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.

Antecedent Precipitation Index to Estimate Soil Moisture and Correlate as a Triggering Process in the Occurrence of Landslides

Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.

Carpel Tunnel Syndrome: A Link with Vitamin D, Body Mass Index and Hyperlipidemia

Introduction: Carbai tunnel syndrome [CTS] is compression of the median nerve at the wrist , this causes tingling in the hands, pain, numbness, tingling in the fingers particularly the thumb, index and middle fingers, loss of sensation in the hands and fingers, also weakness in the hands. The aim of the present study was to study a possible association which could be found between electrophysiological data in CTS, BMI, hyperlipidemia, and vitamin D [Vit D] levels. Methods: We used a sample of 40 females of the same age group, who were divided into Group 1 as a control consists of 18 healthy females and Group II consisted of 22 age matched females with clinical and electrophysiological evidence of CTS. We measured atherogenic index [AI] as a marker of hyperlipidemia, body mass index [BMI], Vit D status and electrophysiological tests of CTS. Results: Subjects with CTS had deficient Vit D status, they had significantly high atherogenic index (AI), and significant high BMI all compared to control Group I. Median sensory conduction velocity was significantly correlated negatively with BMI and atherogenic index, and positively correlated significantly with Vit D status. But median sensory and motor action potential latency were significantly correlated positively with BMI and atherogenic index, and negatively correlated significantly with Vit D status The analysis revealed BMI, atherogenic index and Vit D status as predictors of median nerve sensory and motor action potential latency and sensory nerve conduction velocity in CTS. Conclusion: The results of this study suggest that obesity and hyperlipidemia are potent CTS risk factors and declared the direct association between Vit D status and CTS occurrence. Our study supports the notion of the compensatory neuroprotective role of Vit D which could have a direct impact on the nerves integrity as it has an anti-inflammatory property which acts in relieving nervous insults and stress. .

The Prediction for the Consumer Price Index of Residents in Perspective of Time Series Method in Case of Chongqing

The consumer price index (CPI) measures the relative number of changes in the price level of consumer goods and services over time, reflecting the trend and degree of changes in the price level of goods and services purchased by residents. This article uses the ARMA model to analyze the fluctuation trend of the CPI (taking Chongqing as an example) and make short-term predictions. To test the predictive performance of the model, the observation values from January to December 2023 were retained as the reference object for evaluating the predictive accuracy of the model. Finally, through trial predictions of the data from May to August 2023, it was found that the constructed model had good fitting performance.

Work Ability Index and Work Ability Score: A Comparation between both Scores in a Persistent COVID-19 Cohort

Aims: The present study aims to compare the assessment of work ability based on the use of the Work Ability Index (WAI) with another questionnaire base only on the use of WAI’s first item, termed as the “Work Ability Score” (WAS). Study design: A cohort of 384 Spanish workers included in a Post COVID-19 condition or persistent COVID-19 multicenter research was utilized. Place and Duration of Study: This cohort was enlisted in four hospitals (Hospital Universitario 12 de Octubre, Madrid;Hospital Universitario Virgen Macarena, Sevilla, Andalucía;Hospital Universitario Gregorio Marañón, Madrid and Complejo Asistencial Universitario de Salamanca, Castilla y León), since 2021 until 2022. Methodology: 384 Spanish workers (176 men and 208 women;aged 20 to 70 years) with Post COVID-19 condition or persistent COVID-19 were included. Descriptive analysis of primary scores was conducted. Given the non-normal distribution of data, the Mann-Whitney and Kruskal-Wallis tests were employed. Spearman and Kendall correlations were employed to assess the relationship between WAI and WAS, also used weighted Kappa to estimate the degree agreement between WAI and WAS. Logistic regression models were utilized to study determinants influencing WAI and WAS, categorized as poor or moderate. Results: WAI had an average score of 32.98 (SD = 10.28), whereas WAS had an average of 5.95 (SD = 2.77). Significant differences were observed in both WAI and WAS across the same variables. Strong and statistically significant correlations were evident between WAI and WAS (rs = 0.83, p < 0.001). All the variables used in the logistic regression model (gender, the sector employment, and previous chronic diseases) were statistically significant in both questionnaires. Conclusion: WAS questionnaire could be used as a tool for reliable assessment of work ability among Spanish workers with Post COVID-19 condition or Persistent CO-VID-19.

