Potential Conditioning Factors Research Articles

Automatic Mapping of Potential Landslides Using Satellite Multitemporal Interferometry

Mapping potential landslides is crucial to mitigating and preventing landslide disasters and understanding mountain landscape evolution. However, the existing methods to map and demonstrate potential landslides in mountainous regions are challenging to use and inefficient. Therefore, herein, we propose a method using hot spot analysis and convolutional neural networks to map potential landslides in mountainous areas at a regional scale based on ground deformation detection using multitemporal interferometry synthetic aperture radar. Ground deformations were detected by processing 76 images acquired from the descending and ascending orbits of the Sentinel-1A satellite. In total, 606 slopes with large ground deformations were automatically detected using hot spot analysis in the study area, and the extraction accuracy rate and the missing rate are 71.02% and 7.89%, respectively. Subsequently, based on the high-deformation areas and potential landslide conditioning factors, we compared the performance of convolutional neural networks with the random forest algorithm and constructed a classification model with the area under the curve (AUC), accuracy, recall, and precision for testing being 0.75, 0.75, 0.82, and 0.75, respectively. Our approach underpins the ability of interferometric synthetic aperture radar (InSAR) to map potential landslides regionally and provide a scientific foundation for landslide risk management. It also enables an accurate and efficient identification of potential landslides within a short period and under extremely hazardous conditions.

A new approach in the development and analysis of the landslide susceptibility map of the hillslopes of Bujumbura, Burundi

As in other hilly and mountainous regions of the world, the hillslopes of Bujumbura are prone to landslides. In this area, landslides impact human lives and infrastructures. Despite the high landslide-induced damages, slope instabilities are less investigated. The aim of this research is to assess the landslide susceptibility using a probabilistic/statistical data modeling approach for predicting the initiation of future landslides. A spatial landslide inventory with their physical characteristics through interpretation of high-resolution optic imageries/aerial photos and intensive fieldwork are carried out. Base on in-depth field knowledge and green literature, let’s select potential landslide conditioning factors. A landslide inventory map with 568 landslides is produced. Out of the total of 568 landslide sites, 50 % of the data taken before the 2000s is used for training and the remaining 50 % (post-2000 events) were used for validation purposes. A landslide susceptibility map with an efficiency of 76 % to predict future slope failures is generated. The main landslides controlling factors in ascendant order are the density of drainage networks, the land use/cover, the lithology, the fault density, the slope angle, the curvature, the elevation, and the slope aspect. The causes of landslides support former regional studies which state that in the region, landslides are related to the geology with the high rapid weathering process in tropical environments, topography, and geodynamics. The susceptibility map will be a powerful decision-making tool for drawing up appropriate development plans in the hillslopes of Bujumbura with high demographic exposure. Such an approach will make it possible to mitigate the socio-economic impacts due to these land instabilities

Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential

Delineation of the groundwater’s potential zones is a growing phenomenon worldwide due to the high demand for fresh groundwater. Therefore, the identification of potential groundwater zones is an important tool for groundwater occurrence, protection, and management purposes. More specifically, in arid and semi-arid regions, groundwater is one of the most important natural resources as it supplies water during the drought period. The present research study focused on the delineation of potential groundwater zones in Saveh City, the northern part of the Markazi Province in Iran. The groundwater potential mapping was prepared using hybrid deep learning and machine learning algorithm of the boosted tree (BT), artificial neural network (ANN), deep learning neural network (DLNN), deep learning tree (DLT), and deep boosting (DB). This study was carried out by using fourteen groundwater potential conditioning factors and 349 each for springs and non-springs points. The performance of each model was validated through statistical analysis of sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and receiver operating characteristic (ROC)-area under curve (AUC) analysis. The validation result showed that the success rate of AUC is very good for the DB model (0.87–0.99) and other models are also good i.e. BT (0.81–0.90), ANN (0.77–0.82), DLNN (0.84–0.86), and DLT (0.83–0.91). Among the several factors used in this study altitude, rainfall, distance to fault and soil types are the more important conditioning factors for groundwater potential modeling. Finally, all the models in this study had high efficiency in groundwater potential mapping, but it is recommended to use the Deep Boost model due to the better results in future studies. The result of this work will be useful to planners for optimal use and future planning of groundwater.

