238 research outputs found
Multiorder Sequential Joint Inversion of Gravity Data With Inhomogeneous Depth Weighting: From Near Surface to Basin Modeling Applications
Full text linkWe have established a workflow for a multiorder sequential joint inversion (MOSJI) of gravity and gravity gradients, that aims at modeling vertically stacked sources in various geological scenarios. We consider the joint inversion of the gravity data and one of the th-order derivatives of the gravity data. The first step involves separate inversions, which are fundamental to fully exploit the different wavelength-content of the two quantities to invert. The joint inversion is warranted by using the scheme of a sequential joint inversion with a cross-gradient constraint. The algorithm is able to exploit different types of a priori information, such as compactness and inhomogeneous model-weighting function. First, we test this approach on a realistic synthetic model from the SEg Advanced Modeling (SEAM) Phase I model, involving salt and mother salt structures. Then, we consider a synthetic model containing either shallower or deeper karst cavities. These tests produced a better modeling of both shallower and deeper sources, when compared to the separate unconstrained inversions. Thanks to these good results, we apply our method to a real case for cavity detection in Southern Spain. The method shows an accurate modeling of the expected sources. In all the aforementioned tests, we obtain a strong decrease of the cross-gradient values and a meaningful linearization in the scatter plots of physical parameters, both indicating the good performance of the joint inversion
LETM1-Mediated K+ and Na+ Homeostasis Regulates Mitochondrial Ca2+ Efflux
Full text linkCa2+ transport across the inner membrane of mitochondria (IMM) is of major importance for their functions in bioenergetics, cell death and signaling. It is therefore tightly regulated. It has been recently proposed that LETM1—an IMM protein with a crucial role in mitochondrial K+/H+ exchange and volume homeostasis—also acts as a Ca2+/H+ exchanger. Here we show for the first time that lowering LETM1 gene expression by shRNA hampers mitochondrial K+/H+ and Na+/H+ exchange. Decreased exchange activity resulted in matrix K+ accumulation in these mitochondria. Furthermore, LETM1 depletion selectively decreased Na+/Ca2+ exchange mediated by NCLX, as observed in the presence of ruthenium red, a blocker of the Mitochondrial Ca2+ Uniporter (MCU). These data confirm a key role of LETM1 in monovalent cation homeostasis, and suggest that the effects of its modulation on mitochondrial transmembrane Ca2+ fluxes may reflect those on Na+/H+ exchange activity
Investigating the celerity of propagation for small perturbations and dispersive sediment aggradation under a supercritical flow
Full text linkThe paper presents an investigation of the scales of propagation for sediment aggradation in an overloaded
channel. The process has relevant implications for land protection, since bed aggradation reduces channel
conveyance and thus increases inundation hazard; knowing the time needed for the aggradation to take place is
important for undertaking suitable actions. Attention is here focused on supercritical flow, under which the process
is dispersive and a depositional front cannot be clearly recognized; in these conditions, one needs to define
propagation scales locally and instantaneously. Based on spatial and temporal rates of variation of the bed elevation,
we quantify the celerity of propagation for the sediment aggradation wave. Furthermore, considering
that morphological processes are modeled by a system of differential equations, the eigenvalues of the latter
are the celerities of the so-called small perturbations. After a review of existing approaches to determine the
celerity of small perturbations, taking into account or discarding the concentration of transported sediment, the
paper considers a laboratory experiment with temporally and spatially detailed measurements, whose results are
representative of those of several others performed in the same campaign. The relationships between the local
and instantaneous Froude number, the celerity of small perturbations, and the celerity of the aggradation wave
are explored. The celerity of the aggradation wave is correlated to that of the small perturbations, while their
values differ by orders of magnitude. Our results indicate that accounting or not for the solid concentration in the
governing equations does not significantly impact the correlation between the two types of celerity, even if one of
the eigenvalues changes significantly in value. Finally, the aggradation celerity is generally below 0.05 times the
initial flow velocity, with this serving as a rule-of-thumb estimation that may be useful for engineering purposes
Dataset for 'Effect of damping on performance of magnetostrictive vibration energy harvester'.