TyG指数和AIP与慢性冠脉综合征严重程度的相关性

[目的]探讨慢性冠脉综合征(CCS)患者血浆动脉硬化指数(AIP)和甘油三酯葡萄糖乘积(TyG)指数与其严重程度的相关性。[方法]回顾性选取2017年5月—2023年5月就诊于兰州大学第一医院心内科行冠状动脉造影检查确诊为CCS的患者298例,收集临床指标,根据冠状动脉造影结果计算Gensini积分,比较不同Gensini积分组的临床资料,线性回归分析Gensini积分升高的影响因素,受试者工作特征(ROC)曲线判断AIP和TyG指数对CCS患者冠状动脉病变严重程度的预测价值。[结果]该人群男性占77.9%,平均年龄(61.9±8.0)岁;Gensini高积分组的校正AIP(aAIP)和TyG指数高于低积分组和中积分组,差异具有显著性;线性回归分析显示总胆固醇(TC)、高密度脂蛋白胆固醇(HDLC)、aAIP和TyG指数是Gensini积分升高的影响因素(均P<0.05);相关分析显示aAIP和TyG指数与左心室射血分数(LVEF)呈负相关,与Gensini积分呈正相关,与支架植入和支架植入数量呈正相关(均P<0.05);ROC曲线结果显示,aAIP阈值为1.924时预测Gensini积分≥41分的ROC曲线下面积(AUC)为0.583(95%CI 0.525~0.640),灵敏度为92.62%,特异度为25.50%,约登指数为0.181;TyG指数阈值为8.748时预测Gensini积分≥41分的AUC为0.768(95%CI 0.716~0.815),灵敏度为77.18%,特异度为67.11%,约登指数为0.443。[结论]aAIP和TyG指数与CCS患者的严重程度正相关,两者升高均可预测CCS患者冠状动脉病变严重程度,但TyG指数预测能力优于aAIP。

基于无人机多光谱影像的寒地水稻品质估测

【目的】在稻谷收获前准确估测稻米品质,为改善水稻养分管理、实现优质优价提供参考。【方法】试验在黑龙江省佳木斯市大兴农场和青龙山农场进行,两个地点土壤肥力具有较大差异。每个农场选择一块稻田,以20 m×20 m间隔采集土壤样品分析碱解氮含量,通过变量施氮形成产量水平、长势差异明显的水稻群体。利用大疆精灵4四旋翼多光谱无人机获取水稻分蘖期、拔节期、抽穗期和成熟期冠层多光谱数据。成熟期采集长势具有明显差异的水稻样品和对应的土壤样品,测定土壤有机质和速效氮、磷、钾含量,水稻籽粒蛋白质和直链淀粉含量,产量和食味值,随机选择其中67%的数据通过逐步多元线性回归构建不同生育时期的品质估算模型,其余33%的数据用于模型的验证。【结果】大兴农场水稻成熟期土壤有机质、碱解氮、有效磷和速效钾含量的变异系数分别为11.65%、14.44%、37.66%和11.60%,青龙山农场分别为14.45%、14.32%、36.37%和28.51%。成熟期两个地点水稻产量和食味值的变异系数均大于10%,青龙山农场水稻蛋白质含量变异系数也超过10%,而两地稻米直链淀粉含量的变异系数仅为1.11%~1.83%,因此,水稻直链淀粉含量不适合用于后续的品质估测分析。分蘖期至抽穗期,大兴农场和青龙山农场水稻蛋白质多元回归模型的R~2和RMSE分别为0.262~0.794和0.259~0.686,食味值多元回归模型的R~2和RMSE分别为0.240~0.755和4.211~7.588,估测效果不理想。成熟期,大兴农场和青龙山农场水稻蛋白质多元回归模型的R~2和RMSE分别为0.791~0.874和0.166~0.365,食味值多元回归模型的R~2和RMSE分别为0.786~0.852和2.836~4.039。成熟期基于植被指数的蛋白质和食味值估测精确度优于抽穗期。在抽穗期,将土壤pH、有机质、碱解氮、有效磷、速效钾等指标与植被指数一起建立与蛋白质和食味值的多元回归模型,大兴农场水稻蛋白质模型的R~2由0.585提高到0.720,RMSE由0.301降低至0.247;两农场食味值模型的R~2由0.565~0.755提高到0.706~0.787,RMSE由4.318~4.854降低至3.993~4.029,基本可以满足对稻米品质估测的精度,而在成熟期加入上述土壤指标提升精度不明显。【结论】水稻成熟期利用多光谱无人机对稻米品质进行原位估测的精度较高,如果将估测时期提前到抽穗期,除植被指数外,还需配合土壤有机质和速效养分含量数据来提高多光谱无人机预测稻米品质的精度。