Improvement of Credal Decision Trees Using Ensemble Frameworks for Groundwater Potential Modeling

Groundwater is one of the most important sources of fresh water all over the world, especially in those countries where rainfall is erratic, such as Vietnam. Nowadays, machine learning (ML) models are being used for the assessment of groundwater potential of the region. Credal decision trees (CDT) is one of the ML models which has been used in such studies. In the present study, the performance of the CDT has been improved using various ensemble frameworks such as Bagging, Dagging, Decorate, Multiboost, and Random SubSpace. Based on these methods, five hybrid models, namely BCDT, Dagging-CDT, Decorate-CDT, MBCDT, and RSSCDT, were developed and applied for groundwater potential mapping of DakLak province of Vietnam. Data of 227 groundwater wells of the study area were utilized for the construction and validation of the models. Twelve groundwater potential conditioning factors, namely rainfall, slope, elevation, river density, Sediment Transport Index (STI), curvature, flow direction, aspect, soil, land use, Topographic Wetness Index (TWI), and geology, were considered for the model studies. Various statistical measures, including area under receiver operating characteristic (AUC) curve, were applied to validate and compare the performance of the models. The results show that performance of the hybrid CDT ensemble models MBCDT (AUC = 0.770), BCDT (AUC = 0.731), Dagging-CDT (AUC = 0.763), Decorate-CDT (AUC = 0.750), and RSSCDT (AUC = 0.766) improved significantly in comparison to the single CDT (AUC = 0.722) model. Therefore, these developed hybrid models can be applied for better ground water potential mapping and groundwater resources management of the study area as well as other regions of the world.

Does it matter if those who matter don't mind? Effects of gang versus delinquent peer group membership on labeling processes.

Despite renewed interests in the labeling perspective and the impact of official intervention on individuals' future outcomes, scant attention has been given to potential conditioning factors for theorized labeling processes. We argue that, when viewed through a symbolic interactionist lens, variations in the nature of primary social groups, through which individuals filter official labels like arrest, may generate patterns for subsequent self-concept and delinquency that are contrary to what labeling theory indicates. To test our rationale, we offer a moderated mediation model in which gang membership is expected to differentially impact the effect of arrest on future delinquency through an intermediary mechanism: self-esteem. We test a gang-nongang dichotomy and then probe further to test whether hypothesized effects are gang specific or occur similarly for nongang youths with highly delinquent peer groups. Analyzed using Rochester Youth Development Study (RYDS) data (N = 961), comparisons between gang members and nonaffiliated youths with similarly highly delinquent peer groups revealed no significant differences in conditional indirect effects of arrest on self-esteem and future delinquency; the two groups were similarly insulated from any negative impact of arrest on self-esteem. For nongang youths with fewer delinquent peers, however, arrest significantly reduced later self-esteem, which in turn increased their future delinquency.

Efficacy in type 2 diabetes mellitus remission in patients undergoing bariatric surgery

ObjectivesTo assess remission of type 2 diabetes mellitus (T2DM) after bariatric surgery, to analyze potential conditioning factors, and to compare Spanish and American remission criteria. Material and methodsA retrospective study of diabetic patients undergoing Roux-en-Y gastric bypass from 2009 to 2015. Data collected included age, sex, time since T2DM diagnosis, antidiabetic drugs, insulin (type and dose), weight and BMI, percent excess weight lost, HbA1c, blood glucose levels, and course of T2DM after surgery according to Spanish and American criteria, including a descriptive analysis and correlation between both. ResultsThe study sample consisted of 106 patients. Outcomes one year after surgery was as follows (Spanish criteria): complete remission 65.9%, partial remission 5.5%, improvement 18.9%, no change 9.7% (at 5 years: 68.4, 5.3, 10.5, and 15.8%, respectively). Outcomes according to ADA criteria were as follows: complete remission 61.5%, partial remission 5.3%, and no remission 28.6% (after 5 years, complete remission 68.4%). There was a good correlation between both classifications (rho=0.974; p<0.001). Mean HbA1c levels: 7.3±1.8% at baseline; 5.7±1% at one year; 6.3±1.2% at 5 years. Chance of remission was lower in patients aged over 50 years (54.4% vs. 88.2%; p=0.001), with T2DM diagnosed more than 10 years before (26.3% vs. 81.8%; p<0.001), on insulin treatment (31.3% vs. 87.9%; p<0.001), and with HbA1c levels ≥8% (40% vs. 77%; p=0.001). ConclusionsAt our hospital, bariatric surgery is associated to a high remission rate of T2DM in patients with morbid obesity, with a good correlation between Spanish and American criteria. Age over 50 years old, long T2DM duration, poorer baseline metabolic control, and previous insulin treatment are markers of poorer response.

