Agglomeration and labour productivity in Spanish industry: a long-term analysis

This paper analyzes the relationship between spatial density of economic activity and interregional differences in the productivity of industrial labour in Spain during the period 1860-1999. In the spirit of Ciccone and Hall (1996) and Ciccone (2002), we analyze the evolution of this relationship over the long term in Spain. Using data on the period 1860-1999 we show the existence of an agglomeration effect linking the density of economic activity with labour productivity in the industry. This effect was present since the beginning of the industrialization process in the middle of the 19th century but has been decreasing over time. The estimated elasticity of labour productivity with respect to employment density was close to 8% in the subperiod 1860-1900, reduces to a value of around 7% in the subperiod 1914-1930, to 4% in the subperiod 1965-1979 and becomes insignificant in the final subperiod 1985-1999. At the end of the period analyzed there is no evidence of the existence of net agglomeration effects in the industry. This result could be explained by an important increase in the congestion effects in large industrial metropolitan areas that would have compensated the centripetal or agglomeration forces at work. Furthermore, this result is also consistent with the evidence of a dispersion of industrial activity in Spain during the last decades.

Analysis of linear networks with inconsistent initial conditions

This paper presents a new method to analyze timeinvariant linear networks allowing the existence of inconsistent initial conditions. This method is based on the use of distributions and state equations. Any time-invariant linear network can be analyzed. The network can involve any kind of pure or controlled sources. Also, the transferences of energy that occur at t=O are determined, and the concept of connection energy is introduced. The algorithms are easily implemented in a computer program.

Discrete analysis of dividend payments in a non-life insurance portfolio

The process of free reserves in a non-life insurance portfolio as defined in the classical model of risk theory is modified by the introduction of dividend policies that set maximum levels for the accumulation of reserves. The first part of the work formulates the quantification of the dividend payments via the expectation of their current value under diferent hypotheses. The second part presents a solution based on a system of linear equations for discrete dividend payments in the case of a constant dividend barrier, illustrated by solving a specific case.

Price transmission and market power analysis in the Spanish seafood market chain

[cat] Espanya és un dels principals mercats de productes pesquers d’Europa i del món. El consum de productes pesquers ha estat tradicionalment molt important a Espanya, el 2005 es varen consumir 36,7 kg per persona (MAPA, diversos anys). Malgrat això, el mercat i cóm interactuen els diversos nivells de la cadena de comercialització han gaudit de poca atenció. En aquest estudi, utilitzant dades setmanals, s’analitza per als dotze principals productes pesquers, l’elasticitat en la transmissió de preus al llarg de la cadena de comercialització a Espanya (llotja, mercat central i detallista). Finalment s’investiga la presència d’assimetria en la transmissió de preus entre aquests nivells de mercat. Els resultats obtinguts tenen importants implicacions a l’hora d’analitzar la demanda, poder de mercat i marges al llarg del mercat per als productes pesquers.

Agglomeration and labour productivity in Spanish industry: a long-term analysis

This paper analyzes the relationship between spatial density of economic activity and interregional differences in the productivity of industrial labour in Spain during the period 1860-1999. In the spirit of Ciccone and Hall (1996) and Ciccone (2002), we analyze the evolution of this relationship over the long term in Spain. Using data on the period 1860-1999 we show the existence of an agglomeration effect linking the density of economic activity with labour productivity in the industry. This effect was present since the beginning of the industrialization process in the middle of the 19th century but has been decreasing over time. The estimated elasticity of labour productivity with respect to employment density was close to 8% in the subperiod 1860-1900, reduces to a value of around 7% in the subperiod 1914-1930, to 4% in the subperiod 1965-1979 and becomes insignificant in the final subperiod 1985-1999. At the end of the period analyzed there is no evidence of the existence of net agglomeration effects in the industry. This result could be explained by an important increase in the congestion effects in large industrial metropolitan areas that would have compensated the centripetal or agglomeration forces at work. Furthermore, this result is also consistent with the evidence of a dispersion of industrial activity in Spain during the last decades.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Production Flow Analysis - cases from manufacturing and service industry

Production flow analysis (PFA) is a well-established methodology used for transforming traditional functional layout into product-oriented layout. The method uses part routings to find natural clusters of workstations forming production cells able to complete parts and components swiftly with simplified material flow. Once implemented, the scheduling system is based on period batch control aiming to establish fixed planning, production and delivery cycles for the whole production unit. PFA is traditionally applied to job-shops with functional layouts, and after reorganization within groups lead times reduce, quality improves and motivation among personnel improves. Several papers have documented this, yet no research has studied its application to service operations management. This paper aims to show that PFA can well be applied not only to job-shop and assembly operations, but also to back-office and service processes with real cases. The cases clearly show that PFA reduces non-value adding operations, introduces flow by evening out bottlenecks and diminishes process variability, all of which contribute to efficient operations management.

