of the inland habitat were adopted and used to create a Landuse/cover Environmental Sensitivity Index (ESI) map, while the buffer zones of 100 m, 200 m, 300 m and 400 m were adopted. In the ArcGIS 10.8 environment, the landuse/cover map was generated and buffer distances of 100 m, 200 m, 300 m and 400 m were created on the landuse/cover map to ascertain the features that are vulnerable and could be at risk in the event of oil spill. This study established that the Natural Vegetation areas are the most vulnerable and sensitive feature as a result of their size along the created buffer zones. Findings from this study thus provide insight into the most sensitive land-use/land-cover, in the event of a spill or emergency oil spill clean-up response.

Association between sensitivity to thyroid hormones and non-highdensity lipoprotein cholesterol levels in patients with type 2 diabetes mellitus

BACKGROUND Dyslipidemia and type 2 diabetes mellitus(T2DM)are chronic conditions with substantial public health implications.Effective management of lipid metabolism in patients with T2DM is critical.However,there has been insufficient attention given to the relationship between thyroid hormone sensitivity and dyslipidemia in the T2DM population,particularly concerning non-high-density lipoprotein cholesterol(non-HDL-C).AIM To clarify the association between thyroid hormone sensitivity and dyslipidemia in patients with T2DM.METHODS In this cross-sectional study,thyroid hormone sensitivity indices,the thyroid feedback quantile-based index(TFQI),the thyroid-stimulating hormone index(TSHI),the thyrotrophic T4 resistance index(TT4RI),and the free triiodothyronine(FT3)/free thyroxine(FT4)ratio were calculated.Logistic regression analysis was performed to determine the associations between those composite indices and non-HDL-C levels.Random forest variable importance and Shapley Additive Explanations(SHAP)summary plots were used to identify the strength and direction of the association between hyper-non-HDL-C and its major predictor.RESULTS Among the 994 participants,389(39.13%)had high non-HDL-C levels.Logistic regression analysis revealed that the risk of hyper-non-HDL-C was positively correlated with the TFQI(OR:1.584;95%CI:1.088-2.304;P=0.016),TSHI(OR:1.238;95%CI:1.034-1.482;P=0.02),and TT4RI(OR:1.075;95%CI:1.006-1.149;P=0.032)but was not significantly correlated with the FT3/FT4 ratio.The relationships between composite indices of the thyroid system and non-HDL-C levels differed according to sex.An increased risk of hyper-non-HDL-C was associated with elevated TSHI levels in men(OR:1.331;95%CI:1.003-1.766;P=0.048)but elevated TFQI levels in women(OR:2.337;95%CI:1.4-3.901;P=0.001).Among the analyzed variables,the average SHAP values were highest for TSHI,followed by TT4RI.CONCLUSION Impaired sensitivity to thyroid hormones was associated with high non-HDL-C levels in patients with T2DM.

Study on the Difference of Body Mass Index and Insulin Sensitivity Index in Salt-sensitive Hypertension Patients of Different Traditional Chinese Medicine Syndrome Types