急性前壁ST段抬高型心肌梗死患者直接冠状动脉介入术后微循环阻力指数与左心室不良重构的相关性

目的:评估急性前壁ST段抬高心肌梗死(acute anterior ST elevation myocardial infarction,STEMI)患者直接经皮冠状动脉介入术(primary percutaneous coronary intervention,PPCI)后微循环阻力指数(index of microcirculatory resistance,IMR)与1年后左心室不良重构(left ventricular adverse remodeling,LVAR)之间的关系。方法:采用单中心回顾性队列研究,连续选择2014年1月至2017年8月在北京大学第三医院住院的前壁STEMI并行PPCI患者,术后即刻通过压力/温度导丝测量IMR。利用血清肌酸激酶(creatine kinase,CK)峰值评估梗死面积,心肌梗死(myocardial infarction,MI)后1 d和1年时评估超声心动图,将左心室舒张末期容积(left ventricular end-diastolic volume,LVEDV)较基线增加≥20%定义为LVAR。结果:共入选43例患者,平均年龄(58.7±12.4)岁。根据IMR正常参考值将患者分为两组,IMR>25(n=23)组较IMR≤25组(n=20)患者冠状动脉造影显示梗死相关血管完全闭塞率(95.7%vs.65.0%,P=0.029)更高,血清CK峰值水平更高[4090(383,15833)vs.1580(396,5583),P=0.004],室壁瘤发生率更高(30.4%vs.5.0%,P=0.021)。MI后1 d两组LVEDV差异无统计学意义[(111.0±18.8)mL vs.(115.0±23.6)mL,P=0.503],而1年后IMR>25组LVEDV明显高于IMR≤25组[(141.5±33.7)mL vs.(115.9±27.9)mL,P=0.018]。IMR>25组LVAR发生比例更高(47.4%vs.11.8%,P=0.024)。二元Logistics回归显示IMR[B=0.079,exp(B)(95%CI)为1.082(1.018~1.149),P=0.011]和血清甘油三酯(triglyceride,TG)水平[B=1.610,exp(B)(95%CI)为5.005(1.380~18.152),P=0.014]是患者MI后1年发生LVAR的预测因素,IMR对1年后发生LVAR具有良好的预测价值(曲线下面积=0.749,P=0.019),IMR>29为良好的临界点,敏感性81.8%,特异性68.0%。结论:STEMI患者PPCI术后即刻测定IMR可以反映微血管功能,而微血管功能障碍是STEMI后1年左心室不良重构的有力预测指标。

Learned Index和B-Tree在不同分布数据上的性能对比及优化

Learned Index是一种通过训练模型来建立输入数据和存储位置之间映射关系的索引,它能学习到数据间分布的信息,而不同的数据分布将影响模型训练准确率和模型复杂度之间的平衡。为了探索Learned Index适用的场景,使用不同分布、不同数据量的数据对它和加以优化的可更新的自适应学习索引(ALEX)进行性能测试,并与B-Tree进行对比,最终发现Learned Index构建大批量数据的索引时间比B-Tree短,读操作性能、存储空间大小有明显的优势,但写操作性能较差,因此得出Learned Index更适用于大数据情景下的在线分析处理(OLAP)数据库,用于静态数据的存储和查询操作的结论。基于B-Tree的索引结构,对初版Learned Index的结构进行了优化和调整,最终使优化后Learned Index在大批量数据的读写操作性能上有明显提高,其中读操作最高达到原版Learned Index的2倍,写操作最高达到原版的3倍。

