A simplified finite element model for assessing steel fibre reinforced concrete structural performance

The present numerical investigation offers evidence concerning the validity and objectivity of the predictions of a simple, yet practical, finite element model concerning the responses of steel fibre reinforced concrete structural elements under static monotonic and cyclic loading. Emphasis is focused on realistically describing the fully brittle tensile behaviour of plain concrete and the contribution of steel fibres on the post-cracking behaviour it exhibits. The good correlation exhibited between the numerical predictions and their experimental counterparts reveals that, despite its simplicity, the subject model is capable of providing realistic predictions concerning the response of steel fibre reinforced concrete structural configurations exhibiting both ductile and brittle modes of failure without requiring recalibration.

Determination of a Total Body Model of Efficiency Applied to a Rowing Movement in Humans

Efficiency represents the ratio of work done to energy expended. In human movement, it is desirable to maximise the work done or minimise the energy expenditure. Whilst research has examined the efficiency of human movement for the lower and upper body, there is a paucity of research which considers the efficiency of a total body movement. Rowing is a movement which encompasses all parts of the body to generate locomotion and is a useful modality to measure total body efficiency. It was the aim of this research to develop a total body model of efficiency and explore how skill level of participants and assumptions of the modelling process affected the efficiency estimates Three studies were used to develop and evaluate the efficiency model. Firstly, the efficiency of ten healthy males was established using rowing, cycling and arm cranking. The model included internal work from motion capture and efficiency estimates were comparable to published literature, indicating the suitability of the model to estimate efficiency. Secondly, the model was developed to include a multi-segmented trunk and twelve novice and twelve skilled participants were assessed for efficiency. Whilst the efficiency estimates were similar to published results, novice participants were assessed as more efficient. Issues such as the unique physiology of trained rowers and a lack of energy transfers in the model were considered contributing factors. Finally the model was redeveloped to account for energy transfers, where skilled participants had higher efficiency at large workloads. This work presents a novel model for estimating efficiency during a rowing motion. The specific inclusion of energy transfers expands previous knowledge of internal work and efficiency, demonstrating a need to include energy transfers in the assessment of efficiency of a total body action.

Searches for Beyond Standard Model Higgs Bosons in pp collisions at sqrt(s) = 8 and 13 TeV with the ATLAS detector

Thesis (Ph.D.)--University of Washington, 2016-08

Recognition of Activities of Daily Living from Topic Model

Research in ubiquitous and pervasive technologies have made it possible to recognise activities of daily living through non-intrusive sensors. The data captured from these sensors are required to be classified using various machine learning or knowledge driven techniques to infer and recognise activities. The process of discovering the activities and activity-object patterns from the sensors tagged to objects as they are used is critical to recognising the activities. In this paper, we propose a topic model process of discovering activities and activity-object patterns from the interactions of low level state-change sensors. We also develop a recognition and segmentation algorithm to recognise activities and recognise activity boundaries. Experimental results we present validates our framework and shows it is comparable to existing approaches.

Characterization of the glial scar tissue in a murine model of spinal cord compression, with focus on hyaluronan

