Geographical scale and the role of firm migration in spatial economic dynamics

Spatial economic change can be decomposed in it's demographic constituents firm formation, closure, relocation and growth. This paper focusses on the role of relocation in the balancing equation of spatial economic dynamics: Total Change(zone i) = New firms(i)-Closures(i)+ Growth(i)-Decline(i)+ Inmoves(i)-Outmoves(i). Whereas the other components are scale invariant (i.e. a firm birth is a birth whether measured at the local or the regional level) for firm relocation the geographical scale is very important. The larger the size of the region, the smaller the number of border crossing relocations. The question about the role of firm migration in regional economic change can therefore only be answered taking into account the geographical scale. In this paper we will answer this question for various geographical scales. The data that we use are from the longitudinal business register of the province of Gelderland, in the east of the Netherlands, covering the period 1988-2002.

A model of internal firm relocation in the Netherlands

This paper presents a model of internal relocation of firms in the Netherlands. Firm relocation is driven both by firm internal factors, such as growth, age, and type of activity, as well as external factors, relating to the business cycle, the geographical environment, the composition of the labour force, and the composition of the firm popuation, as well as linkages with other firms. Using a unique longitudinal database of firms in the Province of Gelderland in the Netherlands, we specify and estimate two related models of firm relocation. The decomposition of the migration process in two subprocesses is consitent with the theory of a two stage decision process, whereby in th first stage the firm decides to move, and in the second step it chooses an alternative destination. Different factors are important in both stages of the process.

In search of a modelling strategy for projecting internal migration in European countries - Demographic versus economic-geographical approaches

Internal migration is the most volatile and difficult to predict component of regional demographic change. A pure demographic approach using age and sex-specific parameters of migration intensities cannot fully capture the migration trends over time. One of the approaches that can be used for a better description of past trends and forecasting of future trends is to use additional non-demographic information such as regional economic indicators. In this paper we compare the predictive performance of pure demographic and extended economic-geographical models using data of four European countries at the so-called NUTS 2 level. The models are nested within a GLM specification%2C that allows both demographic and extended models to be written as specific cases of loglinear models. Therefore model fit and performance can be compared directly.

Publishing and sharing multi-dimensional image data with OMERO

Imaging data are used in the life and biomedical sciences to measure the molecular and structural composition and dynamics of cells, tissues, and organisms. Datasets range in size from megabytes to terabytes and usually contain a combination of binary pixel data and metadata that describe the acquisition process and any derived results. The OMERO image data management platform allows users to securely share image datasets according to specific permissions levels: data can be held privately, shared with a set of colleagues, or made available via a public URL. Users control access by assigning data to specific Groups with defined membership and access rights. OMERO’s Permission system supports simple data sharing in a lab, collaborative data analysis, and even teaching environments. OMERO software is open source and released by the OME Consortium at www.openmicroscopy.org

Precision measurement of the η→π+π−π0\eta\to\pi^+\pi^-\pi^0 Dalitz plot distribution with the KLOE detector

Using $1.6$ fb$^{-1}$ of $e^+ e^-\to\phi\to\eta\gamma$ data collected with the KLOE detector at DA$\Phi$NE, the Dalitz plot distribution for the $\eta \to \pi^+ \pi^- \pi^0$ decay is studied with the world's largest sample of $\sim 4.7 \cdot 10^6$ events. The Dalitz plot density is parametrized as a polynomial expansion up to cubic terms in the normalized dimensionless variables $X$ and $Y$. The experiment is sensitive to all charge conjugation conserving terms of the expansion, including a $gX^2Y$ term. The statistical uncertainty of all parameters is improved by a factor two with respect to earlier measurements.Comment: 11 pages, 9 figures, supplement: an ascii tabl

Dietary Acrylamide Intake and the Risk of Lymphatic Malignancies: The Netherlands Cohort Study on Diet and Cancer

BACKGROUND: Acrylamide, a probable human carcinogen, is present in many everyday foods. Since the finding of its presence in foods in 2002, epidemiological studies have found some suggestive associations between dietary acrylamide exposure and the risk of various cancers. The aim of this prospective study is to investigate for the first time the association between dietary acrylamide intake and the risk of several histological subtypes of lymphatic malignancies. METHODS: The Netherlands Cohort Study on diet and cancer includes 120,852 men and women followed-up since September 1986. The number of person years at risk was estimated by using a random sample of participants from the total cohort that was chosen at baseline (n =5,000). Acrylamide intake was estimated from a food frequency questionnaire combined with acrylamide data for Dutch foods. Hazard ratios (HRs) were calculated for acrylamide intake as a continuous variable as well as in categories (quintiles and tertiles), for men and women separately and for never-smokers, using multivariable-adjusted Cox proportional hazards models. RESULTS: After 16.3 years of follow-up, 1,233 microscopically confirmed cases of lymphatic malignancies were available for multivariable-adjusted analysis. For multiple myeloma and follicular lymphoma, HRs for men were 1.14 (95% CI: 1.01, 1.27) and 1.28 (95% CI: 1.03, 1.61) per 10 µg acrylamide/day increment, respectively. For never-smoking men, the HR for multiple myeloma was 1.98 (95% CI: 1.38, 2.85). No associations were observed for women. CONCLUSION: We found indications that acrylamide may increase the risk of multiple myeloma and follicular lymphoma in men. This is the first epidemiological study to investigate the association between dietary acrylamide intake and the risk of lymphatic malignancies, and more research into these observed associations is warranted