OBJECTIVE: To explore the difference of body mass index(BMI) and insulin sensitivity index(ISI) in saltsensitive hypertension patients of different traditional Chinese medicine(TCM) syndrome types, so as to elucidate the effect of the distribution of each syndrome on the degree of insulin resistance in salt-sensitive hypertension patients. METHODS: A total of 131 patients with salt-sensitive hypertension were included in the study. Factor analysis and cluster analysis were used to study the characteristics of TCM viscera, syndrome elements and syndrome differentiation. Furthermore, the following parameters were observed and corresponding differences were analyzed, including BMI, waist circumference, abdominal circumference, neck circumference and insulin sensitivity index among group s of different TCM syndrome types. RESULTS: There were 131 cases of saltsensitive hypertension. The results of factor analysis showed that the total variance contribution of F1-5 common factors was 75.8%. According to the pattern differentiation of zang-fu organs, a basic theory of traditional Chinese medicine(TCM), the main zang-fu organs involved in the five common factors are: liver, spleen, and kidney.The main syndrome factors that had been extracted include yin de?ciency, ?re, qi stagnation, yang hyperactivity,dampness, phlegm, qi reversal, heat, retained fluid, essence deficiency, qi descending, qi deficiency, and yang deficiency. Among them, factor 1 accounted for 18.32%, factor 2 accounted for 21.37%, factor 3 accounted for20.43%, factor 4 accounted for 20.61%, and factor 5 accounted for 22.14%. The proportion of zang-fu organs involvement was: 21.37% of the spleen, 17.56% of the kidney, 18.32% of the liver and spleen, and 42.75% of the spleen and kidney. Syndrome elements: yin de?ciency 18.32%, phlegm-dampness 21.37%, qi stagnation 39.69%, qi de?ciency 42.75%, retained ?uid 20.61%, yang de?ciency 60.31%, essence de?ciency 17.56%, qi sinking 17.56%,heat 21.37%, qi reversal 21.37%. Results of cluster analysis: there were 3 categories when the distance variance was 20-Category 1: Factor 1; Category 2: Factor 2; Category 3: Factor 3, Factor 4, Factor 5. Combined with the clinical practice of TCM, the classi?cation based on TCM syndromes was:Category 1, yin de?ciency and yang hyperactivity pattern(accounting for 18.32%); Category 2, excessive accumulation of phlegm-dampness(accounting for 21.37%); Category 3, spleen-kidney yang de?ciency and pattern of water-rheum collecting internally(accounting for 60.31%), including 24 cases of yin-de?ciency and yang-hyperactivity(YDYH), 28 cases of excessive phlegmdampness syndrome(EPDS), 79 cases of spleen and kidney yang-de?ciency and ?uid retention stagnating in the interior(SKFR). There was no difference in the distribution of age and sex among groups. In addition, no signi?cant difference was found regarding BMI, waist circumference, abdominal circumference, neck circumference among groups of salt-sensitive hypertension of different TCM syndrome types. Meanwhile, ISI was signi?cantly lower in cases of spleen and kidney yang-de?ciency and ?uid retention stagnating in the interior than in the other 2 groups,with statistical difference. CONCLUSION: Insulin resistance is the most serious in salt-sensitive hypertension patients with spleen and kidney yang-de?ciency and ?uid retention stagnating in the interior. Besides, obesity is not a critical factor in determining the distribution of TCM syndrome types in patients with salt-sensitive hypertension.

Comparison of marine controlled-source electromagnetic data acquisition systems by a reservoir sensitivity index:analyzing the effect of water depths

During the past ten years, a marine controlled source electromagnetic（CSEM） method has been developed rapidly as a technology for hydrocarbon exploration. For shallow water environments, two CSEM data acquisition systems： Seabed Logging（SBL） and towed streamer electromagnetics（TSEM） have been developed in recent years. The purpose is to compare the performance of the SBL and TSEM systems at different water depths. Three different methods for the comparison are presented. The first method is a quick one dimensional sensitivity modelling. As a result, the sensitivity of marine CSEM data increases with water depth for the SBL system. Further, the sensitivity decreases with the increasing water depth for the TSEM system. The two other methods use two dimensional synthetic data from a simple 2-D isotropic model. The second method is a reservoir sensitivity index（RSI） method which has been developed to provide a quick comparison of the two systems. The RSI is calculated as the amplitude of the scattered field dividing by data uncertainty. From the calculations, it is found that with the increasing water depth RSI increases for the SBL system, while it decreases for the TSEM system. The third method uses Occam＇s inversion, and applies an anomaly transverse resistance（ATR） ratio for evaluating the resulting resistivity image. In shallow water environments, the resolution of the CSEM inversion results is good for both the SBL and TSEM systems. In deep water environments, the resolution of the CSEM inversion is better for the SBL system than for the TSEM system. The ATR ratios of the resistivity images show the similar conclusion. The SBL data acquisition system has an advantage in deep water environments. The TSEM system, on the other hand, is preferable for the shallow water environments.

Sediment texture and grain-size implications: the Changjiang subaqueous delta

Sediment cores were collected from the subaqueous delta of the Changjiang Estuary. Sediment grain-size profiles and their fractal dimensions were analyzed, to elucidate responses to long-term sedimentary processes. In addition, the environmental sensitive populations of grain size have been extracted. The sediment cores can be divided into two parts, according to the sedimentary structures present. The upper part （0-12 cm） is interpreted as being the active layer, which is influenced frequently by changes in the short-term hydrodynamic environment. The lower part extends from a depth of 12 cm, to the bottom of the core. The pattern of fluctuation is linked to sediment grain size. Moreover, two grain-size sensitive populations can be identified. The fine sensitive population is 6.0-7.2 μm, which is a similar grain size to the suspended sediment from up-river. The coarse sensitive population varies from 40.7 to 57.5 μm, revealing complex changes. Thus, the riverine inputs from the Changjiang River may be an important source, which contributes to seasonal fluctuations of grain-size distribution, over the area. The sediments, with grain-sizes ranging from 0.9 to 20.3 μm, are characterised by self-similar in the fractal non-scale region. The fraetal dimension is eonsistant with the grain-size parameter varatioins, which could be used as a replacement index to reveal and reconstruct the sedimentary environmental evolution.