BD-77雾化吸入给药对肺炎支原体感染小鼠的治疗作用

目的评价BD-77雾化吸入给药对肺炎支原体肺炎小鼠模型的治疗作用。方法Balb/c小鼠按照体质量随机分为正常对照组、模型对照组、阿奇霉素对照组(42 mg·kg^(-1)·d^(-1))、BD-77高剂量组(75 mg·mL^(-1),雾化15 min)、BD-77低剂量组(37.5 mg·mL^(-1),雾化15 min)。以肺炎支原体滴鼻感染建立小鼠支原体肺炎模型,雾化给药4 d后,通过小鼠体重及肺重计算肺指数和肺指数抑制率,酶联免疫吸附试验(ELISA)检测肺组织中白介素-6(IL-6)、白介素-1β(IL-1β)、肿瘤坏死因子-α(TNF-α)含量及血清中C反应蛋白(CRP)水平,苏木精-伊红(HE)染色评估小鼠肺组织病理学变化,全面评价BD-77对小鼠支原体肺炎的治疗作用。结果BD-772个剂量组雾化吸入给药15 min均可显著降低小鼠肺指数,减轻肺部炎症病变,降低肺组织中IL-6、IL-1β、TNF-α含量及血清CRP水平。结论BD-77雾化吸入可治疗支原体感染小鼠肺炎,本研究为BD-77开发作为防治肺炎支原体肺炎的药物提供了实验室数据支持。

面向老龄社会的社区建成环境可步行性测度研究

选取大庆市设施布局、路网形态各异的老龄化社区为研究对象,对其可步行性展开研究。宏观与微观层面建立社区可步行性综合测度模型,利用AHP层次分析法对影响指标进行定性定量的测度评价;中观层面应用步行指数的方法对设施分布及可达性进行分析。结果表明:可步行性综合测度模型和步行指数可以较好的反映社区的可步行性;土地利用多样性、路网结构方式、设施分布及步行环境质量等因素都影响社区步行友好水平。建议:对于社区规划:构建合理路网结构,增加社区用地多样性,打造良好步行环境,提升老年人步行舒适性和愉悦性。对于建成社区:调整现有道路空间,优化停车空间和停车方式,健全社区养老服务设施体系。

玄武岩纤维棒聚合物混凝土的弯曲韧性

研究了玄武岩纤维棒(BFB)的纤维增强指数I_(R)对玄武岩纤维棒聚合物混凝土(BFB-PC)韧性指标T_((2(n-1)))(n)的影响,通过分形理论探究了T_((2(n-1)))(n)与裂缝形貌的关系,并建立了弯曲韧性计算模型.结果表明:当IR=90.0时,BFB对BFB-PC的增韧效果最优,此时BFB-PC的弯曲韧性比未掺BFB时提升了8.39倍;BFB的增韧阈值为IR=37.5和IR=90.0;当IR相同时,与未掺聚合物的混凝土相比,聚灰比为0.06的BFB-PC T_((2(n-1)))(n)更高;IR越大裂缝形貌越复杂,T(2(n-1))(n)与裂缝分形维数呈二次函数关系;本文提出的弯曲韧性计算模型准确描述了BFB对PC梁的增韧作用,其试验值与理论值的相对误差小于15.00%.

高校图书馆科研数据管理服务能力评价指标体系研究

本文通过对相关文献和主流模型的梳理,从形式、内容、效用三个维度构建高校图书馆科研数据管理服务能力评价指标体系,并通过一系列科学验证,最终得到由机构支撑力、管理服务力、社会效应力3个一级指标,经费资源支撑、数据资源管理、用户素养教育、学术影响力等11个二级指标,成本效益分析、数据使用规范、用户素养教育内容、科研成果产出等35个三级指标构成的指标体系。构建高校图书馆科研数据管理服务能力评价指标体系,在为国内实践研究提供评价工具的同时,也可以促进高校图书馆科研数据管理服务规范化发展。