Spinal cord injury (SCI) is a devastating neurological disorder that affects thousands of people each year. Although in recent decades significant progress has been made in relation to understanding the molecular and cellular events underlying the nervous damage, spinal cord injury is still a highly disabling condition for which there is no curative therapy. People affected by spinal cord injuries manifested dysfunction or loss, temporary or permanent, of motor, sensory and / or autonomic functions depending on the spinal lesion damaged. Currently, the incidence rate of this type of injury is approximately 15-40 cases per million people worldwide. At the origin of these lesions are: road accidents, falls, interpersonal violence and the practice of sports. In this work we placed the hypothesis that HA is one of the component of the scar tissue formed after a compressive SCI, that it is likely synthetised by the perilesional glial cells and that it might support the permeation of the glial scar during the late phase of SCI. Nowadays, much focus is drawn on the recovery of CNS function, made impossible after SCI due to the high content of sulfated proteoglycans in the extracellular matrix. Counterbalancing the ratio between these proteoglycans and hyaluronic acid could be one of the experimental therapy to re-permeate the glial scar tissue formed after SCI, making possible axonal regrowth and functional recovery. Therefore, we established a model of spinal cord compression in mice and studied the glial scar tissue, particularly through the characterization of the expression of enzymes related to the metabolism of HA and the subsequent concentration thereof at different distances of the lesion epicenter. Our results show that the lesion induced in mice shows results similar to those produced in human lesions, in terms of histologic similarities and behavioral results. but these animals demonstrate an impressive spontaneous reorganization mechanism of the spinal cord tissue that occurs after injury and allows for partial recovery of the functions of the CNS. As regards the study of the glial scar, changes were recorded at the level of mRNA expression of enzymes metabolizing HA i.e., after injury there was a decreased expression of HA synthases 1-2 (HAS 1-2) and an increase of the expression HAS3 synthase mRNA, as well as the enzymes responsible for the HA catabolism, HYAL 1-2. But the amount of HA measured through the ELISA test was found unchanged after injury, it is not possible to explain this fact only with the change of expression of enzymes. At two weeks and in response to SCI, we found synthesized HA by reactive astrocytes and probably by others like microglial cells as it was advanced by the HA/GFAP+ and HA/IBA1+ cells co-location.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers' consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed. (C) 2016 Elsevier Ltd. All rights reserved.

The synthetic progestin norgestrel modulates Nrf2 signaling and acts as an antioxidant in a model of retinal degeneration

Retinitis pigmentosa (RP) is one of the most common retinal degenerative conditions affecting people worldwide, and is currently incurable. It is characterized by the progressive loss of photoreceptors, in which the death of rod cells leads to the secondary death of cone cells; the cause of eventual blindness. As rod cells die, retinal-oxygen metabolism becomes perturbed, leading to increased levels of reactive oxygen species (ROS) and thus oxidative stress; a key factor in the secondary death of cones. In this study, norgestrel, an FDA-approved synthetic analog of progesterone, was found to be a powerful neuroprotective antioxidant, preventing light-induced ROS in photoreceptor cells, and subsequent cell death. Norgestrel also prevented light-induced photoreceptor morphological changes that were associated with ROS production, and that are characteristic of RP. Further investigation showed that norgestrel acts via post-translational modulation of the major antioxidant transcription factor Nrf2; bringing about its phosphorylation, subsequent nuclear translocation, and increased levels of its effector protein superoxide dismutase 2 (SOD2). In summary, these results demonstrate significant protection of photoreceptor cells from oxidative stress, and underscore the potential of norgestrel as a therapeutic option for RP.

A long-term energy efficiency prediction model for the Brazilian automotive industry

According to law number 12.715/2012, Brazilian government instituted guidelines for a program named Inovar-Auto. In this context, energy efficiency is a survival requirement for Brazilian automotive industry from September 2016. As proposed by law, energy efficiency is not going to be calculated by models only. It is going to be calculated by the whole universe of new vehicles registered. In this scenario, the composition of vehicles sold in market will be a key factor on profits of each automaker. Energy efficiency and its consequences should be taken into consideration in all of its aspects. In this scenario, emerges the following question: which is the efficiency curve of one automaker for long term, allowing them to adequate to rules, keep balancing on investment in technologies, increasing energy efficiency without affecting competitiveness of product lineup? Among several variables to be considered, one can highlight the analysis of manufacturing costs, customer value perception and market share, which characterizes this problem as a multi-criteria decision-making. To tackle the energy efficiency problem required by legislation, this paper proposes a framework of multi-criteria decision-making. The proposed framework combines Delphi group and Analytic Hierarchy Process to identify suitable alternatives for automakers to incorporate in main Brazilian vehicle segments. A forecast model based on artificial neural networks was used to estimate vehicle sales demand to validate expected results. This approach is demonstrated with a real case study using public vehicles sales data of Brazilian automakers and public energy efficiency data.