Study on comparison of different methods to calculating sensitivity index of Jensen model

Real coded Accelerating Genetic Algorithm （RAGA）, Chaos Algorithm （CA） were used to solve the sensitivity index of Jensen model which is one of models of crop water production function. After comparing with the outcome of Least Square Regression （LSR）, the result showed that RAGA not only had high accuracy and more effective, but also saved calculating time. The authors provides new effective methods for calculating index of crop water production function.

Using Crop Management Scenario Simulations to Evaluate the Sensitivity of the Ohio Phosphorus Risk Index

Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important to evaluate weighting/scoring of all P Index parameters to ensure Ohio farmers are credited for practices that reduce P runoff risk and not unduly penalized for things not demonstrably related to runoff risk. A sensitivity analysis provides information as to how sensitive the P Index score is to changes in inputs. The objectives were to determine 1) which inputs are most highly associated with P Index scores and 2) the relative impact of each input variable on resultant P Index scores. The current approach uses simulations across 6134 Ohio point locations and five crop management scenarios (CMSs), representing increasing soil disturbance. The CMSs range from all no-till, which is being promoted in Ohio, rotational tillage, which is a common practice in Ohio to full tillage to represent an extreme practice. Results showed that P Index scores were best explained by soil test P (31.9%) followed by connectivity to water (29.7%), soil erosion (13.4%), fertilizer application amount (11.3%), runoff class (9.5%), fertilizer application method (2.2%), and finally filter strip (2.0%). Ohio P Index simulations across CMSs one through five showed that >40% scored <15 points (low) while <1.5% scored >45 points (very high). Given Ohio water quality problems, the Ohio P Index needs to be stricter. The current approach is useful for Ohio P Index evaluations and revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.

A Methodology for Identification of Weather Sensitive Component of Electrical Load Using Empirical Mode Decomposition Technique

The expansion planning and operation of all three sectors, generation, transmission and distribution, of power system essentially require load forecasting. Weather conditions have significant impacts on forecasted load, especially short-term and mid-term. A momentous portion of the electrical energy is consumed, especially in cold or hot countries, to mitigate the impact of weather on the daily life of human society. Usually, weather dependent component of load is identified by fitting appropriate non-linear curve to the scatter plot of weather-load model. This technique some times shows lower correlation with weather variables. This paper proposes a new methodology to identify the weather sensitive component of electrical load using empirical mode decomposition (EMD) technique. The proposed methodology is applied to the daily peak load of Dhaka zone of Bangladesh Power System (BPS) of the year 2012. A detailed numerical process to evaluate the weather sensitive portion of the load is also presented. The proposed methodology is validated through statistical error evaluation process. Finally the salient features of the results are discussed.

Total Sensitivity Index Calculation of Tool Requirement Model via Error Propagation Equation

A new and convenient method is presented to calculate the total sensitivity indices defined by variance-based sensitivity analysis. By decomposing the output variance using error propagation equations, this method can transform the ＂double-loop＂ sampling procedure into ＂single-loop＂ one and obviously reduce the computation cost of analysis. In contrast with Sobors and Fourier amplitude sensitivity test （FAST） method, which is limited in non-correlated variables, the new approach is suitable for correlated input variables. An application in semiconductor assembling and test manufacturing （ATM） factory indicates that this approach has a good performance in additive model and simple non-additive model.

Sensitivity Analysis of a Bioinspired Refractive Index Based Gas Sensor

It was found out that the change of refractive index of ambient gas can lead to obvious change of the color of Morpho butterfly＇s wing. Such phenomenon has been employed as a sensing principle for detecting gas. In the present study, Rigorous Coupled-Wave Analysis （RCWA） was described briefly, and the partial derivative of optical reflection efficiency with respect to the refractive index of ambient gas, i.e., sensitivity of the sensor, was derived based on RCWA. A bioinspired grating model was constructed by mimicking the nanostructure on the ground scale of Morpho didius butterfly＇s wing. The analytical sensitivity was verified and the effect of the grating shape on the reflection spectra and its sensitivity were discussed. The results show that by tuning shape parameters of the grating, we can obtain desired reflection spectra and sensitivity, which can be applied to the design of the bioinspired refractive index based gas sensor.