化学外加剂对粉煤灰湿法细化活化的影响

将粉煤灰(FA)作为矿物掺合料使用,是降低胶凝材料碳排放的重要手段之一,但其早期活性低是学者们普遍关注的问题。本研究提出在湿磨过程中引入化学功能组分来提升FA细化活化效率的技术思路;通过激光粒度仪(PSD)、pH仪、全谱直读等离子体发射光谱仪(ICP)、XRD、SEM和TG-DTG等测试手段评价了FA的物化性能及活性指数,揭示了液相研磨机械力和化学溶蚀协同作用机理。结果表明:引入TIPA、TEA、NaOH、Na_(2)SO_(4)及电石渣(CS)化学功能组分优化了湿磨的液相环境介质,可显著提升湿磨效率;当FA的中值粒径降低至2μm时,TIPA+CS作用效果最为显著,研磨时间由原来的120 min缩短至40 min,缩短67%。从活性指数的角度来看,1 d龄期时,Na_(2)SO_(4)作用效果最为显著,湿磨FA的活性指数达到60.1%;3 d、7 d、28 d龄期时,TIPA+CS作用效果较好,湿磨FA的活性指数分别可达到81.3%、89.1%、97%。在液相研磨机械力作用过程中,液相环境介质可溶蚀粉煤灰表面,促进表面[AlO_(4)]和[SiO_(4)]的解聚,加速离子溶出,形成钙矾石、C-S-H凝胶等水化产物,显著提升FA的湿磨细化活化效率。

钻井过程中井漏特征精细识别方法研究与应用

井漏是钻井工程中普遍存在的井下复杂问题,严重影响着钻井施工安全与钻井周期,井漏特征精细识别是高效治理井漏的关键。首先,综合测井、钻井、录井及地质等资料,结合漏层力学性质与物理机理分析,利用加权系数法,建立了基于“井漏综合指数”的井漏层位识别新方法。然后,研究了漏失通道类型及尺寸、漏失压差、漏失速度等井漏特征参数的定量分析方法,并给出计算模型,形成了多信息融合的井漏特征精细识别方法。该方法在X区块进行了实例分析,分析结果表明,X区块实际井资料的处理结果与现场实际漏失地层的层位、漏失类型及漏失速度等井漏特征基本吻合。井漏特征精细识别方法综合考虑了井漏的主要影响因素,利用其可以准确识别漏层的特征,为防漏堵漏技术优化及施工提供科学依据。

Colombian Migration and the Body Mass Index: The Relationship between Migration and Weight Gain among Colombian Migrants

The Latin American Migration Project-Colombia is used to study the Body Mass Index (BMI) of Colombian migrants to determine whether their BMI score increased the longer they were abroad. The study contributes to the literature on BMI by studying Colombian migrants, an understudied migrant group. Duration of trip is used as a measure of acculturation. The study also evaluates the claim that trip duration is a measure of acculturation using data specific to migrants, which shows that trip duration is an adequate proxy measure of acculturation. The study includes current migrants, returned migrants and non-migrants. The study accounts for the selectivity of migration by comparing migrants to non-migrants, as some studies highlight the health selectivity of migration. The study uses multinomial regression to test whether the probability of being overweight and/or obese is associated with spending more time abroad. Consistent with studies conducted within the receiving countries, the study finds that increased duration of trip is positively and significantly associated with the probability of being overweight and obese. Furthermore, the study also shows that among return migrants there is a negative relationship between time they had remained in Colombia and probability of being obese. The findings show that migrants put on weight while abroad and lose that weight the longer they remain in Colombia. The findings show that place has an indelible impact on health through migrant’s weight.