Eficacia en la remisión de la diabetes mellitus tipo 2 en pacientes sometidos a cirugía bariátrica en nuestro medio

ObjectivesTo assess remission of type 2 diabetes mellitus (T2DM) after bariatric surgery, to analyze potential conditioning factors, and to compare Spanish and American remission criteria. Material and methodsA retrospective study of diabetic patients undergoing Roux-en-Y gastric bypass from 2009 to 2015. Data collected included age, sex, time since T2DM diagnosis, antidiabetic drugs, insulin (type and dose), weight and BMI, percent excess weight lost, HbA1c, blood glucose levels, and course of T2DM after surgery according to Spanish and American criteria, including a descriptive analysis and correlation between both. ResultsThe study sample consisted of 106 patients. Outcomes one year after surgery was as follows (Spanish criteria): complete remission 65.9%, partial remission 5.5%, improvement 18.9%, no change 9.7% (at 5 years: 68.4, 5.3, 10.5, and 15.8%, respectively). Outcomes according to ADA criteria were as follows: complete remission 61.5%, partial remission 5.3%, and no remission 28.6% (after 5 years, complete remission 68.4%). There was a good correlation between both classifications (Rho=0.974; P<.001). Mean HbA1c levels: 7.3±1.8% at baseline; 5.7±1% at one year; 6.3±1.2% at 5 years. Chance of remission was lower in patients aged over 50 years (54.4 vs. 88.2%; P=.001), with T2DM diagnosed more than 10 years before (26.3 vs. 81.8%; P<.001), on insulin treatment (31.3 vs. 87.9%; P<.001), and with HbA1c levels≥8% (40 vs. 77%; P=.001). ConclusionsAt our hospital, bariatric surgery is associated to a high remission rate of T2DM in patients with morbid obesity, with a good correlation between Spanish and American criteria. Age over 50 years old, long T2DM duration, poorer baseline metabolic control, and previous insulin treatment are markers of poorer response.

Application of vulnerability modeling techniques in groundwater resources management: a comparative study

The sustainability management of groundwater resource globally is challenged by its vulnerability to pollution resulting from anthropogenic activities. In order to address this problem, the DRASTIC index model (DIM) method among the existing vulnerability modeling techniques is commonly used. OWA-DRASTIC index model (ODIM) technique is another recently developed method for the same task. This study investigated the application of these vulnerability-biased modeling methods in a multi-faceted geologic setting at Perak Province, Malaysia with the view of establishing their efficiencies. The models considered seven pollution potential conditioning factors (PPCFs) obtained from difference data sources. Applying the GIS-based multi-criterial algorithm of these models, the PPCFs were related for developing multi-parameters-based vulnerability index model equations. Groundwater vulnerability to pollution index (GVPI) maps was produced from the synthesized estimated results of the applied multi-parameters-based vulnerability index model equations. The reliability of the produced GVPI maps was established using analyzed groundwater quality data results. The obtained prediction accuracy results for the ODIM-based GVPI map and DIM-based GVPI map are 85.71 and 64.29%, respectively. Besides, the regression coefficient results obtained from the spatially estimate from the DIM and ODIM’ vulnerability index’s values relationship with the pH and manganese concentrations give 83 and 85% for the ODIM technique and 68 and 63% for the DIM technique, respectively. The overall results indicated that the applied ODIM method in the area is a better alternative to the conventional DIM method. The produced GVPI maps can be useful to regional planners and environmental managers entrusted with the protection of groundwater resource.

