Test of a mediation model of perceived organisational support

This study examined the mediating influence of trust in organization (TIO) and organization-based self-esteem (OBSE) on the relationship between perceived organization support (POS) and its work outcomes. Data were obtained from employee–supervisor dyads from multiple organizations located in a major city in southern China. Structural equation modeling results revealed that: (a) POS related to TIO and OBSE and (b) TIO and OBSE fully mediated the relationship between POS and the work outcomes of organizational commitment and in-role performance, but partially mediated the POS–organizational citizenship behavior relationship.

Antecedents and outcomes of abusive supervision:test of a trickle-down model

The authors examined antecedents of abusive supervision and the relative importance of interactional and procedural justice as mediators of the relationship between abusive supervision and the work outcomes of affective organizational commitment and individual- and organization-directed citizenship behaviors. Data were obtained from subordinate-supervisor dyads from a telecommunication company located in southeastern China. Results of moderated regression analysis revealed that authoritarian leadership style moderated the relationship between supervisors' perceptions of interactional justice and abusive supervision such that the relationship was stronger for supervisors high rather than low in authoritarian leadership style. In addition, results of structural equation modeling analysis revealed that subordinates' perceptions of interactional but not procedural justice fully mediated the relationship between abusive supervision and the work outcomes. Implications for future investigations of abusive supervision are discussed. Copyright 2007 by the American Psychological Association.

Countering the trend towards careerist orientation in the age of downsizing:test of a social exchange model

Predicated on the assumption that employee careerist orientation resulting from organizational actions to cut costs constitutes a potential threat to their long-term profitability and success, this study proposed and tested a social exchange model of careerist orientation in the People's Republic of China. Specifically, it was hypothesized that organizational justice and career growth opportunities will be related to careerist orientation, but the relationship will be mediated by trust in employer. Structural equation modeling results provided support for the model. Trust in organization fully mediated the relationship between careerist orientation and its antecedents.

Smart microsystems for cell manipulations

This thesis documents the design, manufacture and testing of a passive and non-invasive micro-scale planar particle-from-fluid filter for segregating cell types from a homogeneous suspension. The microfluidics system can be used to separate spermatogenic cells from testis biopsy samples, providing a mechanism for filtrate retrieval for assisted reproduction therapy. The system can also be used for point-of-service diagnostics applications for hospitals, lab-on-a-chip pre-processing and field applications such as clinical testing in the third world. Various design concepts are developed and manufactured, and are assessed based on etched structure morphology, robustness to variations in the manufacturing process, and design impacts on fluid flow and particle separation characteristics. Segregation was measured using image processing algorithms that demonstrate efficiency is more than 55% for 1 µl volumes at populations exceeding 1 x 107. the technique supports a significant reduction in time over conventional processing, in the separation and identification of particle groups, offering a potential reduction in the associated cost of the targeted procedure. The thesis has developed a model of quasi-steady wetting flow within the micro channel and identifies the forces across the system during post-wetting equalisation. The model and its underlying assumptions are validated empirically in microfabricated test structures through a novel Micro-Particle Image Velocimetry technique. The prototype devices do not require ancillary equipment nor additional filtration media, and therefore offer fewer opportunities for sample contamination over conventional processing methods. The devices are disposable with minimal reagent volumes and process waste. Optimal processing parameters and production methods are identified with any improvements that could be made to enhance their performance in a number of identified potential applications.

Assessment of physical and hydrological properties of biological soil crusts using x-ray microtomography and modelling

Biological soil crusts (BSCs) are formed by aggregates of soil particles and communities of microbial organisms and are common in all drylands. The role of BSCs on infiltration remains uncertain due to the lack of data on their role in affecting soil physical properties such as porosity and structure. Quantitative assessment of these properties is primarily hindered by the fragile nature of the crusts. Here we show how the use of a combination of non-destructive imaging X-ray microtomography (XMT) and Lattice Boltzmann method (LBM) enables quantification of key soil physical parameters and the modeling of water flow through BSCs samples from Kalahari Sands, Botswana. We quantify porosity and flow changes as a result of mechanical disturbance of such a fragile cyanobacteria-dominated crust. Results show significant variations in porosity between different types of crusts and how they affect the flow and that disturbance of a cyanobacteria-dominated crust results in the breakdown of larger pore spaces and reduces flow rates through the surface layer. We conclude that the XMT–LBM approach is well suited for study of fragile surface crust samples where physical and hydraulic properties cannot be easily quantified using conventional methods.

