Location of hubs in a competitive environment

We offer a formulation that locates hubs on a network in a competitiveenvironment; that is, customer capture is sought, which happenswhenever the location of a new hub results in a reduction of thecurrent cost (time, distance) needed by the traffic that goes from thespecified origin to the specified destination.The formulation presented here reduces the number of variables andconstraints as compared to existing covering models. This model issuited for both air passenger and cargo transportation.In this model, each origin-destination flow can go through either oneor two hubs, and each demand point can be assigned to more than a hub,depending on the different destinations of its traffic. Links(``spokes'' have no capacity limit. Computational experience is provided.

Business cycles, unemployment insurance and the calibration of matching models

This paper theoretically and empirically documents a puzzle that arises when an RBC economy with a job matching function is used to model unemployment. The standard model can generate sufficiently large cyclical fluctuations in unemployment, or a sufficiently small response of unemployment to labor market policies, but it cannot do both. Variable search and separation, finite UI benefit duration, efficiency wages, and capital all fail to resolve this puzzle. However, either sticky wages or match-specific productivity shocks can improve the model's performance by making the firm's flow of surplus more procyclical, which makes hiring more procyclical too.

Entropy Production In Thermodynamic Climate Models

We present a non-equilibrium theory in a system with heat and radiative fluxes. The obtained expression for the entropy production is applied to a simple one-dimensional climate model based on the first law of thermodynamics. In the model, the dissipative fluxes are assumed to be independent variables, following the criteria of the Extended Irreversible Thermodynamics (BIT) that enlarges, in reference to the classical expression, the applicability of a macroscopic thermodynamic theory for systems far from equilibrium. We analyze the second differential of the classical and the generalized entropy as a criteria of stability of the steady states. Finally, the extreme state is obtained using variational techniques and observing that the system is close to the maximum dissipation rate

Effect of expiratory flow limitation on respiratory mechanical impedance: a model study

Large phasic variations of respiratory mechanical impedance (Zrs) have been observed during induced expiratory flow limitation (EFL) (M. Vassiliou, R. Peslin, C. Saunier, and C. Duvivier. Eur. Respir. J. 9: 779-786, 1996). To clarify the meaning of Zrs during EFL, we have measured from 5 to 30 Hz the input impedance (Zin) of mechanical analogues of the respiratory system, including flow-limiting elements (FLE) made of easily collapsible rubber tubing. The pressures upstream (Pus) and downstream (Pds) from the FLE were controlled and systematically varied. Maximal flow (Vmax) increased linearly with Pus, was close to the value predicted from wave-speed theory, and was obtained for Pus-Pds of 4-6 hPa. The real part of Zin started increasing abruptly with flow (V) >85%Vmax and either further increased or suddenly decreased in the vicinity of V¿max. The imaginary part of Zin decreased markedly and suddenly above 95%Vmax. Similar variations of Zin during EFL were seen with an analogue that mimicked the changes of airway transmural pressure during breathing. After pressure andV measurements upstream and downstream from the FLE were combined, the latter was analyzed in terms of a serial (Zs) and a shunt (Zp) compartment. Zs was consistent with a large resistance and inertance, and Zp with a mainly elastic element having an elastance close to that of the tube walls. We conclude that Zrs data during EFL mainly reflect the properties of the FLE.

GIS-based debris flow source and runout susceptibility assessment from DEM data - a case study in NW Nicaragua

In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.

"Suddenly I get into the zone": Examining discontinuities and nonlinear changes in flow experiences at work

Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees" perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest and absorption were measured using the experience sampling method, yielding a total of 6981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R2, AICc and BIC indexes, the nonlinear dynamical systems model (i.e. cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modelling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

Spreading due to heterogeneity in two-phase flow

Postprint (published version)

Flow resistance equations for mountain rivers

Three models of flow resistance (a Keulegan-type logarithmic law and two models developed for large-scale roughness conditions: the full logarithmic law and a model based on an inflectional velocity profile) were calibrated, validated and compared using an extensive database (N = 1,533) from rivers and flumes, representative of a wide hydraulic and geomorphologic range in the field of gravel-bed and mountain channels. It is preferable to apply the model based on an inflectional velocity profile in the relative submergence (y/d90) interval between 0.5 and 15, while the full logarithmic law is preferable for values below 0.5. For high relative submergence, above 15, either the logarithmic law or the full logarithmic law can be applied. The models fitted to the coarser percentiles are preferable to those fitted to the median diameter, owing to the higher explanatory power achieved by setting a model, the smaller difference in the goodness-of-fit between the different models and the lower influence of the origin of the data (river or flume).

Fluid flow processes at basin scale

S u b s u r face fluid flow plays a significant role in many geologic processes and is increasingly being studied in the scale of sedimentary basins and geologic time perspective. Many economic resources such as petroleum and mineral deposits are products of basin scale fluid flow operating over large periods of time. Such ancient flow systems can be studied through analysis of diagenetic alterations and fluid inclusions to constrain physical and chemical conditions of fluids and rocks during their paleohy d r og e o l ogic evolution. Basin simulation models are useful to complement the paleohy d r og e o l ogic record preserved in the rocks and to derive conceptual models on hydraulic basin evolution and generation of economic resources. Different types of fluid flow regimes may evo l ve during basin evolution. The most important with respect to flow rates and capacity for transport of solutes and thermal energy is gr avitational fluid flow driven by the topographic configuration of a basin. Such flow systems require the basin to be elevated above sea level. Consolidational fluid flow is the principal fluid migration process in basins below sea level, caused by loading of compressible rocks. Flow rates of such systems are several orders of magnitude below topogr a p hy driven flow. Howeve r, consolidation may create significant fluid ove rpressure. Episodic dewatering of ove rpressured compart m e n t s m ay cause sudden fluid release with elevated flow velocities and may cause a transient local thermal and chemical disequilibrium betwe e n fluid and rock. This paper gives an ove rv i ew on subsurface fluid flow processes at basin scale and presents examples related to the Pe n e d è s basin in the central Catalan continental margin including the offshore Barcelona half-graben and the compressive South-Pyrenean basin.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.