Influence of Lean and Green on supply chain performance: an interpretive structural modelling model

This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

Macroeconomic shocks and the business cycle: evidence from a structural factor model

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and six. Focusing on the four-shock specification, we identify, using sign restrictions, two non-policy shocks, demand and supply, and two policy shocks, monetary and fiscal. We obtain the following results. (ii) Both supply and demand shocks are important sources of fluctuations; supply prevails for GDP, while demand prevails for employment and inflation. (ii) Policy matters, Both monetary and fiscal policy shocks have sizeable effects on output and prices, with little evidence of crowding out; both monetary and fiscal authorities implement important systematic countercyclical policies reacting to demand shocks. (iii) Negative demand shocks have a large long-run positive effect on productivity, consistently with the Schumpeterian "cleansing" view of recessions.

Structural Dynamics Model of a Cartesian Robot

Methods are developed for predicting vibration response characteristics of systems which change configuration during operation. A cartesian robot, an example of such a position-dependent system, served as a test case for these methods and was studied in detail. The chosen system model was formulated using the technique of Component Mode Synthesis (CMS). The model assumes that he system is slowly varying, and connects the carriages to each other and to the robot structure at the slowly varying connection points. The modal data required for each component is obtained experimentally in order to get a realistic model. The analysis results in prediction of vibrations that are produced by the inertia forces as well as gravity and friction forces which arise when the robot carriages move with some prescribed motion. Computer simulations and experimental determinations are conducted in order to calculate the vibrations at the robot end-effector. Comparisons are shown to validate the model in two ways: for fixed configuration the mode shapes and natural frequencies are examined, and then for changing configuration the residual vibration at the end of the mode is evaluated. A preliminary study was done on a geometrically nonlinear system which also has position-dependency. The system consisted of a flexible four-bar linkage with elastic input and output shafts. The behavior of the rocker-beam is analyzed for different boundary conditions to show how some limiting cases are obtained. A dimensional analysis leads to an evaluation of the consequences of dynamic similarity on the resulting vibration.

Psychosocial sources of stress and burnout in the consruction sector : a structural equation model. 'Fuentes psicosociales de estr??s y burnout en el sector de la construcci??n : un modelo de ecuaciones estructurales'

Resumen tomado de la publicaci??n. Resumen tambi??n en ingl??s

Hypotheses testing for structural calibration model

The main objective of this paper is to discuss maximum likelihood inference for the comparative structural calibration model (Barnett, in Biometrics 25:129-142, 1969), which is frequently used in the problem of assessing the relative calibrations and relative accuracies of a set of p instruments, each designed to measure the same characteristic on a common group of n experimental units. We consider asymptotic tests to answer the outlined questions. The methodology is applied to a real data set and a small simulation study is presented.

Constructing a Structural Macroeconomic Model Using Multiple Techniques

This project constructs a structural model of the United States Economy. This task is tackled in two separate ways: first econometric methods and then using a neural network, both with a structure that mimics the structure of the U.S. economy. The structural model tracks the performance of U.S. GDP rather well in a dynamic simulation, with an average error of just over 1 percent. The neural network performed well, but suffered from some theoretical, as well as some implementation issues.

A Robust Structural PGN Model for Control of Cell-Cycle Progression Stabilized by Negative Feedbacks

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.

Transcriptional activation by protein-induced DNA bending: evidence for a DNA structural transmission model.

Integration host factor (IHF) is a DNA-bending protein that binds to an upstream activating sequence (UAS1) and, on a negatively supercoiled DNA template, activates transcription from the ilvPG promoter of the ilvG-MEDA operon of Escherichia coli. The transcriptional initiation site of the ilvGMEDA operon is located 92 bp downstream of UAS1. Activation is still observed when the orientation of the upstream IHF binding site is reversed. This manipulation places the IHF binding site on the opposite face of the DNA helix, directs the IHF-induced DNA bend in the opposite direction, and presents the opposite face of the nonsymmetrical, heterodimeric, IHF molecule to the downstream RNA polymerase. Lymphoid enhancer-binding factor, LEF-1, is a DNA-bending, lymphoid-specific, mammalian transcription factor that shares no amino acid sequence similarity with IHF. When the IHF site in UAS1 is replaced with a LEF-1 site, LEF-1 activates transcription from the downstream ilvPG promoter in E. coli as well as it is activated by its natural activator, IHF. These results suggest that specific interactions between IHF and RNA polymerase are not required for activation. The results of DNA structural studies show that IHF forms a protein-DNA complex in the UAS1 region that, in the absence of RNA polymerase, alters the structure of the DNA helix in the -10 hexanucleotide region of the downstream ilvPG promoter. The results of in vitro abortive transcription assays show that IIIF also increases the apparent rate of RNA polymerase isomerization from a closed to an open complex. We suggest, therefore, that IHF activates transcription by forming a higher-order protein-DNA complex in the UAS1 region that structurally alters the DNA helix in a way that facilitates open complex formation at the downstream ilvPG promoter site.