A contribution to the study of post-depositional alterations of pottery using TL dating analysis

In luminescence dating, the potassium concentration significantly contributes to the dose rate value in the age estimation. Within this study, fine-grain thermoluminescence dating has been applied on sherds of calcareous pottery of known age, excavated at a Roman site in Mallorca, Spain. For those of the samples that showed signs of severe potassium leaching, according to chemical and mineralogical examination, the thermoluminescence analysis provided overestimated dates. By using the known archaeological age of the samples, a corrected dose rate value can be estimated which provides the potassium concentration averaged for the burial period. Finally, a step-like model can then be used to estimate the fraction of the burial period after which most of the alteration effects took place.

Brain Connectivity Analysis in Children. Effects of Prematurity. and Prenatal Growth Restriction

Introduction: Survival of children born prematurely or with very low birth weight has increased dramatically, but the long term developmental outcome remains unknown. Many children have deficits in cognitive capacities, in particular involving executive domains and those disabilities are likely to involve a central nervous system deficit. To understand their neurostructural origin, we use DTI. Structurally segregated and functionally regions of the cerebral cortex are interconnected by a dense network of axonal pathways. We noninvasively map these pathways across cortical hemispheres and construct normalized structural connection matrices derived from DTI MR tractography. Group comparisons of brain connectivity reveal significant changes in fiber density in case of children with poor intrauterine grown and extremely premature children (gestational age<28 weeks at birth) compared to control subjects. This changes suggest a link between cortico-axonal pathways and the central nervous system deficit. Methods: Sixty premature born infants (5-6 years old) were scanned on clinical 3T scanner (Magnetom Trio, Siemens Medical Solutions, Erlangen, Germany) at two hospitals (HUG, Geneva and CHUV, Lausanne). For each subject, T1-weighted MPRAGE images (TR/TE=2500/2.91,TI=1100, resolution=1x1x1mm, matrix=256x154) and DTI images (30 directions, TR/TE=10200/107, in-plane resolution=1.8x1.8x2mm, 64 axial, matrix=112x112) were acquired. Parent(s) provided written consent on prior ethical board approval. The extraction of the Whole Brain Structural Connectivity Matrix was performed following (Cammoun, 2009 and Hagmann, 2008). The MPARGE images were registered using an affine registration to the non-weighted-DTI and WM-GM segmentation performed on it. In order to have equal anatomical localization among subjects, 66 cortical regions with anatomical landmarks were created using the curvature information, i.e. sulcus and gyrus (Cammoun et al, 2007; Fischl et al, 2004; Desikan et al, 2006) with freesurfer software (http://surfer.nmr.mgh.harvard.edu/). Tractography was performed in WM using an algorithm especially designed for DTI/DSI data (Hagmann et al., 2007) and both information were then combined in a matrix. Each row and column of the matrix corresponds to a particular ROI. Each cell of index (i,j) represents the fiber density of the bundle connecting the ROIs i and j. Subdividing each cortical region, we obtained 4 Connectivity Matrices of different resolution (33, 66, 125 and 250 ROI/hemisphere) for each subject . Subjects were sorted in 3 different groups, namely (1) control, (2) Intrauterine Growth Restriction (IUGR), (3) Extreme Prematurity (EP), depending on their gestational age, weight and percentile-weight score at birth. Group-to-group comparisons were performed between groups (1)-(2) and (1)-(3). The mean age at examination of the three groups were similar. Results: Quantitative analysis were performed between groups to determine fibers density differences. For each group, a mean connectivity matrix with 33ROI/hemisphere resolution was computed. On the other hand, for all matrix resolutions (33,66,125,250 ROI/hemisphere), the number of bundles were computed and averaged. As seen in figure 1, EP and IUGR subjects present an overall reduction of fibers density in both interhemispherical and intrahemispherical connections. This is given quantitatively in table 1. IUGR subjects presents a higher percentage of missing fiber bundles than EP when compared to control subjects (~16% against 11%). When comparing both groups to control subjects, for the EP subjects, the occipito-parietal regions seem less interhemispherically connected whilst the intrahemispherical networks present lack of fiber density in the lymbic system. Children born with IUGR, have similar reductions in interhemispherical connections than the EP. However, the cuneus and precuneus connections with the precentral and paracentral lobe are even lower than in the case of the EP. For the intrahemispherical connections the IUGR group preset a loss of fiber density between the deep gray matter structures (striatum) and the frontal and middlefrontal poles, connections typically involved in the control of executive functions. For the qualitative analysis, a t-test comparing number of bundles (p-value<0.05) gave some preliminary significant results (figure 2). Again, even if both IUGR and EP appear to have significantly less connections comparing to the control subjects, the IUGR cohort seems to present a higher lack of fiber density specially relying the cuneus, precuneus and parietal areas. In terms of fiber density, preliminary Wilcoxon tests seem to validate the hypothesis set by the previous analysis. Conclusions: The goal of this study was to determine the effect of extreme prematurity and poor intrauterine growth on neurostructural development at the age of 6 years-old. This data indicates that differences in connectivity may well be the basis for the neurostructural and neuropsychological deficit described in these populations in the absence of overt brain lesions (Inder TE, 2005; Borradori-Tolsa, 2004; Dubois, 2008). Indeed, we suggest that IUGR and prematurity leads to alteration of connectivity between brain structures, especially in occipito-parietal and frontal lobes for EP and frontal and middletemporal poles for IUGR. Overall, IUGR children have a higher loss of connectivity in the overall connectivity matrix than EP children. In both cases, the localized alteration of connectivity suggests a direct link between cortico-axonal pathways and the central nervous system deficit. Our next step is to link these connectivity alterations to the performance in executive function tests.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Evaluation of Carbonate Aggregate Using X-Ray Analysis, HR-266, 1989

