Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role isto provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Perspectives for Forensic Intelligence in anti-doping: thinking outside the box

Today's approach to anti-doping is mostly centered on the judicial process, despite pursuing a further goal in the detection, reduction, solving and/or prevention of doping. Similarly to decision-making in the area of law enforcement feeding on Forensic Intelligence, anti-doping might significantly benefit from a more extensive gathering of knowledge. Forensic Intelligence might bring a broader logical dimension to the interpretation of data on doping activities for a more future-oriented and comprehensive approach instead of the traditional case-based and reactive process. Information coming from a variety of sources related to doping, whether directly or potentially, would feed an organized memory to provide real time intelligence on the size, seriousness and evolution of the phenomenon. Due to the complexity of doping, integrating analytical chemical results and longitudinal monitoring of biomarkers with physiological, epidemiological, sociological or circumstantial information might provide a logical framework enabling fit for purpose decision-making. Therefore, Anti-Doping Intelligence might prove efficient at providing a more proactive response to any potential or emerging doping phenomenon or to address existing problems with innovative actions or/and policies. This approach might prove useful to detect, neutralize, disrupt and/or prevent organized doping or the trafficking of doping agents, as well as helping to refine the targeting of athletes or teams. In addition, such an intelligence-led methodology would serve to address doping offenses in the absence of adverse analytical chemical evidence.

Compositional data analysis: where we are and where should we be heading?

We take stock of the present position of compositional data analysis, of what has beenachieved in the last 20 years, and then make suggestions as to what may be sensibleavenues of future research. We take an uncompromisingly applied mathematical view,that the challenge of solving practical problems should motivate our theoreticalresearch; and that any new theory should be thoroughly investigated to see if it mayprovide answers to previously abandoned practical considerations. Indeed a main themeof this lecture will be to demonstrate this applied mathematical approach by a number ofchallenging examples

On the use of QoS requirements as base of multicast charging

We propose a charging scheme for cost distribution along a multicast tree when cost is the responsibility of the receivers. This scheme focuses on QoS considerations and it does not depend on any specific type of service. The scheme has been designed to be used as a bridge between unicast and multicast services, solving the problem of charging multicast services by means of unicast charging and existing QoS routing mechanisms. We also include a numerical comparison and discussions of the case of non-numerical or relative QoS and on the application to some service examples in order to give a better understanding of the proposal

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches

The molecular signature of the stroma response in prostate cancer-induced osteoblastic bone metastasis highlights expansion of hematopoietic and prostate epithelial stem cell niches.

The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

Role of surgery in the management of brain arteriovenous malformations: prospective cohort study.

BACKGROUND AND PURPOSE: Management of brain arteriovenous malformation (bAVM) is controversial. We have analyzed the largest surgical bAVM cohort for outcome. METHODS: Both operated and nonoperated cases were included for analysis. A total of 779 patients with bAVMs were consecutively enrolled between 1989 and 2014. Initial management recommendations were recorded before commencement of treatment. Surgical outcome was prospectively recorded and outcomes assigned at the last follow-up visit using modified Rankin Scale. First, a sensitivity analyses was performed to select a subset of the entire cohort for which the results of surgery could be generalized. Second, from this subset, variables were analyzed for risk of deficit or near miss (intraoperative hemorrhage requiring blood transfusion of ≥2.5 L, hemorrhage in resection bed requiring reoperation, and hemorrhage associated with either digital subtraction angiography or embolization). RESULTS: A total of 7.7% of patients with Spetzler-Ponce classes A and B bAVM had an adverse outcome from surgery leading to a modified Rankin Scale >1. Sensitivity analyses that demonstrated outcome results were not subject to selection bias for Spetzler-Ponce classes A and B bAVMs. Risk factors for adverse outcomes from surgery for these bAVMs include size, presence of deep venous drainage, and eloquent location. Preoperative embolization did not affect the risk of perioperative hemorrhage. CONCLUSIONS: Most of the ruptured and unruptured low and middle-grade bAVMs (Spetzler-Ponce A and B) can be surgically treated with a low risk of permanent morbidity and a high likelihood of preventing future hemorrhage. Our results do not apply to Spetzler-Ponce C bAVMs.

Angiographic demonstration of neoangiogenesis after intra-arterial infusion of autologous bone marrow mononuclear cells in diabetic patients with critical limb ischemia.