数智环境下社交媒体用户算法素养评价指标体系构建研究

[目的/意义]构建社交媒体用户算法素养评价指标体系,科学地测量社交媒体的算法素养,发现社交媒体用户算法素养存在的问题,进而展开有针对性的算法素养教育。[方法/过程]采用文献研究法、专家调查法以及层次分析法,根据国内外相关研究成果,从算法意识与态度、算法知识、算法技能、算法规范4个维度构建社交媒体用户算法素养评价指标体系,并对算法素养评价指标权重进行分析,为提升社交媒体用户算法素养提出有针对性的建议和策略。[结果/结论]通过对社交媒体用户算法素养评价指标体系分析,未来可以从三个方面提升社交媒体用户的算法素养:将算法素养纳入通识教育体系;以风险教育为切入点加强算法风险知识与算法风险控制能力的培养;丰富算法素养教育与培训的形式。

生物质热转化过程中积灰沾污结渣特性及趋势预测研究进展

为阐明生物质灰的沾污结渣特性及其趋势预测研究现状,使生物质能热转化利用过程更加安全,在综合分析生物质灰沾污结渣的危害及机制的基础上,从沾污结渣特性与沾污结渣预测两方面归纳国内外研究进展,梳理出影响结渣的主要因素——灰分组成、反应温度、气氛和添加剂等;并对沾污结渣趋势的预测方法和研究趋势进行分析。针对实际工程中锅炉受热面结渣和腐蚀问题,可以采用混烧、混入添加剂、水洗、酸洗、改变受热面材料、优化锅炉和烟道结构设计、优化反应条件等措施解决。在生物质灰沾污结渣趋势预测方面,目前并没有完整的统一标准,简单沿用煤灰的结渣指标存在严重的不适应性,且现有的预测方法通常只考虑固态或熔融成分对结渣的影响,而忽略了碱金属、氯、硫等元素挥发与温度变化的关系。因此,以热转化过程中碱金属的气-固分配趋势为基础,结合不同温度下生物质灰的特点及成灰特性,建立适用于不同温度下生物质灰的沾污结渣预测模型,是下一步研究应重点关注的问题。

Investigating the Relationship between TyG, TyG-BMI Index and Laboratory Indicators and COVID-19 Severity

Objective: The objective of this study was to investigate the relationship between the triglyceride-glucose (TyG) index, triglyceride-glucose-BMI (TyG-BMI) index, laboratory indices, and disease severity in patients with COVID-19. Methods: A retrospective analysis of COVID-19 patients treated at a tertiary hospital in Mianyang City, Sichuan Province, China, from 1 May to 31 May 2023 was performed. The patients were divided into two groups: 66 cases in the moderate group and 61 cases in the severe group. Additionally, 69 uninfected individuals from the medical examination center during the same period were selected as the control group. Spearman rank correlation was used to determine the correlation between the indices and COVID-19 severity. Multiple logistic regression analysis was performed to identify the factors affecting COVID-19 severity. ROC curves were constructed to assess the predictive value of the TyG and TyG-BMI indices for severe COVID-19. Results: There were significant differences in smoking and diabetes between the three groups (P Conclusion: Smoking, AST, ALB, TyG index, and TyG-BMI index are valuable in assessing the severity of COVID-19, with the TyG-BMI index having a higher predictive value than the TyG index.

Development and Application of Water Quality Index (WQI) for the Evaluation of the Physico-Chemical Quality of Groundwater in Gold Mining Areas of Southeastern Senegal

Water is the most essential requirement for life. It provides a variety of purposes such as a source of water supply for drinking, domestic and industrial use, irrigated agriculture, livestock, and mining activities. Evaluating the status of water quality from traditional approaches does not guarantee the whole overview of the water quality situation. Therefore, developing a tool that can convert multiple parameters data into information that is understandable by both technical and non-technical personnel is vital. In this context, the purpose of this paper was to develop, calculate, and apply a water quality index for assessing the suitability (for drinking purposes) of groundwater in the gold mining areas in south-eastern Senegal. The development of this index based on WHO water quality guidelines followed the five standards steps i.e., parameters selection, sub-index formation, parameters weighting and sub-index aggregation and evaluation. Finally, the WQI summarized twelve key water quality parameters into 05 simple terms (excellent, good, medium, poor, and very poor) which is more relevant for reporting to managers and the public in a consistent manner. Thus, it was observed in the study area, that the water quality indexes in artisanal and industrial mining areas are either poor or very poor while in the reference stations (where there are no mining activities) WQI are either good or excellent. This situation was attributed to the effects of mining activities in such zones which contribute to the pollution of groundwater with heavy metals, nitrates, and suspended solids.