Priors about observables in vector autoregressions

Standard practice in Bayesian VARs is to formulate priors on the autoregressive parameters, but economists and policy makers actually have priors about the behavior of observable variables. We show how this kind of prior can be used in a VAR under strict probability theory principles. We state the inverse problem to be solved and we propose a numerical algorithm that works well in practical situations with a very large number of parameters. We prove various convergence theorems for the algorithm. As an application, we first show that the results in Christiano et al. (1999) are very sensitive to the introduction of various priors that are widely used. These priors turn out to be associated with undesirable priors on observables. But an empirical prior on observables helps clarify the relevance of these estimates: we find much higher persistence of output responses to monetary policy shocks than the one reported in Christiano et al. (1999) and a significantly larger total effect.

CAV2 vector gene transfer into central nervious System

Estudi realitzat a partir d’una estada al Institut de Génétique Moléculaire de Montpellier, França, entre 2010 i 2012. En aquest projecte s’ha avaluat les avantatges dels vectors adenovirals canins tipus 2 (CAV2) com a vectors de transferència gènica al sistema nerviós central (SNC) en un model primat no-humà i en un model caní del síndrome de Sly (mucopolisacaridosis tipus 7, MPS VII), malaltia monogènica que cursa amb neurodegeneració. En una primera part del projecte s’ha avaluat la biodistribució, l’eficàcia i la durada de l’expressió del transgen en un model primat no humà, (Microcebus murinus). Com ha vector s’ha utilitzat un CAV2 de primera generació que expressa la proteïna verda fluorescent (CAVGFP). Els resultats aportats en aquesta memòria demostren que en primats no humans, com en d’altres espècies testades anteriorment per l’equip de l’EJ Kremer, la injecció intracerebral de CAV2 resulta en una extensa transducció del SNC, siguent les neurones i els precursors neuronals les cèl•lules preferencialment transduïdes. Els vectors canins, servint-se de vesícules intracel•lulars són transportats, majoritàriament, des de les sinapsis cap al soma neuronal, aquest transport intracel•lular permet una extensa transducció del SNC a partir d’una única injecció intracerebral dels vectors virals. En una segona part d’aquest projecte s’ha avaluat l’ús terapèutic dels CAV2. S’ha injectat un vector helper-dependent que expressa el gen la b-glucuronidasa i el gen de la proteïna verda fluorescent (HD-RIGIE), en el SNC del model caní del síndrome de Sly (MPS VII). La biodistribució i la eficàcia terapèutica han estat avaluades. Els nivells d’activitat enzimàtica en animals malalts injectats amb el vector terapèutic va arribar a valors similars als dels animals no afectes. A més a més s’ha observat una reducció en la quantitat dels GAGs acumulats en les cèl•lules dels animals malalts tractats amb el vector terapèutic, demostrant la potencialitat terapèutica dels CAV2 per a malalties que afecten al SNC. Els resultats aportats en aquest treball ens permeten dir que els CAV2 són unes bones eines terapèutiques per al tractament de malalties que afecten al SNC.

Generation of mouse-induced pluripotent stem cells by transient expression of a single nonviral polycistronic vector

Induced pluripotent stem (iPS) cells have generated keen interestdue to their potential use in regenerative medicine. They havebeen obtained from various cell types of both mice and humans byexogenous delivery of different combinations of Oct4, Sox2, Klf4,c-Myc, Nanog, and Lin28. The delivery of these transcription factorshas mostly entailed the use of integrating viral vectors (retrovirusesor lentiviruses), carrying the risk of both insertional mutagenesisand oncogenesis due to misexpression of these exogenousfactors. Therefore, obtaining iPS cells that do not carry integratedtransgene sequences is an important prerequisite for their eventualtherapeutic use. Here we report the generation of iPS cell linesfrom mouse embryonic fibroblasts with no evidence of integrationof the reprogramming vector in their genome, achieved by nucleofectionof a polycistronic construct coexpressing Oct4, Sox2, Klf4,and c-Myc

Dose optimization approach to fast X-ray microtomography of the lung alveoli.