A multicriteria approach to karst subsidence hazard mapping supported by weights-of-evidence analysis

Soil subsidence/collapse is a major geohazard occurring in karst regions. It occurs as suffosion or dropout sinkholes developing in the overburden overlying karst. Less frequently it corresponds to a breakdown of karst void ceiling (i.e., collapse sinkhole). This hazard can cause significant engineering challenges. Therefore decision-makers require the elaboration of methodologies for reliable predictions of such hazards (e.g., karst subsidence susceptibility and hazards maps, planning strategies, priority areas for detailed investigations).This study aims at developing a methodological framework for the evaluation of potential conditioning factors controlling the occurrence of sinkholes in a context of limestone karst: potential conditioning factors are first determined based on underlying physical processes for different geological contexts (barren and mantled karsts). Then the relevance of each factor is evaluated against a set of representative karst subsidence locations using the weight-of-evidence theory and relevant factors are tested for independence. Relevant and independent factors are finally weighed and combined together (i.e., superimposed) to achieve karst subsidence susceptibility models. The best model (i.e., the one showing the highest predictability) is determined by a receiver operating characteristic (ROC) curve analysis, which is performed using a set of independent and representative karst subsidence locations.The method is applied to one case study where mantled karst setting prevails (Val d'Orléans, south of Paris). Results show higher susceptibility in mantled karst with significant role of the overburden lithology (presence/absence of low-permeability layer) and position of the karst piezometric surface within the overburden. The limited area of barren karst shows a low susceptibility.Although this approach was developed for a specific karst context, it can easily be replicated in other karst contexts (e.g., interstratal karst, chalk or evaporitic karsts) which are known to be highly susceptible to karst subsidence even if some of the conditioning factors will be different.

Statistical Modeling of Carbonation in Concrete Incorporating Recycled Aggregates

Durability and recycling are two major concerns in the construction industry. Concrete carbonation may impair reinforced concrete durability as it favors the onset of reinforcement corrosion. The use of recycled aggregates, as a replacement for natural aggregates, in construction applications is a feasible way of recycling given materials from construction and demolition waste. The aim of this study is to quantify the contribution of potential conditioning factors to the carbonation rate of concrete incorporating recycled aggregates. For this purpose, a multiple linear regression technique was used, considering the mix design characteristics, environmental conditions, and recycled aggregates’ properties as explanatory variables, capable of predicting the coefficient of carbonation. The investigation was founded on ample experimental data, collated from several studies. This study proposes a general model, in which the carbonation in concrete depends on the 28-day compressive strength, clinker content, environment’s CO₂ content, and aggregates’ equivalent water absorption. The models are statistically significant, with determination coefficients suggesting high correlation between the coefficients of accelerated carbonation of concrete in the experimental data and values predicted by the proposed models.

Statistical modelling of carbonation in reinforced concrete

As time passes the properties of concrete change as a result of its interaction with the environment and durability is affected. Reinforcement corrosion is singled out in various studies as being mainly responsible for reinforced concrete degradation. Concrete alkalinity protects the reinforcement bars from corrosion but the carbonation phenomenon significantly contributes to the destruction of their passive coating, thus favouring the corrosion onset. Therefore, concrete carbonation is considered an important problem both in Civil Engineering and in Materials Science. This study’s main objective is to try to quantify the contribution of potential conditioning factors to concrete carbonation’s rate. This study addresses the statistical modelling of the concrete carbonation phenomenon, using a large number of results (964 case studies), collected in the literature. A computational method (multiple linear regression analysis) is used to define a mathematical model that can estimate the carbonation coefficient as a function of a set of conditioning factors. These models allow the estimation of the carbonation coefficient, and consequently the carbonation as a function of the variables considered statistically significant in explaining this phenomenon. Two distinct models are proposed to suit predictions to two environmental exposure relative humidity ranges.

