Relative accuracy of spatial predictive models for lynx Lynx canadensis derived using logistic regression-AIC,multiple criteria evaluation and Bayesian approaches

We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems （GIS） -based approaches： logistic regression and Akaike＇s Information Criterion （AIC）, Multiple Criteria Evaluation （MCE）, and Bayesian Analysis （specifically Dempster-Shafer theory）. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified （overall accuracy）, the failure to predict a species where it occurred （omission error） and the prediction of presence where there was absence （commission error）. Our overall accuracy showed the logistic regression approach was the most accurate （74.51%）. The multiple criteria evaluation was intermediate （39.22%）, while the Dempster-Shafer （D-S） theory model was the poorest （29.90%）. However, omission and commission error tell us a different story： logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach （e.g. Dempster-Shafer） that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans .

Multi-Model Approach for Assessing the Influence of Calibration Criteria on the Water Balance in Ouémé Basin

Hydrological models are very useful tools for evaluating water resources, and the hydroclimatic hazards associated with the water cycle. However, their calibration and validation require the use of performance criteria which choice is not straightforward. This paper aims to evaluate the influence of the performance criteria on water balance components and water extremes using two global rainfall-runoff models (HBV and GR4J) over the Ouémé watershed at the Bonou and Savè outlets. Three (3) Efficacy criteria (Nash, coefficient of determination, and KGE) were considered for calibration and validation. The results show that the Nash criterion provides a good assessment of the simulation of the different parts of the hydrograph. KGE is better for simulating peak flows and water balance elements than other efficiency criteria. This study could serve as a basis for the choice of performance criteria in hydrological modelling.

Unequal Distribution of Innovation Efforts for Neglected Tropical Diseases: The Role of Funding Evaluation Criteria

Background: International research and innovation efforts for neglected tropical diseases have increased in recent decades due to disparities in overall health research funding in relation to global burden of disease. However, within the field of neglected tropical diseases some seem far more neglected than others. In this research the aim is to investigate the distribution of resources and efforts, as well as the mechanisms that underpin funding allocation for neglected tropical diseases. Methodology: A systematic literature review was conducted to establish a comprehensive overview of known indicators for innovation efforts related to a wide range of neglected tropical diseases. Articles were selected based on a subjective evaluation of their relevance, the presence of original data, and the breadth of their scope. This was followed by thirteen in-depth open-ended interviews with representatives of private, public and philanthropic funding organizations, concerning evaluation criteria for funding research proposals. Results: The findings reveal a large difference in the extent to which the individual diseases are neglected with notable differences between absolute and relative efforts. Criteria used in the evaluation of research proposals relate to potential impact, the probability of success and strategic fit. Private organizations prioritize strategic fit and economic impact;philanthropic organizations prioritize short-term societal impact;and public generally prioritize the probability of success by accounting for follow-up funding and involvement of industry. Funding decisions of different types of organizations are highly interrelated. Conclusions: This study shows that the evaluation of funding proposals introduces and retains unequal funding distribution, reinforcing the relative neglect of diseases. Societal impact is the primary rationale for funding but application of it as a funding criterion is associated with significant challenges. Furthermore, current application of evaluation criteria leads to a primary focus on short-term impact. Through current practice, the relatively most neglected diseases will remain so, and a long-term strategy is needed to resolve this.

Local Criteria Used by Farmers to Evaluate the Agronomic Performance and the Fertilizing Capacity of Cowpea Varieties: Diversity, Variability and Proximal Relation with Agronomic Measurements in Contrasted Sahelian Locations

When contributing to participatory research, farmers usually appreciate the performance of cowpea varieties using qualitative scores. The score they attribute to each variety are based on local knowledge. The specific criteria they individually use to attribute a score are not well described. The objectives of this work were to: 1) identify and describe exhaustively the local criteria used by farmers to measure the agronomic performance of cowpea;2) assess the variability and statistical structure of these farmer criteria across local contexts;3) and analyze the association between these farmer criteria and the classical agronomic measurement. To achieve these objectives, an augmented block design was implemented across fifteen locations in the regions of Maradi, Dosso and Tillabéri, representing a diversity of local contexts. From a set of 36 cowpea varieties, fifteen varieties were sown per location, including five varieties (controls) common to all locations. In each location, two replicates were sown in randomized Fisher’s blocks. After agronomic measurement and participatory evaluation (scoring of varieties by farmers), a group survey (focus group) was conducted in each location to identify the criteria considered by farmers to found their discretional scoring of varieties during the participatory evaluation. The analysis of the data identified, across locations, thirteen criteria defined by farmers to characterize the agronomic performance of cowpea. Some of these criteria were different according to location. Farmers ranked the three varieties with the best performance for each agronomical trait (Top 3 varieties). A comparison of the farmer ranking with the ranking based on agronomic measurements revealed similarity and complementary between both methods. This study highlighted the importance of considering both local and scientific knowledge in local varietal evaluations.

