Dynamic optimal law enforcement with learning

We incorporate the process of enforcement learning by assuming that the agency's current marginal cost is a decreasing function of its past experience of detecting and convicting. The agency accumulates data and information (on criminals, on opportunities of crime) enhancing the ability to apprehend in the future at a lower marginal cost.We focus on the impact of enforcement learning on optimal stationary compliance rules. In particular, we show that the optimal stationary fine could be less-than-maximal and the optimal stationary probability of detection could be higher-than-otherwise.

Optimal law enforcement under asymmetric information

In this paper, we focus on the problem created by asymmetric informationabout the enforcer's (agent's) costs associated to enforcement expenditure. This adverse selection problem affects optimal law enforcement because a low cost enforcer may conceal its information by imitating a high cost enforcer, and must then be given a compensation to be induced to reveal its true costs. The government faces a trade-off between minimizing the enforcer's compensation and maximizing the net surplus of harmful acts. As a consequence, the probability of apprehension and punishment is usually reduced leading to more offenses being committed. We show that asymmetry of information does not affect law enforcement as long as raising public funds is costless. The consideration of costly raising of public funds permits to establish the positive correlation between asymmetry of information between government and enforcers andthe crime rate.

The geophysical electromagnetic prospecting in the spatial location of the travertine deposits of the Banyoles Depression (Girona)

The results of the application of the geophysical electromagnetic prospection methods in the resolution of the problems of the spatial location of the travertine quaternary formations of the Banyoles depression are presented

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Sustainability of the Peruvian anchoveta supply chains from sea to shelf: towards a new strategy for optimal use of resources

The research performed a sustainability assessment of supply chains of the anchoveta (Engraulis ringens) in Peru. The corresponding fisheries lands 6.5 million t per year, of which <2% is rendered into products for direct human consumption (DHC) and 98% reduced into feed ingredients (fishmeal and fish oil, FMFO), for export. Several industries compete for the anchoveta resources, generating local and global impacts. The need for understanding these dynamics, towards sustainability-improving management and policy recommendations, determined the development of a sustainability assessment framework: 1) characterisation and modelling of the systems under study (with Life Cycle Assessment and other tools) including local aquaculture, 2) calculation of sustainability indicators (i.e. energy efficiency, nutritional value, socio-economic performances), and 3) sustainability comparison of supply chains; definition and comparison of alternative exploitation scenarios. Future exploitation scenarios were defined by combining an ecosystem and a material flow models: continuation of the status quo (Scenario 1), shift towards increased proportion of DHC production (Scenario 2), and radical reduction of the anchoveta harvest in order for other fish stocks to recover and be exploited for DHC (Scenario 3). Scenario 2 was identified as the most sustainable. Management and policy recommendations include improving of: controls for compliance with management measures, sanitary conditions for DHC, landing infrastructure for small- and medium-scale (SMS) fisheries; the development of a national refrigerated distribution chain; and the assignation of flexible tolerances for discards from different DHC processes.

Do Agglomeration Economies Reduce the Sensitivity of Firm Location to Tax Differentials?

Recent theoretical work in economic geography has shown that agglomeration forces can mitigate 'race-to-the-bottom' tax competition, by partly or fully offsetting firms' sensitivity to tax differentials. We test this proposition using data on firm births across Swiss municipalities. We find that corporate taxes deter firm births less in more spatially concentrated sectors. Firms in sectors with an agglomeration intensity in the top quintile are less than half as responsive to differences in corporate tax burdens as firms in sectors with an agglomeration intensity in the bottom quintile. Hence, agglomeration economies do appear to attenuate the impact of tax differentials on firms' location choices.

Optimal public rationing and price response.

We study optimal public health care rationing and private sector price responses. Consumers differ in their wealth and illness severity (defined as treatment cost). Due to a limited budget, some consumers must be rationed. Rationed consumers may purchase from a monopolistic private market. We consider two information regimes. In the first, the public supplier rations consumers according to their wealth information (means testing). In equilibrium, the public supplier must ration both rich and poor consumers. Rationing some poor consumers implements price reduction in the private market. In the second information regime, the public supplier rations consumers according to consumers' wealth and cost information. In equilibrium, consumers are allocated the good if and only if their costs are below a threshold (cost effectiveness). Rationing based on cost results in higher equilibrium consumer surplus than rationing based on wealth.

Short-term moderate hypocapnia augments detection of optimal cerebral perfusion pressure.