No full textSupporting Matlab M file - Code for modelling of Energy Harvester Access is currently subject to embargo (09/07/23). For more information please contact the corresponding author, Mojtaba Ghodsi
Corrigendum: Confirmatory factor analysis and gender invariance of the Persian version of psychological control scale: association with internalizing and externalizing behavior problems (Frontiers in Psychology, (2023), 14, (1128264), 10.3389/fpsyg.2023.1128264)
No full textCopyright © 2024 Habibi Asgarabad, Salehi Yegaei, Mokhtari, Izalnoo and Trejos-Castillo. cc-byIn the published article, there was an error in the correspondence details. As well as Pardis Salehi Yegaei, Mojtaba Habibi Asgarabad should also be listed as a corresponding author. The complete correspondence details are shown below: *Correspondence: Pardis Salehi Yegaei Mojtaba Habibi Asgarabad The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated
ORIGINAL ARTICLE Strategic Stakeholder Modelofthe Banking System, Mining: Bank SARMAYE Mojtaba Mali; Strategic Stakeholder Modelofthe Banking System, Mining: Bank SARMAYE
No full textABSTRACT Effective organization is an organization meet requires of its environmental components that continuity of organization survival requires to their supports. The Stakeholders analyze is important because it can be have an effective and influential role in the strategic management process of organization. The research problem is the major benefits conflict of the banks strategic stakeholders. The aim of this study is application and its method is descriptive -analytic. The statistical community for the Strategic stakeholders' research is Bank Sarmayeh Iran
How Do Experts Think? An Investigation of the Barriers to Internationalisation of SMEs in Iran
No full textNowadays, “internationalisation” is a topic of concern for many types of research on small and medium-sized enterprises (SMEs). SMEs pursue internationalization policy as a leading process to keep and improve their position in the competitive business markets. However, SMEs face many challenges that hinder the successful implementation of the internationalization process. This chapter aims to recognise the important barriers to internationalisation for Iranian SMEs. We conduct two studies using a combined exploratory and confirmatory approach. We apply the Delphi method for exploring and forecasting the key barriers in the first study. In the second study, we validate the key indicator employing a Structural Equation Modelling technique for the Confirmatory Factor Analysis of the survey data. In the Delphi method, a group of 24 managers and academic professors in Iran, identified the main barriers. A sample of 210 survey observations was collected from the owner and top managers, senior managers, and employees. The results suggest 8 key factors and 31 indicators of barriers to internationalisation associated with Iranian SMEs: informational, financial, marketing, functional, procedural, governmental, environmental and, tariff and non-tariff. This research contributes to the knowledge of critical obstacles concern for current and future business internationalisation, and the outcomes provide practical implications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
A Multi-Purpose Continuum Robot for Minimally Invasive Surgery
No full textThis thesis is about ''A Multi-Purpose Continuum Robot for Minimally Invasive surgery'' which consists of five chapters. It starts with an Introduction and Literature Review that studies some of the most famous surgical robotic systems and analyses their pros and cons. Chapter two has to do with the problem statement and challenges that need to be addressed while designing our specific surgical tool, and a CAD design of a flexible continuum robot will be done for our brain surgery application. In chapter three, the kinematic modeling of the proposed robot is analyzed by a new model based on the Euler spirals and the results are compared with conventional constant curvature models. In chapter four, a model predictive control algorithm is proposed that considers the input saturation constraints on robot actuators. Finally, a discussion and conclusion will be provided in chapter five
Uncertainty quantification for pavement life-cycle stages
Full text linkLife-cycle assessment (LCA), a common sustainability metric, is usually adopted to quantify the environmental consequences of a product. It has been shown that rolling resistance (RR), a major component of pavement LCA use stage, has significant impact on transportation-related energy consumption. Pavement related RR mainly includes pavement structure, surface roughness (or smoothness) and texture. This research aims at addressing current challenges in pavement LCA use stage. A robust framework is proposed to evaluate RR via developing models for pavement roughness- and structural-induced RR.
A roughness–speed impact (RSI) model was developed to quantify the energy and environmental impacts due to RR. The model uses vehicle-specific power as part of the pavement–vehicle interaction (PVI) analysis. According to the model, one unit change of IRI (1 m/km) results in 3% and 2% fuel consumption, respectively, at high and low speeds (105 and 56 km/h) for passenger cars.
In addition to the RSI model, the study proposes a practical approach to assess the vehicle excess fuel consumption (EFC) due to pavement deflection. The developed relationship relies on the fundamental energy-deformation principles obtained by conducting nonlinear regression analysis on 3-D finite element (FE) simulations. The proposed model is formulated using a quadratic form of maximum pavement deflection. Factors affect EFC includes, truck loading and speed and pavement temperature. It was found that the estimated EFC for a heavy truck could be as low as 0.03% for a half loaded truck at a temperature of 0 °C a speed of 115 km/h and as high as 6.5% for a fully loaded truck at a temperature of 40 °C and a speed of 8 km/h. This could be increased for low volume road pavement structure. At a speed of 100 km/h, a typical HS20-44 truck could consume an additional 0.5% fuel due to structural rolling resistance (SRR).