Coal-rock gas:Concept,connotation and classification criteria

In recent years,great breakthroughs have been made in the exploration and development of natural gas in deep coal-rock reservoirs in Junggar,Ordos and other basins in China.In view of the inconsistency between the industrial and academic circles on this new type of unconventional natural gas,this paper defines the concept of"coal-rock gas"on the basis of previous studies,and systematically analyzes its characteristics of occurrence state,transport and storage form,differential accumulation,and development law.Coal-rock gas,geologically unlike coalbed methane in the traditional sense,occurs in both free and adsorbed states,with free state in abundance.It is generated and stored in the same set of rocks through short distance migration,occasionally with the accumulation from other sources.Moreover,coal rock develops cleat fractures,and the free gas accumulates differentially.The coal-rock gas reservoirs deeper than 2000 m are high in pressure,temperature,gas content,gas saturation,and free-gas content.In terms of development,similar to shale gas and tight gas,coal-rock gas can be exploited by natural formation energy after the reservoirs connectivity is improved artificially,that is,the adsorbed gas is desorbed due to pressure drop after the high-potential free gas is recovered,so that the free gas and adsorbed gas are produced in succession for a long term without water drainage for pressure drop.According to buried depth,coal rank,pressure coefficient,reserves scale,reserves abundance and gas well production,the classification criteria and reserves/resources estimation method of coal-rock gas are presented.It is preliminarily estimated that the coal-rock gas in place deeper than 2000 m in China exceeds 30×10^(12)m^(3),indicating an important strategic resource for the country.The Ordos,Sichuan,Junggar and Bohai Bay basins are favorable areas for large-scale enrichment of coal-rock gas.The paper summarizes the technical and management challenges and points out the research directions,laying a foundation for the management,exploration,and development of coal-rock gas in China.

Evaluation of AVNRT & AVRT by Different Criteria: Old & New

The two most frequent causes of paroxysmal SVT are atrioventricular tachycardia (AVRT) and atrioventricular nodal re-entrant tachycardia (AVNRT). The purpose of this study was to assess the diagnostic efficacy of traditional and newly proposed ECG criteria in the identification of Avnrt and Avrt. Aim of the Study: The aim of this study was to evaluate Atrioventricular Nodal Reentrant Tachycardia (AVNRT) and Atrioventricular Re-entrant Tachycardia (AVRT) using both traditional and novel criteria. Methods: This prospective observational study was conducted at the Electrophysiology Unit, Department of Cardiology, National Institute of Cardiovascular Diseases (NICVD) in Dhaka, from February 2019 to January 2020. A total of 62 patients with Supraventricular Tachycardia (SVT) undergoing electrophysiology study (EPS) were included. Standard ECG criteria were applied for the differential diagnosis, and electrophysiological diagnoses were made using established criteria. Statistical analysis, including descriptive statistics and appropriate tests, was performed using SPSS 23.0. Result: In our study of 62 patients with Supraventricular Tachycardia (SVT), we found that 66.1% had AVNRT and 33.9% had AVRT. The mean age in AVNRT was higher than AVRT (41.3 ± 9.7 vs. 38.5 ± 14.3, p = 0.36) with statistically no significant difference, with similar gender distribution between AVNRT and AVRT groups. Classical AVNRT criteria were present in 30.6% of patients, and 45.2% showed a Pseudo R' wave in aVR. Additionally, 30.6% had an RP interval ≥100ms, more prevalent in AVRT patients (66.7%). Conclusion: Integrating traditional and novel criteria, including lead aVR analysis, enhances the electrocardiographic diagnosis of AVNRT and AVRT, offering a pathway to refined patient care.