Study of effect on tensile stress test from distortion of fibre laser welded Ti6Al4V using FEA

Distortion is one type of defect in the weld, which is troublesome for some reasons, especially in thin plate welding. Distortion was found in fibre laser welding processing for 0.7mm thickness Ti6Al4V plate. The purpose of this paper is to understand and evaluate the effect of distortion on stress level by FEA and tensile test. A group of 0.7mm Ti6Al4V plates welded using continuous wave fibre laser. FEA models were established for fibre laser welded Ti6Al4V in abaqus 6.7. © (2011) Trans Tech Publications.

Site specific growth of metal catalyzed silica nanowires for biological and chemical sensing

In this research the integration of nanostructures and micro-scale devices was investigated using silica nanowires to develop a simple yet robust nanomanufacturing technique for improving the detection parameters of chemical and biological sensors. This has been achieved with the use of a dielectric barrier layer, to restrict nanowire growth to site-specific locations which has removed the need for post growth processing, by making it possible to place nanostructures on pre-pattern substrates. Nanowires were synthesized using the Vapor-Liquid-Solid growth method. Process parameters (temperature and time) and manufacturing aspects (structural integrity and biocompatibility) were investigated. Silica nanowires were observed experimentally to determine how their physical and chemical properties could be tuned for integration into existing sensing structures. Growth kinetic experiments performed using gold and palladium catalysts at 1050°C for 60 minutes in an open-tube furnace yielded dense and consistent silica nanowire growth. This consistent growth led to the development of growth model fitting, through use of the Maximum Likelihood Estimation (MLE) and Bayesian hierarchical modeling. Transmission electron microscopy studies revealed the nanowires to be amorphous and X-ray diffraction confirmed the composition to be SiO2 . Silica nanowires were monitored in epithelial breast cancer media using Impedance spectroscopy, to test biocompatibility, due to potential in vivo use as a diagnostic aid. It was found that palladium catalyzed silica nanowires were toxic to breast cancer cells, however, nanowires were inert at 1μg/mL concentrations. Additionally a method for direct nanowire integration was developed that allowed for silica nanowires to be grown directly into interdigitated sensing structures. This technique eliminates the need for physical nanowire transfer thus preserving nanowire structure and performance integrity and further reduces fabrication cost. Successful nanowire integration was physically verified using Scanning electron microscopy and confirmed electrically using Electrochemical Impedance Spectroscopy of immobilized Prostate Specific Antigens (PSA). The experiments performed above serve as a guideline to addressing the metallurgic challenges in nanoscale integration of materials with varying composition and to understanding the effects of nanomaterials on biological structures that come in contact with the human body.

(Table 1) Sample characteristics, test consolidations and calculated elastic parameters of ODP Sites 194-1193 and 194-1196

This study is based on rock mechanical tests of samples from platform carbonate strata to document their petrophysical properties and determine their potential for porosity loss by mechanical compaction. Sixteen core-plug samples, including eleven limestones and five dolostones, from Miocene carbonate platforms on the Marion Plateau, offshore northeast Australia, were tested at vertical effective stress, sigma1', of 0-70 MPa, as lateral strain was kept equal to zero. The samples were deposited as bioclastic facies in platform-top settings having paleo-water depths of <10-90 m. They were variably cemented with low-Mg calcite and five of the samples were dolomitized before burial to present depths of 39-635 m below sea floor with porosities of 8-46%. Ten samples tested under dry conditions had up to 0.22% strain at sigma1' = 50 MPa, whereas six samples tested saturated with brine, under drained conditions, had up to 0.33% strain. The yield strength was reached in five of the plugs. The measured strains show an overall positive correlation with porosity. Vp ranges from 3640 to 5660 m/s and Vs from 1840 to 3530 m/s. Poisson coefficient is 0.20-0.33 and Young's modulus at 30 MPa ranged between 5 and 40 GPa. Water saturated samples had lower shear moduli and slightly higher P- to S-wave velocity ratios. Creep at constant stress was observed only in samples affected by pore collapse, indicating propagation of microcracks. Although deposited as loose carbonate sand and mud, the studied carbonates acquired reef-like petrophysical properties by early calcite and dolomite cementation. The small strains observed experimentally at 50 MPa indicate that little mechanical compaction would occur at deeper burial. However, as these rocks are unlikely to preserve their present high porosities to 4-5 km depth, further porosity loss would proceed mainly by chemical compaction and cementation.