A basic prerequisite for in vivo X-ray imaging of the lung is the exact determination of radiation dose. Achieving resolutions of the order of micrometres may become particularly challenging owing to increased dose, which in the worst case can be lethal for the imaged animal model. A framework for linking image quality to radiation dose in order to optimize experimental parameters with respect to dose reduction is presented. The approach may find application for current and future in vivo studies to facilitate proper experiment planning and radiation risk assessment on the one hand and exploit imaging capabilities on the other.

Dowel Bar Optimization: Phases I and II, October 2001

America’s roadways are in serious need of repair. According to the American Society of Civil Engineers (ASCE), one-third of the nation’s roads are in poor or mediocre condition. ASCE has estimated that under these circumstances American drivers will sacrifice $5.8 billion and as many as 13,800 fatalities a year from 1999 to 2001 ( 1). A large factor in the deterioration of these roads is a result of how well the steel reinforcement transfers loads across the concrete slabs. Fabricating this reinforcement using a shape conducive to transferring these loads will help to aid in minimizing roadway damage. Load transfer within a series of concrete slabs takes place across the joints. For a typical concrete paved road, these joints are approximately 1/8-inch gaps between two adjacent slabs. Dowel bars are located at these joints and used to transfer load from one slab to its adjacent slabs. As long as the dowel bar is completely surrounded by concrete no problems will occur. However, when the hole starts to oblong a void space is created and difficulties can arise. This void space is formed due to a stress concentration where the dowel contacts the concrete. Over time, the repeated process of traffic traveling over the joint crushes the concrete surrounding the dowel bar and causes a void in the concrete. This void inhibits the dowel’s ability to effectively transfer load across the joint. Furthermore, this void gives water and other particles a place to collect that will eventually corrode and potentially bind or lock the joint so that no thermal expansion is allowed. Once there is no longer load transferred across the joint, the load is transferred to the foundation and differential settlement of the adjacent slabs will occur.

Dowel Bar Optimization: Phases I and II, October 2001

America’s roadways are in serious need of repair. According to the American Society of Civil Engineers (ASCE), one-third of the nation’s roads are in poor or mediocre condition (1). ASCE has estimated that under these circumstances American drivers will sacrifice $5.8 billion and as many as 13,800 fatalities a year from 1999 to 2001 ( 1). A large factor in the deterioration of these roads is a result of how well the steel reinforcement transfers loads across the concrete slabs. Fabricating this reinforcement using a shape conducive to transferring these loads will help to aid in minimizing roadway damage. Load transfer within a series of concrete slabs takes place across the joints. For a typical concrete paved road, these joints are approximately 1/8-inch gaps between two adjacent slabs. Dowel bars are located at these joints and used to transfer load from one slab to its adjacent slabs. As long as the dowel bar is completely surrounded by concrete no problems will occur. However, when the hole starts to oblong a void space is created and difficulties can arise. This void space is formed due to a stress concentration where the dowel contacts the concrete. Over time, the repeated process of traffic traveling over the joint crushes the concrete surrounding the dowel bar and causes a void in the concrete. This void inhibits the dowel’s ability to effectively transfer load across the joint. Furthermore, this void gives water and other particles a place to collect that will eventually corrode and potentially bind or lock the joint so that no thermal expansion is allowed. Once there is no longer load transferred across the joint, the load is transferred to the foundation and differential settlement of the adjacent slabs will occur.

Material and Construction Optimization for Prevention of Premature Pavement Distress in PCC Pavements, September 2004

The chemistry of today’s concrete mixture designs is complicated by many variables, including multiple sources of aggregate and cements and a plethora of sometimes incompatible mineral and chemical admixtures. Concrete paving has undergone significant changes in recent years as new materials have been introduced into concrete mixtures. Supplementary cementitious materials such as fly ash and ground granulated blast furnace slag are now regularly used. In addition, many new admixtures that were not even available a few years ago now have widespread usage. Adding to the complexity are construction variables such as weather, mix delivery times, finishing practices, and pavement opening schedules. Mixture materials, mix design, and pavement construction are not isolated steps in the concrete paving process. Each affects and is affected by the other in ways that determine overall pavement quality and long-term performance. Equipment and procedures commonly used to test concrete materials and concrete pavements have not changed in decades, leaving serious gaps in our ability to understand and control the factors that determine concrete durability. The concrete paving community needs tests that will adequately characterize the materials, predict interactions, and monitor the properties of the concrete.