Sensitivity Analysis and Selection of Check Index of Signal Intersection Simulation Model Based on VISSIM

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay’s is maximum, so it’s necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

Grain-size features of aeolian sand on the east coast of Hainan Island and the revealed evolutionary processes of the sedimentary environment

The Mudui stratigraphic section represents the typical records of sedimentation processes of sand dunes and interdune depressions on the east coast of Hainan Island.Based on high-density sampling and optically stimulated luminescence(OSL) dating of the strata of the section,the grain-size composition,grain-size parameters,cumulative distribution probability curve,and grain-size-sensitivity indexes(SC/D) were analyzed.The analyzed results show that the grain-size features of aeolian sand,weakly developed sandy paleosol,two-facies(aeolian and aqueous) deposits,and lagoon deposits are all different.This indicates four evolutionary phases of the sedimentary environment of the east coast of Hainan Island since 38 ka B.P.Phase I:38-22 ka B.P.;phase II:22-17 ka B.P.;phase III:17-10 ka B.P.;phase IV:10 ka B.P.-present.The climate experienced the hot-wet/hot-dry,hot-wet/hot-dry,and warm-wet/hot-wet fluctuations,and the sedimentary environment also underwent lagoon deposition,dune and interdune depression deposition,dune stabilization and soil development,shifting sand deposition,and evolutionary processes.

A Social Stability Analysis System Based on Web Sensitive Information Mining

Researches on domestic social stability analysis mainly focus on construction of social stability theory,architecture and index,while few pay attention on quantitative analysis.In this paper,a social stability supervising framework is proposed based on sensitive Web information mining,semantic pattern matching and quantitative calculating.A sensitive information knowledge base is constructed by analyzing sensitive information about social environment,national harmonious and happy index of people’s live in natural language online news texts from Internet,and recognizing hot keywords as well as the event trends led by the keywords.A social stability index theoretic model and a quantitative calculating model are proposed to evaluate social stability quantitatively.Parameters of the calculating model are determined by employing social investigations and an iterative feedback learning method.A prototype system is built on proposed framework and experiments are conducted on six frontier provinces,e.g.,Xinjiang and Tibet.The result of an average accurate of 73.29%shows the effectiveness of the proposed model.

基于地表敏感变形和房屋因素的矿区建筑物损坏评价方法

针对目前建筑物采动损坏评价因素的不尽合理与区域性评判结果的局限性,提出基于地表敏感变形和房屋因素的矿区建筑物采动损坏评价方法。采用理论分析、数值模拟和现场调查等方法对建筑物采动损坏评价进行了研究与探讨。首先,采用数值模拟方法,揭示地表变形、建筑物结构类型、主变形方向与建筑物长轴的夹角等因素对建筑物损坏影响规律,模拟结果表明:①当沿建筑物长轴的变形增大时,建筑物的损坏程度增大,得出了平房建筑加速损伤的地表变形临界值为曲率K=0.6 mm/m^(2),水平变形ε=6 mm/m;②不同结构的建筑物损坏程度不同,其中具有圈梁或构造柱的建筑物抗变形能力强,研究并确定了二层砖混结构(圈梁和构造柱)损坏程度的地表临界变形值;③建筑物对其长轴方向的地表变形较为敏感,影响损坏大,但对其长轴的垂直方向的变形不太敏感,而变形与建筑物斜交方向的建筑物损坏程度介于2者之间。其次,基于地表敏感变形因素、主变形方向、房屋因素共选取7个评价指标,建立建筑物采动损坏评价的未确知测度模型,根据各评价指标对建筑物的重要程度,采用层次分析法定权;最后,应用于峰峰矿区和徐州矿区3个村庄的建筑物损坏实例,结果表明:在选取的50户140余栋建筑物评价中,预测准确率在80%以上,预测精度高于传统方法,且预测效果良好,弥补了传统评价方法的不足,验证了评价指标选取和评价模型的可靠性。

青海省三级医院信息化护理质控平台建设及应用

目的/意义建立青海省三级医院信息化护理质控平台,分析其对护理质量的影响。方法/过程根据青海省护理质量管理现状,依托青海省护理质量数据平台,建立护理质量指标监测模块,选取1家三级医院作为试点,采用历史对照研究方法,将2021年1—6月该医院护理质量数据作为对照组,2022年1—6月采用信息化护理质控平台收集的数据作为观察组,对比平台应用前后护理质量的变化情况。结果/结论信息化护理质控平台应用后,住院患者身体约束率和气管插管非计划拔管率显著下降,患者对护理工作满意度评分显著提升,平台可操作性强,具有临床应用价值。