Análise cefalométrica: ortodontistas x radiologistas

Cephalometric analysis is the mensuration of linear and angular measures through demarcation points as distances and lines on teleradiography, and is considered of fundamental importance for diagnosis and orthodontic planning. In this manner, the objective of this research was to compare cephalometric measurements obtained by dentists and radiologists from the analysis of the same radiograph, in a computerized cephalometric analysis program. All research participants marked 18 cephalometric points on a 14-inch notebook computer, as directed by the program itself (Radiocef 2®). From there, they generated 14 cephalometric parameters including skeletal, dental-skeletal, dental and soft tissue. In order to verify the intra-examiner agreement, 10 professionals from each group repeated the marking of the points with a minimum interval of eight days between the two markings. The intra-group variability was calculated based on the coefficients of variation (CV). The comparison between groups was performed using the Student t-test for normally distributed variables, and using the Mann-Whitney test for those with non-normal distribution. In the group of orthodontists, the measurements of Pog and 1-NB, SL, S-Ls Line, S-Li Line and 1.NB showed high internal variability. In the group of radiologists, the same occurred with the values of Pog and 1-NB, S-Ls Line, S-Li Line and 1.NA. In the comparison between groups, all the analyzed linear values and two angular values showed statistically significant differences between radiologists and dentists (p <0.05). According to the results, the interexaminer error in cephalometric analysis requires more attention, but does not come from a specific class of specialists, being either dentists or radiologists.

Otimização do controle do diagrama de radiação de radares de varredura para rastreio de foguetes usando o método GAMMC para o Caso Planar (GAMMC-P)

Launching centers are designed for scientific and commercial activities with aerospace vehicles. Rockets Tracking Systems (RTS) are part of the infrastructure of these centers and they are responsible for collecting and processing the data trajectory of vehicles. Generally, Parabolic Reflector Radars (PRRs) are used in RTS. However, it is possible to use radars with antenna arrays, or Phased Arrays (PAs), so called Phased Arrays Radars (PARs). Thus, the excitation signal of each radiating element of the array can be adjusted to perform electronic control of the radiation pattern in order to improve functionality and maintenance of the system. Therefore, in the implementation and reuse projects of PARs, modeling is subject to various combinations of excitation signals, producing a complex optimization problem due to the large number of available solutions. In this case, it is possible to use offline optimization methods, such as Genetic Algorithms (GAs), to calculate the problem solutions, which are stored for online applications. Hence, the Genetic Algorithm with Maximum-Minimum Crossover (GAMMC) optimization method was used to develop the GAMMC-P algorithm that optimizes the modeling step of radiation pattern control from planar PAs. Compared with a conventional crossover GA, the GAMMC has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, the GAMMC prevents premature convergence, increases population fitness and reduces the processing time. Therefore, the GAMMC-P uses a reconfigurable algorithm with multiple objectives, different coding and genetic operator MMC. The test results show that GAMMC-P reached the proposed requirements for different operating conditions of a planar RAV.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Mathematical Modeling of Perifusion Cell Culture Experiments