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model

There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional-structural plant model (FSPM) was constructed, parameterized, and evaluated to analyse the effects of temperature on architectural traits, which strongly influence canopy light interception and shoot dry mass. The FSPM predicted the organ growth, organ size, and shoot dry mass over time with high accuracy (>85%). Analyses of this FSPM showed that, in comparison with the reference canopy, shoot dry mass may be affected by leaf angle by as much as 20%, leaf curvature by up to 7%, the leaf length: width ratio by up to 5%, internode length by up to 9%, and curvature ratios and leaf arrangement by up to 6%. Tomato canopies at low temperature had higher canopy density and were more clumped due to higher leaf area and shorter internodes. Interestingly, dry mass production and light interception of the clumped canopy were more sensitive to changes in architectural traits. The complex interactions between architectural traits, canopy light interception, dry mass production, and environmental conditions can be studied by the dynamic FSPM, which may serve as a tool for designing a canopy structure which is 'ideal' in a given environment.

Compósitos Portland-biopolímeros para cimentação de poços de petróleo

The oil production in mature areas can be improved by advanced recovery techniques. In special, steam injection reduces the viscosity of heavy oils, thus improving its flow to surrounding wells. On the other hand, the usually high temperatures and pressures involved in the process may lead to cement cracking, negatively affecting both the mechanical stability and zonal isolation provided by the cement sheath of the well. The addition of plastic materials to the cement is an alternative to prevent this scenario. Composite slurries consisting of Portland cement and a natural biopolymer were studied. Samples containing different contents of biopolymer dispersed in a Portland cement matrix were prepared and evaluated by mechanical and rheological tests in order to assess their behavior according to API (American Petroleum Institute) guidelines. FEM was also applied to map the stress distribution encountered by the cement at bottom bole. The slurries were prepared according to a factorial experiment plan by varying three parameters, i.e., cement age, contents of biopolymer and water-to-cement ratio. The results revealed that the addition of the biopolymer reduced the volume of free water and the setting time of the slurry. In addition, tensile strength, compressive strength and toughness improved by 30% comparing hardened composites to plain Portland slurries. FEM results suggested that the stresses developed at bottomhole may be 10 to 100 times higher than the strength of the cement as evaluated in the lab by unconfined mechanical testing. An alternative approach is proposed to adapt the testing methodology used to evaluate the mechanical behavior of oilwell cement slurries by simulating the confined conditions encountered at bottornhole

Compósitos Portland-biopolímeros para cimentação de poços de petróleo

The oil production in mature areas can be improved by advanced recovery techniques. In special, steam injection reduces the viscosity of heavy oils, thus improving its flow to surrounding wells. On the other hand, the usually high temperatures and pressures involved in the process may lead to cement cracking, negatively affecting both the mechanical stability and zonal isolation provided by the cement sheath of the well. The addition of plastic materials to the cement is an alternative to prevent this scenario. Composite slurries consisting of Portland cement and a natural biopolymer were studied. Samples containing different contents of biopolymer dispersed in a Portland cement matrix were prepared and evaluated by mechanical and rheological tests in order to assess their behavior according to API (American Petroleum Institute) guidelines. FEM was also applied to map the stress distribution encountered by the cement at bottom bole. The slurries were prepared according to a factorial experiment plan by varying three parameters, i.e., cement age, contents of biopolymer and water-to-cement ratio. The results revealed that the addition of the biopolymer reduced the volume of free water and the setting time of the slurry. In addition, tensile strength, compressive strength and toughness improved by 30% comparing hardened composites to plain Portland slurries. FEM results suggested that the stresses developed at bottomhole may be 10 to 100 times higher than the strength of the cement as evaluated in the lab by unconfined mechanical testing. An alternative approach is proposed to adapt the testing methodology used to evaluate the mechanical behavior of oilwell cement slurries by simulating the confined conditions encountered at bottornhole

Bayesian model selection of structural explanatory models: Application to road accident data

Using the Bayesian approach as the model selection criteria, the main purpose in this study is to establish a practical road accident model that can provide a better interpretation and prediction performance. For this purpose we are using a structural explanatory model with autoregressive error term. The model estimation is carried out through Bayesian inference and the best model is selected based on the goodness of fit measures. To cross validate the model estimation further prediction analysis were done. As the road safety measures the number of fatal accidents in Spain, during 2000-2011 were employed. The results of the variable selection process show that the factors explaining fatal road accidents are mainly exposure, economic factors, and surveillance and legislative measures. The model selection shows that the impact of economic factors on fatal accidents during the period under study has been higher compared to surveillance and legislative measures.