Uncertainty of pavement roughness has significant impact on the energy and emission output of the pavement-vehicle system depending on the precision level of the model used, input variabilities, and prior knowledge of the model parameters. When quantified uncertainties, successfully utilized in this study, are implemented, LCA parameters prediction would be improved.
The introduced RR models may be used as part of the decision-making for short-term energy and emission reduction policies.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-12-01The student, Mojtaba Ziyadi, accepted the attached license on 2017-12-05 at 10:01.The student, Mojtaba Ziyadi, submitted this Dissertation for approval on 2017-12-05 at 10:10.This Dissertation was approved for publication on 2017-12-05 at 17:05.DSpace SAF Submission Ingestion Package generated from Vireo submission #11853 on 2018-03-13 at 09:56:49Made available in DSpace on 2018-03-13T15:25:25Z (GMT). No. of bitstreams: 3
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Motion Planning of Robotic Systems in Diagnostic and Therapy Applications Using Control and AI
No full textThis thesis presents significant research on robotic motion planning within diagnostic and therapy applications, with a primary focus on the integration of control and AI techniques. The research encompasses three main contributions: a robotic ultrasound imaging method, a robot-assisted ultrasound scanning system, and an innovative framework for uncertainty-aware control in medical robots.
The first component of this thesis introduces a robotic ultrasound imaging method that employs a five Degrees of Freedom (DoFs) robotic system. The primary objective is to achieve precise scanning of breast tissue for the generation of high-quality ultrasound images. This method initiates with a pre-scan phase, wherein geometric analysis of the target within the breast is utilized to determine the desired scanning trajectory. Subsequently, in the post-scan phase, the probe's rotational and translational movements are continually adjusted based on the center of mass of segmented targets within each acquired frame and the average confidence map of the images. The experimental validation of this visual servoing algorithm on a plastisol phantom demonstrates the system's proficiency in controlling the ultrasound probe's motion, effectively targeting tissue, and efficiently executing real-time robotic control loops.
The second significant contribution of this thesis is the development of a robot-assisted ultrasound scanning system, a response to the challenges posed by the COVID-19 pandemic. Traditional ultrasound scans require close contact between the sonographer and the patient, which increases the risk of disease transmission. This novel system mitigates this risk by automating tissue scanning through a dexterous robot arm holding the ultrasound probe. The system constantly evaluates the quality of acquired ultrasound images in real-time using a quality assessment algorithm based on correlation, compression, and noise characteristics. Feedback from the ultrasound images guides the system in automatically adjusting the probe's contact force, ensuring consistent high image quality. An SVM classifier analyzes image features and provides feedback to the robot arm for precise force adjustments. Experimental trials conducted on plastisol phantom tissue confirm the system's capacity to maintain image quality while minimizing direct sonographer-patient contact.
The third and equally crucial contribution of this thesis centers around addressing safety concerns and uncertainty analysis in deep learning-based medical robotic applications for motion planning. The integration of deep learning algorithms into medical robots introduces uncertainties that can compromise the safety of both patients and the overall operation. To tackle this challenge, a pioneering framework for uncertainty-aware control of medical robots is introduced. This framework is particularly designed for a lower-limb exoskeleton intended to assist individuals with disabilities. The framework leverages fast uncertainty analysis within the medical robot's control loop. By quantifying uncertainty levels during both training and testing phases, the proposed framework ensures safe and reliable human-robot interactions.
During the training phase, the framework employs Kullback-Leibler (KL) divergence to identify similarities between labels and predictions. In the testing phase, it utilizes Mahalanobis distance to detect out-of-distribution (OOD) data, enhancing safety and improving decision-making for the robot controller. Experimental trials conducted on the ExoH3 lower-limb exoskeleton illustrate the effectiveness of this uncertainty analysis technique in real-time motion planning and its ability to identify OOD features that may lead to unsafe motion execution.
In summary, this thesis represents a significant advancement in the field of motion planning for robotic systems in diagnostic and therapy applications, particularly addressing critical challenges related to safety and uncertainty. The proposed approaches for robotic ultrasound imaging, robot-assisted ultrasound scanning, and uncertainty-aware control have the potential to enhance the efficacy and safety of medical robotics, ultimately benefiting both patients and healthcare providers
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