A MODEL FOR EVALUATING IMPACT OF BUSINESS PROCESS MANAGEMENT IN ORGANIZATIONAL PERFORMANCE

Business Process Management (BPM) is able to organize and frame a company focusing in the improvement or assurance of performance in order to gain competitive advantage. Although it is believed that BPM improves various aspects of organizational performance, there has been a lack of empirical evidence about this. The present study has the purpose to develop a model to show the impact of business process management in organizational performance. To accomplish that, the theoretical basis required to know the elements that configurate BPM and the measures that can evaluate the BPM success on organizational performance is built through a systematic literature review (SLR). Then, a research model is proposed according to SLR results. Empirical data will be collected from a survey of  larg and mid-sized industrial and service companies headquartered in Brazil. A quantitative analysis will be performed using structural equation modeling (SEM) to show if the direct effects among BPM and organizational performance can be considered statistically significant. At the end will discuss these results and their managerial and cientific implications.Keywords: Business process management (BPM). Organizational performance. Firm performance. Business models. Structural Equation Modeling. Systematic Literature Review.

Simulations of forest loss in North America, the Amazon, and combined using the Community Earth System Model

The netcdf files in this archive comprise climate model output from Community Earth System Model for experiments looking at forest loss over Western North America and the Amazon. For further description of the model and configuration for these experiments please see the accompanying manuscript: Synergistic ecoclimate teleconnections from forest loss in different regions structure global ecological responses Elizabeth S. Garcia, Abigail L. S. Swann, Juan C. Villegas, David D. Breshears, Darin J. Law, Scott R. Saleska, and Scott C. Stark published in PLOS ONE, 2016. Contact information in README.txt

Supporting data for Blossey et al (2016): CGILS Phase 2 LES intercomparison of response of subtropical marine low cloud regimes to CO2 quadrupling and a CMIP3-composite forcing change

This archive provides supporting data with forcings, data and plotting scripts for the paper P. N. Blossey, C. S. Bretherton, A. Cheng, S. Endo, T. Heus, A. Lock and J. J. van der Dussen, 2016. CGILS Phase 2 LES intercomparison of response of subtropical marine low cloud regimes to CO2 quadrupling and a CMIP3-composite forcing change. J. Adv. Model. Earth Syst., Under revision.

Flavour symmetries in a renormalizable SO(10) model

In the context of a renormalizable supersymmetric SO(10) Grand Unified Theory, we consider the fermion mass matrices generated by the Yukawa couplings to a 10 circle plus 120 circle plus (126) over bar representation of scalars. We perform a complete investigation of the possibilities of imposing flavour symmetries in this scenario; the purpose is to reduce the number of Yukawa coupling constants in order to identify potentially predictive models. We have found that there are only 14 inequivalent cases of Yukawa coupling matrices, out of which 13 cases are generated by 74 symmetries, with suitable n, and one case is generated by a Z(2) x Z(2) symmetry. A numerical analysis of the 14 cases reveals that only two of them-dubbed A and B in the present paper allow good fits to the experimentally known fermion masses and mixings. (C) 2016 The Authors. Published by Elsevier B.V.

The stochastic geometric machine model

This paper introduces the stochastic version of the Geometric Machine Model for the modelling of sequential, alternative, parallel (synchronous) and nondeterministic computations with stochastic numbers stored in a (possibly infinite) shared memory. The programming language L(D! 1), induced by the Coherence Space of Processes D! 1, can be applied to sequential and parallel products in order to provide recursive definitions for such processes, together with a domain-theoretic semantics of the Stochastic Arithmetic. We analyze both the spacial (ordinal) recursion, related to spacial modelling of the stochastic memory, and the temporal (structural) recursion, given by the inclusion relation modelling partial objects in the ordered structure of process construction.