Iowa has more than 13,000 miles of portland cement concrete (PCC) pavement. Some pavements have performed well for over 50 years, while others have been removed or overlaid due to the premature deterioration of joints and cracks. Some of the premature deterioration is classical D-cracking, which is attributed to a critically saturated aggregate pore system (freeze-thaw damage). However, some of the premature deterioration is related to adverse chemical reactivity involving carbonate coarse aggregate. The objective of this paper is to demonstrate the value of a chemical analysis of carbonate aggregate using X-ray equipment to identify good or poor quality. At least 1.5% dolomite is necessary in a carbonate aggregate to produce a discernible dolomite peak. The shift of the maximum-intensity X-ray diffraction dolomite d-spacing can be used to predict poor performance of a carbonate aggregate in PCC. A limestone aggregate with a low percentage of strontium (less than 0.013) and phosphorus (less than 0.010) would be expected to give good performance in PCC pavement. Poor performance in PCC pavement is expected from limestone aggregates with higher percentages (above 0.05) of strontium.

Genetic polymorphisms of the main transcription factors for adiponectin gene promoter in regulation of adiponectin levels: association analysis in three European cohorts.

Adiponectin serum concentrations are an important biomarker in cardiovascular epidemiology with heritability etimates of 30-70%. However, known genetic variants in the adiponectin gene locus (ADIPOQ) account for only 2%-8% of its variance. As transcription factors are thought to play an under-acknowledged role in carrying functional variants, we hypothesized that genetic polymorphisms in genes coding for the main transcription factors for the ADIPOQ promoter influence adiponectin levels. Single nucleotide polymorphisms (SNPs) at these genes were selected based on the haplotype block structure and previously published evidence to be associated with adiponectin levels. We performed association analyses of the 24 selected SNPs at forkhead box O1 (FOXO1), sterol-regulatory-element-binding transcription factor 1 (SREBF1), sirtuin 1 (SIRT1), peroxisome-proliferator-activated receptor gamma (PPARG) and transcription factor activating enhancer binding protein 2 beta (TFAP2B) gene loci with adiponectin levels in three different European cohorts: SAPHIR (n = 1742), KORA F3 (n = 1636) and CoLaus (n = 5355). In each study population, the association of SNPs with adiponectin levels on log-scale was tested using linear regression adjusted for age, sex and body mass index, applying both an additive and a recessive genetic model. A pooled effect size was obtained by meta-analysis assuming a fixed effects model. We applied a significance threshold of 0.0033 accounting for the multiple testing situation. A significant association was only found for variants within SREBF1 applying an additive genetic model (smallest p-value for rs1889018 on log(adiponectin) = 0.002, β on original scale = -0.217 µg/ml), explaining ∼0.4% of variation of adiponectin levels. Recessive genetic models or haplotype analyses of the FOXO1, SREBF1, SIRT1, TFAPB2B genes or sex-stratified analyses did not reveal additional information on the regulation of adiponectin levels. The role of genetic variations at the SREBF1 gene in regulating adiponectin needs further investigation by functional studies.

Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide.

PURPOSE: In the setting of a prospective clinical trial, we determined the predictive value of the methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter for outcome in glioblastoma patients treated with the alkylating agent temozolomide. Expression of this excision repair enzyme has been associated with resistance to alkylating chemotherapy. EXPERIMENTAL DESIGN: The methylation status of MGMT in the tumor biopsies was evaluated in 38 patients undergoing resection for newly diagnosed glioblastoma and enrolled in a Phase II trial testing concomitant and adjuvant temozolomide and radiation. The epigenetic silencing of the MGMT gene was determined using methylation-specific PCR. RESULTS: Inactivation of the MGMT gene by promoter methylation was associated with longer survival (P = 0.0051; Log-rank test). At 18 months, survival was 62% (16 of 26) for patients testing positive for a methylated MGMT promoter but reached only 8% (1 of 12) in absence of methylation (P = 0.002; Fisher's exact test). In the presence of other clinically relevant factors, methylation of the MGMT promoter remains the only significant predictor (P = 0.017; Cox regression). CONCLUSIONS: This prospective clinical trial identifies MGMT-methylation status as an independent predictor for glioblastoma patients treated with a methylating agent. The association of the epigenetic inactivation of the DNA repair gene MGMT with better outcome in this homogenous cohort may have important implications for the design of future trials and supports efforts to deplete MGMT by O-6-benzylguanine, a noncytotoxic substrate of this enzyme.

Predictive value of readiness, importance, and confidence in ability to change drinking and smoking.

BACKGROUND: Visual analog scales (VAS) are sometimes used to assess change constructs that are often considered critical for change. Aims of Study: 1.) To determine the association of readiness to change, importance of changing and confidence in ability to change alcohol and tobacco use at baseline with the risk for drinking (more than 21 drinks per week/6 drinks or more on a single occasion more than once per month) and smoking (one or more cigarettes per day) six months later. 2.) To determine the association of readiness, importance and confidence with alcohol (number of drinks/week, number of binge drinking episodes/month) and tobacco (number of cigarettes/day) use at six months. METHODS: This is a secondary analysis of data from a multi-substance brief intervention randomized trial. A sample of 461 Swiss young men was analyzed as a prospective cohort. Participants were assessed at baseline and six months later on alcohol and tobacco use, and at baseline on readiness to change, importance of changing and confidence in ability to change constructs, using visual analog scales ranging from 1-10 for drinking and smoking behaviors. Regression models controlling for receipt of brief intervention were employed for each change construct. The lowest level (1-4) of each scale was the reference group that was compared to the medium (5-7) and high (8-10) levels. RESULTS: Among the 377 subjects reporting unhealthy alcohol use at baseline, mean (SD) readiness, importance and confidence to change drinking scores were 3.9 (3.0), 2.7 (2.2) and 7.2 (3.0), respectively. At follow-up, 108 (29%) reported no unhealthy alcohol use. Readiness was not associated with being risk-free at follow-up, but high importance (OR 2.94; 1.15, 7.50) and high confidence (OR 2.88; 1.46, 5.68) were. Among the 255 smokers at baseline, mean readiness, importance and confidence to change smoking scores were 4.6 (2.6), 5.3 (2.6) and 5.9 (2.7), respectively. At follow-up, 13% (33) reported no longer smoking. Neither readiness nor importance was associated with being a non-smoker, whereas high confidence (OR 3.29; 1.12, 9.62) was. CONCLUSIONS: High confidence in ability to change was associated with favorable outcomes for both drinking and smoking, whereas high importance was associated only with a favorable drinking outcome. This study points to the value of confidence as an important predictor of successful change for both drinking and smoking, and shows the value of importance in predicting successful changes in alcohol use. TRIAL REGISTRATION NUMBER: ISRCTN78822107.