An autoregulation-oriented strategy has been proposed to guide neurocritical therapy toward the optimal cerebral perfusion pressure (CPPOPT). The influence of ventilation changes is, however, unclear. We sought to find out whether short-term moderate hypocapnia (HC) shifts the CPPOPT or affects its detection. Thirty patients with traumatic brain injury (TBI), who required sedation and mechanical ventilation, were studied during 20 min of normocapnia (5.1±0.4 kPa) and 30 min of moderate HC (4.4±3.0 kPa). Monitoring included bilateral transcranial Doppler of the middle cerebral arteries (MCA), invasive arterial blood pressure (ABP), and intracranial pressure (ICP). Mx -autoregulatory index provided a measure for the CPP responsiveness of MCA flow velocity. CPPOPT was assessed as the CPP at which autoregulation (Mx) was working with the maximal efficiency. During normocapnia, CPPOPT (left: 80.65±6.18; right: 79.11±5.84 mm Hg) was detectable in 12 of 30 patients. Moderate HC did not shift this CPPOPT but enabled its detection in another 17 patients (CPPOPT left: 83.94±14.82; right: 85.28±14.73 mm Hg). The detection of CPPOPT was achieved via significantly improved Mx-autoregulatory index and an increase of CPP mean. It appeared that short-term moderate HC augmented the detection of an optimum CPP, and may therefore usefully support CPP-guided therapy in patients with TBI.

Efficient T cell activation requires an optimal dwell-time of interaction between the TCR and the pMHC complex.

Cytotoxic T cell (CTL) activation by antigen requires the specific detection of peptide-major histocompatibility class I (pMHC) molecules on the target-cell surface by the T cell receptor (TCR). We examined the effect of mutations in the antigen-binding site of a Kb-restricted TCR on T cell activation, antigen binding and dissociation from antigen.These parameters were also examined for variants derived from a Kd-restricted peptide that was recognized by a CTL clone. Using these two independent systems, we show that T cell activation can be impaired by mutations that either decrease or increase the binding half-life of the TCR-pMHC interaction. Our data indicate that efficient T cell activation occurs within an optimal dwell-time range of TCR-pMHC interaction. This restricted dwell-time range is consistent with the exclusion of either extremely low or high affinity T cells from the expanded population during immune responses.

Optimal management of microgrids

Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.. Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.

The optimal dividend barrier in the Gamma-Omega model

In the traditional actuarial risk model, if the surplus is negative, the company is ruined and has to go out of business. In this paper we distinguish between ruin (negative surplus) and bankruptcy (going out of business), where the probability of bankruptcy is a function of the level of negative surplus. The idea for this notion of bankruptcy comes from the observation that in some industries, companies can continue doing business even though they are technically ruined. Assuming that dividends can only be paid with a certain probability at each point of time, we derive closed-form formulas for the expected discounted dividends until bankruptcy under a barrier strategy. Subsequently, the optimal barrier is determined, and several explicit identities for the optimal value are found. The surplus process of the company is modeled by a Wiener process (Brownian motion).

Office of Location and Environment Manual, August 2009

This manual captures the experience of practitioners in the Iowa Department of Transportation’s (Iowa DOT’s) Office of Location and Environment (OLE). It also documents the need for coordinated project development efforts during the highway project planning, or location study phase and engineering design. The location study phase establishes: * The definition of, and need for, the highway improvement project * The range of alternatives and many key attributes of the project’s design * The recommended alternative, its impacts, and the agreed-to conditions for project approval The location study process involves developing engineering alternatives, collecting engineering and environmental data, and completing design refinements to accomplish functional designs. The items above also embody the basic content required for projects compliant with the National Environmental Policy Act (NEPA) of 19691, which directs federal agencies to use a systematic, interdisciplinary approach during the planning process whenever proposed actions (or “projects”) have the potential for environmental impacts. In doing so, NEPA requires coordination with stakeholders, review, comment, and public disclosure. Are location studies and environmental studies more about the process or the documents? If properly conducted, they concern both—unbiased and reasonable processes with quality and timely documents. In essence, every project is a story that needs to be told. Engineering and environmental regulations and guidance, as documented in this manual, will help project staff and managers become better storytellers.

When "enough" is not enough: new perspectives on optimal methadone maintenance dose.

Some methadone maintenance treatment (MMT) programs prescribe inadequate daily methadone doses. Patients complain of withdrawal symptoms and continue illicit opioid use, yet practitioners are reluctant to increase doses above certain arbitrary thresholds. Serum methadone levels (SMLs) may guide practitioners dosing decisions, especially for those patients who have low SMLs despite higher methadone doses. Such variation is due in part to the complexities of methadone metabolism. The medication itself is a racemic (50:50) mixture of 2 enantiomers: an active "R" form and an essentially inactive "S" form. Methadone is metabolized primarily in the liver, by up to five cytochrome P450 isoforms, and individual differences in enzyme activity help explain wide ranges of active R-enantiomer concentrations in patients given identical doses of racemic methadone. Most clinical research studies have used methadone doses of less than 100 mg/day [d] and have not reported corresponding SMLs. New research suggests that doses ranging from 120 mg/d to more than 700 mg/d, with correspondingly higher SMLs, may be optimal for many patients. Each patient presents a unique clinical challenge, and there is no way of prescribing a single best methadone dose to achieve a specific blood level as a "gold standard" for all patients. Clinical signs and patient-reported symptoms of abstinence syndrome, and continuing illicit opioid use, are effective indicators of dose inadequacy. There does not appear to be a maximum daily dose limit when determining what is adequately "enough" methadone in MMT.