Critical limb ischemia in diabetic patients is associated with high rates of morbidity and mortality. Suboptimal responses to the available medical and surgical treatments are common in these patients, who also demonstrate limited vascular homeostasis. Neovasculogenesis induced by stem cell therapy could be a useful approach for these patients. Neovasculogenesis and clinical improvement were compared at baseline and at 3 and 12 months after autologous bone marrow-derived mononuclear cell (BMMNC) transplantation in diabetic patients with peripheral artery disease. We conducted a prospective study to evaluate the safety and efficacy of intra-arterial administration of autologous BMMNCs (100-400 × 10(6) cells) in 20 diabetic patients with severe below-the-knee arterial ischemia. Although the time course of clinical effects differed among patients, after 12 months of follow-up all patients presented a notable improvement in the Rutherford-Becker classification, the University of Texas diabetic wound scales, and the Ankle-Brachial Index in the target limb. The clinical outcome was consistent with neovasculogenesis, which was assessed at 3 months by digital subtraction angiography and quantified by MetaMorph software. Unfortunately, local cell therapy in the target limb had no beneficial effect on the high mortality rate in these patients. In diabetic patients with critical limb ischemia, intra-arterial perfusion of BMMNCs is a safe procedure that generates a significant increase in the vascular network in ischemic areas and promotes remarkable clinical improvement.

A shared space. [Q]uality Plan of the Andalusian Public Health System 2010 - 2014

The Quality Plan aims to create an image of the health system as an intelligent system comprised of knowledge-generating organisations integrated into a much more comprehensive paradigm in line with knowledge societies; a health system which is part of an equally intelligent and innovative society that acknowledges the use of science and technology both as a source of welfare and as a means of solving many of its problems. The aim of this document is to collate the many activities which comprise three scenarios (citizens, professionals and shared space) and establish the roadmap for the quality policy strategies designed by the Ministry of Health of the Regional Government of Andalusia for the coming years and also to open the necessary channels of communication with society so that society itself, as well as being the beneficiary of the outcomes, also becomes the main protagonist.

Contribution to Asterisk Open Source Project

With this final master thesis we are going to contribute to the Asterisk open source project. Asterisk is an open source project that started with the main objective of develop an IP telephony platform, completely based on Software (so not hardware dependent) and under an open license like GPL. This project was started on 1999 by the software engineer Mark Spencer at Digium. The main motivation of that open source project was that the telecommunications sector is lack of open solutions, and most of the available solutions are based on proprietary standards, which are close and not compatible between them. Behind the Asterisk project there is a company, Digum, which is the project leading since the project was originated in its laboratories. This company has some of its employees fully dedicated to contribute to the Asterisk project, and also provide the whole infrastructure required by the open source project. But the business of Digium isn't based on licensing of products due to the open source nature of Asterisk, but it's based on offering services around Asteriskand designing and selling some hardware components to be used with Asterisk. The Asterisk project has grown up a lot since its birth, offering in its latest versions advanced functionalities for managing calls and compatibility with some hardware that previously was exclusive of proprietary solutions. Due to that, Asterisk is becoming a serious alternative to all these proprietaries solutions because it has reached a level of maturity that makes it very stable. In addition, as it is open source, it can be fully customized to a givenrequirement, which could be impossible with the proprietaries solutions. Due to the bigness that is reaching the project, every day there are more companies which develop value added software for telephony platforms, that are seriously evaluating the option of make their software fully compatible withAsterisk platforms. All these factors make Asterisk being a consolidated project but in constant evolution, trying to offer all those functionalities offered by proprietaries solutions. This final master thesis will be divided mainly in two blocks totally complementaries. In the first block we will analyze Asterisk as an open source project and Asterisk as a telephony platform (PBX). As a result of this analysis we will generate a document, written in English because it is Asterisk project's official language, which could be used by future contributors as an starting point on joining Asterisk. On the second block we will proceed with a development contribution to the Asterisk project. We will have several options in the form that we do the contribution, such as solving bugs, developing new functionalities or start an Asterisk satellite project. The type of contribution will depend on the needs of the project on that moment.

Mutigrid preconditioner for nonconforming discretization of elliptic problems with jump coefficients

In this paper, we present a multigrid preconditioner for solving the linear system arising from the piecewise linear nonconforming Crouzeix-Raviart discretization of second order elliptic problems with jump coe fficients. The preconditioner uses the standard conforming subspaces as coarse spaces. Numerical tests show both robustness with respect to the jump in the coe fficient and near-optimality with respect to the number of degrees of freedom.