Weakening of Intervocalic /s/ in the Nijmegen Corpus of Casual Spanish

This study describes the weakening of intervocalic /s/ in the Nijmegen Corpus of Casual Spanish and investigates the role of several potential conditioning factors, including morphological, lexical and probabilistic variables. Three acoustic parameters were examined: voicing, the difference in high-band (4–8 kHz) intensity between /s/ and the following vowel, and the duration of the dip in low-band (0–1.5 kHz) intensity in /s/. Over a third of the /s/ consonants exhibited uninterrupted voicing. All three parameters were highly sensitive to speech rate and, less consistently, to prosodic factors such as word position and stress. We also found that /s/ suffixes in redundant morphosyntactic contexts were more prone to weakening than other word-final /s/ segments. Several high-frequency words were particularly prone to weakening, but no general probabilistic effects were observed for factors claimed to favor reduction such as word frequency, contextual predictability or grammatical class. These findings demonstrate the complex variability characteristic of reduction phenomena in spontaneous speech.

Predicting sinkholes by means of probabilistic models

Abstract A quantitative method for assessing sinkhole susceptibility and hazard has been developed and independently tested in an evaporite karst of NE Spain. Three genetic types of sinkholes have been mapped: 947 small cover-collapse sinkholes, 23 large collapse sinkholes and 24 large subsidence depressions. By analysing the statistical relationships between the sinkholes and the potential conditioning factors, susceptibility models have been developed. These were evaluated using several strategies that have allowed us to assess quantitatively the quality of the models. The best susceptibility model for the small collapse sinkholes was transformed into a hazard map by considering the frequency and average size of an independent population of new occurrences. The susceptibility and hazard models obtained indicate that it is possible to produce reasonably good predictions on the distribution and frequency of sinkholes in the study area.

Probabilistic sinkhole modelling for hazard assessment

AbstractA method for quantitatively assessing sinkhole susceptibility (spatial probability) and hazard (spatio‐temporal probability) has been developed and independently tested in a 50 km2 sector of the Ebro Valley evaporite karst. Three genetic types of sinkholes have been mapped in the floodplain and a terrace surface: 947 small cover‐collapse sinkholes (type 1, terrace), large collapse sinkholes (type 2, floodplain) and large subsidence depressions (type 3, floodplain). The type 1 sinkhole inventory includes two temporal populations: 447 sinkholes formed before 24 November 2005, and 500 between that date and 2 November 2006. Sinkhole susceptibility models have been elaborated analysing the statistical relationships between the sinkholes of the 2005 inventory and a set of potential conditioning factors. The independent evaluation (validation) of the susceptibility models by means of several strategies (random, sequentially excluded, and temporal) has allowed us to select the most significant variables for each sinkhole type and assess quantitatively the quality of models; which are reasonable for the three sinkhole types. Validation has also provided information on the contribution of specific variables and the effect of changing their accuracy to the prediction capability of models. Susceptibility models for type 3 sinkholes have been validated satisfactorily with the 2006 sinkhole inventory (temporal validation). The best susceptibility model has been transformed into a hazard map considering the frequency of sinkholes that occurred in each susceptibility class between 2005 and 2006, as well as their average size. The susceptibility and hazard models obtained could be used as an objective basis for the application of mitigation measures, either of preventive or corrective nature. Copyright © 2008 John Wiley &amp; Sons, Ltd.

‘… That is the question': complementizer omission in extraposed that-clauses

This article investigates the omission of the that-complementizer in extraposed subject clauses (e.g. It is obvious (that) she did it), which has so far received very little attention in the literature. Using corpus data from the British component of the International Corpus of English (ICE-GB) various potential conditioning factors are analysed. Of these the following are found to have a major impact on the choice of zero that: informality of the text category, type of matrix predicate, and information value of the complement clause. On the basis of these corpus results the article then proposes a unified explanation for the use of that or zero by positing an underlying abstract feature of ‘distance’; for the that-complementizer, a semantic residue of its original demonstrative use, which gives rise to different pragmatic interpretations, depending on the actual use of that in context.

The gradient tissue culture method

Preliminary results with a simple method of tissue culture which provides a continuous gradient in cell number, oxygen tension, oxidation-reduction potential, and cell conditioning factors are described and pictured. Cells may readily be examined in in situ at any desired interval with any stain, or by phase microscopy in the living state. The method has proved far superior to any method hitherto tried for cultures of hemic cells of the blood and blood-forming organs. Many possible applications and variations are suggested on this simple procedure of inserting a sterile standard slide at a 45 ° angle into a deep suspension culture in a 1-pint wide mouth French square bottle and allowing the cells to settle out on the surface.