质量敏感指标联合阶段递进式护理应用于消毒供应室对器械合格及院内感染的影响

目的 对于消毒供应室采取质量敏感指标联合阶段递进式护理后对器械合格及院内感染的影响进行分析。方法 消毒供应室2022年度采取常规护理模式(对照组),2023年度采取质量敏感指标联合阶段递进式护理(研究组)。分别在每个年度随机选出4300件器械(器械包共计100包),对比合格率(回收、清洗、消毒灭菌、包装、发放)。在年度收治使用器械的患者中各选取100例,对比院内感染率。以消毒供应室工作人员为研究对象(10名),比较护理质量。比较对护理的满意度。结果 研究组回收、清洗、消毒灭菌、包装、发放合格率均比对照组更高(P <0.05)。研究组院内感染率比对照组低,但无明显差异(P> 0.05)。研究组比对照组护理质量好(P <0.05)。护理满意度两组更高的是研究组(P <0.05)。结论 消毒供应室采取质量敏感指标联合阶段递进式护理可以提高器械合格率,预防院内感染,护理质量提高,满意度高。

黄河流域生态敏感性评价研究

以黄河流域为研究对象,依据地形条件、自然环境和人类活动3个方面,选取了7个指标,构建了生态敏感性评价体系,采用AHP层次分析法确定各指标权重,运用GIS加权叠加法对黄河流域生态敏感性进行综合评价。结果表明:黄河流域生态敏感性的空间分布存在显著差异,呈现出中上游高、下游低的分布格局,整体上中敏感区占主导地位,面积达33.59万km^(2),占流域总面积的42.25%,高敏感区和极高敏感区面积17.37万km^(2),占流域总面积的21.85%。

海上油气平台不稳定电源与储能联合配置优化策略

针对海上油气平台集群接入不稳定电源与储能的联合配置问题,结合海上风电、光伏特点及已有的拓扑结构,提出了三阶段风机/光伏/储能阶段式联合配置策略,介绍嵌入潮流计算的阶段式粒子群算法。第一阶段通过LightGBM网络预测模型得到风机光伏的时序预测发电功率,再以投资建设经济性和潮流稳定性为目标优化每个节点的风机/光伏容量;第二阶段针对不稳定电源配置后的配电网,提出了基于电压和损耗灵敏度为指标的集群划分方法,将配电网集群划分为若干个子集群;第三阶段根据划分后的子集群,以储能容量、配电网损耗和节点电压波动为目标为每个子集群内配置储能。以渤海油田某10 kV实际油气平台配电网为例,设立燃气机出力功率自定义和经济性自定义两种方案来验证联合配置优化决策的合理性。结果表明,两种配置策略都可以有效地提升海上油气平台配电网的潮流稳定性,提高新能源的渗透率。本文研究验证了海上分散式风机/光伏发电工程的可行性,有利于实现未来海上油气平台的“零碳”建设。

专科护理敏感指标干预对患者肠道准备清洁度及满意度的影响

目的研究专科护理敏感指标干预对患者肠道准备清洁度及满意度的影响。方法选取2021年1月至2022年6月接受肠镜检查患者97例,随机数字表法分为对照组(n=48)和观察组(n=49)。对照组给予常规护理干预,观察组给予专科护理敏感指标干预,比较2组肠道准备依从性和清洁度,统计肠道检查围检查期不良反应和事件发生情况,并比较2组患者护理满意度。结果观察组肠道准备依从性、肉眼下肠道准备合格率、镜下肠道准备清洁度总分、满意度高于对照组(P<0.05),肠道检查围检查期不良反应和事件总发生率低于对照组(P<0.05)。结论给予接受肠镜检查患者专科护理敏感指标干预可提升其肠道准备依从性,提升肠道准备质量,减少肠镜准备和检查不良情况的发生,使肠镜检查可顺利进行,患者满意度较高。

基于FAST和Sobol指数法的雷达系统效能敏感性分析

为了以较小的代价快速提升对空探测雷达系统的综合效能,首先搭建了对空探测雷达系统综合效能的评估指标体系,在此基础上完成了综合效能评估模型的建立。选择两种基于方差原理的全局敏感性分析方法,即傅里叶幅度敏感性测试(Fourier amplitudes sensitivity test,FAST)和Sobol指数法,分别从频域和时域对建立的评估模型进行敏感性分析。在基于FAST进行敏感性分析时,提出了21维输入指标所对应的特征频率集的选取方法;在基于Sobol指数法进行敏感性分析时,考虑了二阶及高阶敏感性指数的影响。对比FAST和Sobol指数法的分析结果,两种方法获得的敏感性分析结果具有较好的一致性。其中,功率和频率为对空探测雷达系统的主要影响指标,为雷达系统的研发和升级提供了可靠性依据。