In perifusion cell cultures, the culture medium flows continuously through a chamber containing immobilized cells and the effluent is collected at the end. In our main applications, gonadotropin releasing hormone (GnRH) or oxytocin is introduced into the chamber as the input. They stimulate the cells to secrete luteinizing hormone (LH), which is collected in the effluent. To relate the effluent LH concentration to the cellular processes producing it, we develop and analyze a mathematical model consisting of coupled partial differential equations describing the intracellular signaling and the movement of substances in the cell chamber. We analyze three different data sets and give cellular mechanisms that explain the data. Our model indicates that two negative feedback loops, one fast and one slow, are needed to explain the data and we give their biological bases. We demonstrate that different LH outcomes in oxytocin and GnRH stimulations might originate from different receptor dynamics. We analyze the model to understand the influence of parameters, like the rate of the medium flow or the fraction collection time, on the experimental outcomes. We investigate how the rate of binding and dissociation of the input hormone to and from its receptor influence its movement down the chamber. Finally, we formulate and analyze simpler models that allow us to predict the distortion of a square pulse due to hormone-receptor interactions and to estimate parameters using perifusion data. We show that in the limit of high binding and dissociation the square pulse moves as a diffusing Gaussian and in this limit the biological parameters can be estimated.

A Bayesian Dirichlet-Multinomial Test for Cross-Group Differences

Testing for differences within data sets is an important issue across various applications. Our work is primarily motivated by the analysis of microbiomial composition, which has been increasingly relevant and important with the rise of DNA sequencing. We first review classical frequentist tests that are commonly used in tackling such problems. We then propose a Bayesian Dirichlet-multinomial framework for modeling the metagenomic data and for testing underlying differences between the samples. A parametric Dirichlet-multinomial model uses an intuitive hierarchical structure that allows for flexibility in characterizing both the within-group variation and the cross-group difference and provides very interpretable parameters. A computational method for evaluating the marginal likelihoods under the null and alternative hypotheses is also given. Through simulations, we show that our Bayesian model performs competitively against frequentist counterparts. We illustrate the method through analyzing metagenomic applications using the Human Microbiome Project data.

An Alternative Goodness-of-fit Test for Normality with Unknown Parameters

Goodness-of-fit tests have been studied by many researchers. Among them, an alternative statistical test for uniformity was proposed by Chen and Ye (2009). The test was used by Xiong (2010) to test normality for the case that both location parameter and scale parameter of the normal distribution are known. The purpose of the present thesis is to extend the result to the case that the parameters are unknown. A table for the critical values of the test statistic is obtained using Monte Carlo simulation. The performance of the proposed test is compared with the Shapiro-Wilk test and the Kolmogorov-Smirnov test. Monte-Carlo simulation results show that proposed test performs better than the Kolmogorov-Smirnov test in many cases. The Shapiro Wilk test is still the most powerful test although in some cases the test proposed in the present research performs better.

The Pico de Navas slump (Burgos, Spain): a large rocky landslide caused by underlying clayey sand fluidification

The Pico de Navas landslide was a large-magnitude rotational movement, affecting 50x106m3 of hard to soft rocks. The objectives of this study were: (1) to characterize the landslide in terms of geology, geomorphological features and geotechnical parameters; and (2) to obtain an adequate geomechanical model to comprehensively explain its rupture, considering topographic, hydro-geological and geomechanical conditions. The rupture surface crossed, from top to bottom: (a) more than 200 m of limestone and clay units of the Upper Cretaceous, affected by faults; and (b) the Albian unit of Utrillas facies composed of silty sand with clay (Kaolinite) of the Lower Cretaceous. This sand played an important role in the basal failure of the slide due to the influence of fine particles (silt and clay), which comprised on average more than 70% of the sand, and the high content presence of kaolinite (>40%) in some beds. Its geotechnical parameters are: unit weight (δ) = 19-23 KN/m3; friction angle (φ) = 13º-38º and cohesion (c) = 10-48 KN/m2. Its microstructure consists of accumulations of kaolinite crystals stuck to terrigenous grains, making clayey peds. We hypothesize that the presence of these aggregates was the internal cause of fluidification of this layer once wet. Besides the faulted structure of the massif, other conditioning factors of the movement were: the large load of the upper limestone layers; high water table levels; high water pore pressure; and the loss of strength due to wet conditions. The 3D simulation of the stability conditions concurs with our hypothesis. The landslide occurred in the Recent or Middle Holocene, certainly before at least 500 BC and possibly during a wet climate period. Today, it appears to be inactive. This study helps to understand the frequent slope instabilities all along the Iberian Range when facies Utrillas is present.