基于Sage-Husa-AUKF的AIC多模型优化的锂离子SOC估计

随着新能源技术异军突起,从发电端到受电端能源存储与并网问题研究不断深入,锂离子电池SOC充放问题也得到关注。其中EKF算法对锂离子能源模块改进时,存在阶段性波动及噪声问题会引起输出数值范围较大,并且一般能源模块采用单一阶梯的Thevenin/RC模型,模型初始化存在自适应问题。对此本文通过Sage-Husa-AUKF改进策略优化EKF算法,并且引入AIC多阶可调模块解决单一阶梯模式固化问题。通过这种融合模式改进算法,一方面使得锂离子模块自身物理结构具有可调性和自适应性,另一方面改进型算法使得系统输出平稳、启动性稳定。通过多次实验数据论证,本方法可以将锂离子能源系统输出波动降低到1%范围,对模块误差和精确度进行了有效改进,系统开启阶段到充放电完成,全过程平滑、无发散,可以用在供电端电能质量差、高次谐波多的锂离子模块SOC估计,可以有效弥补电力能源系统的稳定性。

基于Beers Criteria 2023 评估我院门诊老年患者潜在不适当用药现状

目的评估我院门诊老年患者潜在不适当用药(PIM)的发生情况,分析影响因素,探讨如何促进老年合理用药。方法收集常州市第一人民医院2023年5月~2023年7月,年龄65~99岁门诊患者处方,按照Beers Criteria 2023对患者的用药进行分析,采用二元logistic回归模型分析发生PIM的影响因素。结果最终筛选出24217例患者,男11823例,占比48.8%,女12394例,占比51.2%。疾病数量、用药种类、年龄为PIM发生的危险因素,就诊科室数为保护因素(P<0.05)。结论Beers Criteria 2023检出PIM率为20.37%,临床药师应结合临床,减少用药种类以减少老年患者PIM的发生率,对必需使用导致PIM药物治疗的老年患者应加强监测并个体化用药,保证老年患者用药安全。

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.

Evaluating the Association between Human Papillomavirus and Vulvar Cancer:A Comprehensive Analysis Using Bradford Hill Criteria

Background:The role of human papillomavirus(HPV)in the development of vulvar cancer(VC)has been widely studied,but findings have been inconsistent.Despite numerous meta-analyses exploring the potential link between HPV and VC,the association remains controversial due to inherent limitations in meta-analytic methods.Objectives:To address this controversy,the study aims to investigate the potential link between HPV and VC using the Bradford Hill criteria,which offer a more comprehensive framework for establishing causation.Methodology:The study began by extracting all relevant studies on the association between HPV and VC from the PubMed database.The potential links were then assessed by examining the data using the major postulates of the Bradford Hill criteria.To ensure the reliability of the findings,the methodologies of the identified studies were critically evaluated to account for possible false-negative and false-positive results.Results:The assessment of previous studies against the Bradford Hill criteria revealed that the major postulates were not fulfilled.Conclusion:Based on the findings,it can concluded that there is no causal association between HPV and VC.

异构人工智能加速器统一接口(AICL)标准正式启动实施 试验验证单位持续征集中

1月17日,新一代人工智能标准与应用工信部重点实验室学术委员会会议在北京成功召开。会上,凝聚人工智能计算产业共识《异构人工智能加速器统一接口AICL》课题通过评审。该课题将推动异构人工智能加速器互联互通,提升异构智算系统的集成部署效率,目前已取得显著成效。同时,T/CESA 1303—2023《人工智能异构人工智能加速器统一接口》AICL团体标准正式发布并启动实施,试验验证单位持续征集中。AICL(全称AI Computing Library,人工智能计算库),是基于《人工智能异构人工智能加速器统一接口》等国家标准的跨架构.

Contribution of GIS to Soil Landscape Mapping by Multi-Criteria Analysis Using Weighting: The Case of the Square Degrees of M’Bahiakro (Centre) and Daloa (Centre-West) in Ivory Coast

As part of the drive to improve coffee and cocoa production in Ivory Coast, studies are carried out to identify soils that are favourable for these crops. It is therefore necessary to orientate soil investigations based on reliable criteria that best discriminate soil cover. With this in mind, this study is being carried out to help improve survey methods by mapping soil landscapes. It uses GIS and weighted multicriteria analysis. To do this, satellite images were processed and the geological map of the square degrees of M’Bahiakro and Daloa was reclassified. The results show that relief is the main factor in soil landscape differentiation, with respective weights of 0.58 and 0.67 for the forest and pre-forest zones. In contrast, the weight of geological formation in soil landscape differentiation remains low (0.05 for the forest zone and 0.07 for the pre-forest zone). The criteria used on the base of aggregation sum methods have made it possible to formulate soil landscape mapping prediction functions according to agro-ecological environments in the humid intertropical zone. This is essential for the orientation of soil survey work. Nevertheless, other comparative methods, such as the coding mapping method, could provide elements for discussion to validate the models.

Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

模型选择信息量准则AIC及其在方差分析中的应用

【目的】探讨模型选择信息量准则AIC在方差分析模型选择中的必要性和意义。【方法】简要介绍了模型选择信息量准则AIC的概念,推导了AIC在方差分析模型选择的公式,并运用AIC对水稻品种比较试验数据进行了最佳ANOVA模型选择分析。【结果】对5个水稻品种比较试验进行方差分析模型的选择是必要的;AIC准则在方差分析模型选择中是一种简单有效的方法。【结论】AIC可用于方差分析模型的选择,以改进方差分析结论的可靠性。

基于AIC准则的锂离子电池变阶RC等效电路模型研究

提出一种变阶RC等效电路模型,并基于赤池信息量准则(AIC)辨识不同SOC处RC模型的最优阶数,兼顾了模型的准确度和实用性。通过脉冲充放电、恒流充放电以及自定义UDDS循环工况实验验证了该模型的有效性。变阶RC模型通过略增加模型的复杂度,能更加准确地描述锂离子电池两端陡、中间平的非线性电压特性,相对误差在1%以内,具有较高的实用价值。

AIC与BIC在亲体-补充量模型选择中的应用及比较

由于渔业资源评估中补充量的剧烈变动、亲体量的测量误差以及时间序列的偏差常常使亲体 补充量(SR)关系模型的确定存在很大偏差问题。本文以7种SR(Stock Recruitment)模型的模拟数据作为观测数据,研究了AIC(AkaikeInfor mationCriterion)与BIC(BayesianInformationCriterion)在SR模型选择中的应用。作为例证,文中采用AIC和BIC对8组实际的SR数据进行了SR模型的选择,并对其结果进行了比较。参数的估计方法为最大似然法(Maximumlikelihoodmethod)。结果表明,AIC和BIC在SR模型选择中是有效的。但是,对于嵌套模型,BIC可能比AIC更有效。

AIC准则在数据融合中的应用

提出了一种利用AIC准则来确定信息源信任度系数的方法,并以此衡量信息源的质量.实验结果表明,利用AIC准则确定的信任度系数可以得到较好的图像识别结果,同时也证明了将该方法应用在数据融合中的可行性.

基于AIC准则的回归方法在建筑物变形分析中的应用

鉴于引起建筑物变形的地质、水文、气候、附近开挖等原因的不确定性和各种因素影响度的不确定性,本文提出将基于AIC准则的回归理论应用到变形分析中,实现了多项式回归系数和幂次方的自适应处理,并实现了建筑物变形分析中变形因子和回归函数的自动确定。在MATLAB下编写了算法,并提出了优化方案。实践证明,这一理论很适合于变形分析。

基于AIC准则和时窗能量比的电缆局部放电在线检测与定位

在利用多高频电流传感器进行电缆局部放电在线检测与定位时,针对局放信号初至时刻拾取精度不高影响定位精度的问题,提出一种基于AIC(Akaike’s Information Criterion)准则和时窗能量比的局放故障在线检测与精确定位方法。首先利用时窗能量比检测出局部放电发生的时窗,然后求取确定时窗的局部AIC特征曲线,并基于AIC准则精确拾取局放信号初至时刻。最后,运用到达时间法对局放源进行定位。仿真结果表明,该方法定位精度高,抗噪声干扰能力强,在-2 d B的噪声环境下可实现99.85%的定位准确率,具备工程实用价值。

极大似然估计与AIC准则联合建模

将极大似然估计与ＡＩＣ准则有机结合进行回归模型建模。这样不仅可省去一般回归模型建模时繁杂的模型检验工作，而且还可快速有效地同时估计模型参数和确定模型阶数。最后用实例验证本方法的实用性和正确性。