Personalized modeling for drug concentration prediction using Support Vector Machine

Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

A new hybrid summarizer based on vector Space model, statistical physics and linguistics

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.

Development, optimization, and validation of novel anti-TEM1/CD248 affinity agent for optical imaging in cancer.

Tumor Endothelial Marker-1 (TEM1/CD248) is a tumor vascular marker with high therapeutic and diagnostic potentials. Immuno-imaging with TEM1-specific antibodies can help to detect cancerous lesions, monitor tumor responses, and select patients that are most likely to benefit from TEM1-targeted therapies. In particular, near infrared(NIR) optical imaging with biomarker-specific antibodies can provide real-time, tomographic information without exposing the subjects to radioactivity. To maximize the theranostic potential of TEM1, we developed a panel of all human, multivalent Fc-fusion proteins based on a previously identified single chain antibody (scFv78) that recognizes both human and mouse TEM1. By characterizing avidity, stability, and pharmacokinectics, we identified one fusion protein, 78Fc, with desirable characteristics for immuno-imaging applications. The biodistribution of radiolabeled 78Fc showed that this antibody had minimal binding to normal organs, which have low expression of TEM1. Next, we developed a 78Fc-based tracer and tested its performance in different TEM1-expressing mouse models. The NIR imaging and tomography results suggest that the 78Fc-NIR tracer performs well in distinguishing mouse- or human-TEM1 expressing tumor grafts from normal organs and control grafts in vivo. From these results we conclude that further development and optimization of 78Fc as a TEM1-targeted imaging agent for use in clinical settings is warranted.

Optimisation des doses en tomographie computérisée pédiatrique [Patient dose optimization in pediatric computerized tomography]

The development of CT applications might become a public health problem if no effort is made on the justification and the optimisation of the examinations. This paper presents some hints to assure that the risk-benefit compromise remains in favour of the patient, especially when one deals with the examinations of young patients. In this context a particular attention has to be made on the justification of the examination. When performing the acquisition one needs to optimise the extension of the volume investigated together with the number of acquisition sequences used. Finally, the use of automatic exposure systems, now available on all the units, and the use of the Diagnostic Reference Levels (DRL) should allow help radiologists to control the exposure of their patients.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Materials and Mix Optimization Procedures for PCC Pavements, March 2006

Severe environmental conditions, coupled with the routine use of deicing chemicals and increasing traffic volume, tend to place extreme demands on portland cement concrete (PCC) pavements. In most instances, engineers have been able to specify and build PCC pavements that met these challenges. However, there have also been reports of premature deterioration that could not be specifically attributed to a single cause. Modern concrete mixtures have evolved to become very complex chemical systems. The complexity can be attributed to both the number of ingredients used in any given mixture and the various types and sources of the ingredients supplied to any given project. Local environmental conditions can also influence the outcome of paving projects. This research project investigated important variables that impact the homogeneity and rheology of concrete mixtures. The project consisted of a field study and a laboratory study. The field study collected information from six different projects in Iowa. The information that was collected during the field study documented cementitious material properties, plastic concrete properties, and hardened concrete properties. The laboratory study was used to develop baseline mixture variability information for the field study. It also investigated plastic concrete properties using various new devices to evaluate rheology and mixing efficiency. In addition, the lab study evaluated a strategy for the optimization of mortar and concrete mixtures containing supplementary cementitious materials. The results of the field studies indicated that the quality management concrete (QMC) mixtures being placed in the state generally exhibited good uniformity and good to excellent workability. Hardened concrete properties (compressive strength and hardened air content) were also satisfactory. The uniformity of the raw cementitious materials that were used on the projects could not be monitored as closely as was desired by the investigators; however, the information that was gathered indicated that the bulk chemical composition of most materials streams was reasonably uniform. Specific minerals phases in the cementitious materials were less uniform than the bulk chemical composition. The results of the laboratory study indicated that ternary mixtures show significant promise for improving the performance of concrete mixtures. The lab study also verified the results from prior projects that have indicated that bassanite is typically the major sulfate phase that is present in Iowa cements. This causes the cements to exhibit premature stiffening problems (false set) in laboratory testing. Fly ash helps to reduce the impact of premature stiffening because it behaves like a low-range water reducer in most instances. The premature stiffening problem can also be alleviated by increasing the water–cement ratio of the mixture and providing a remix cycle for the mixture.