Semantic inference using chemogenomics data for drug discovery

<p>Abstract</p> <p>Background</p> <p>Semantic Web Technology (SWT) makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, and Chem2Bio2RDF. Integration of these sets creates large networks of information. We have previously described a tool called WENDI for aggregating information pertaining to new chemical compounds, effectively creating evidence paths relating the compounds to genes, diseases and so on. In this paper we examine the utility of automatically inferring new compound-disease associations (and thus new links in the network) based on semantically marked-up versions of these evidence paths, rule-sets and inference engines.</p> <p>Results</p> <p>Through the implementation of a semantic inference algorithm, rule set, Semantic Web methods (RDF, OWL and SPARQL) and new interfaces, we have created a new tool called Chemogenomic Explorer that uses networks of ontologically annotated RDF statements along with deductive reasoning tools to infer new associations between the query structure and genes and diseases from WENDI results. The tool then permits interactive clustering and filtering of these evidence paths.</p> <p>Conclusions</p> <p>We present a new aggregate approach to inferring links between chemical compounds and diseases using semantic inference. This approach allows multiple evidence paths between compounds and diseases to be identified using a rule-set and semantically annotated data, and for these evidence paths to be clustered to show overall evidence linking the compound to a disease. We believe this is a powerful approach, because it allows compound-disease relationships to be ranked by the amount of evidence supporting them.</p

Clinical Relevance and Discriminatory Value of Elevated Liver Aminotransferase Levels for Dengue Severity

Dengue is a global public health problem, as the incidence of the disease has reached hyperendemic proportions in recent decades. Infection with dengue can cause acute, febrile illness or severe disease, which can lead to plasma leakage, bleeding, and organ impairment. One of the most prominent clinical characteristics of dengue patients is increased aspartate and alanine aminotransferase liver enzyme levels. The significance of this is uncertain, as it is transient in the majority of cases, and most patients recover uneventfully without liver damage. In this study, we characterized this phenomenon in the context of dengue severity and found that, although liver enzyme levels increased concurrently with dengue severity, they could not sufficiently discriminate between dengue fever and dengue hemorrhagic fever or between non-severe and severe dengue. Therefore clinicians may need to use other parameters to distinguish dengue severity in patients during early illness

A controlled trial of protein enrichment of meal replacements for weight reduction with retention of lean body mass

<p>Abstract</p> <p>Background</p> <p>While high protein diets have been shown to improve satiety and retention of lean body mass (LBM), this study was designed to determine effects of a protein-enriched meal replacement (MR) on weight loss and LBM retention by comparison to an isocaloric carbohydrate-enriched MR within customized diet plans utilizing MR to achieve high protein or standard protein intakes.</p> <p>Methods</p> <p>Single blind, placebo-controlled, randomized outpatient weight loss trial in 100 obese men and women comparing two isocaloric meal plans utilizing a standard MR to which was added supplementary protein or carbohydrate powder. MR was used twice daily (one meal, one snack). One additional meal was included in the meal plan designed to achieve individualized protein intakes of either 1) 2.2 g protein/kg of LBM per day [high protein diet (HP)] or 2) 1.1 g protein/kg LBM/day standard protein diet (SP). LBM was determined using bioelectrical impedance analysis (BIA). Body weight, body composition, and lipid profiles were measured at baseline and 12 weeks.</p> <p>Results</p> <p>Eighty-five subjects completed the study. Both HP and SP MR were well tolerated, with no adverse effects. There were no differences in weight loss at 12 weeks (-4.19 ± 0.5 kg for HP group and -3.72 ± 0.7 kg for SP group, p > 0.1). Subjects in the HP group lost significantly more fat weight than the SP group (HP = -1.65 ± 0.63 kg; SP = -0.64 ± 0.79 kg, P = 0.05) as estimated by BIA. There were no significant differences in lipids nor fasting blood glucose between groups, but within the HP group a significant decrease in cholesterol and LDL cholesterol was noted at 12 weeks. This was not seen in the SP group.</p> <p>Conclusion</p> <p>Higher protein MR within a higher protein diet resulted in similar overall weight loss as the standard protein MR plan over 12 weeks. However, there was significantly more fat loss in the HP group but no significant difference in lean body mass. In this trial, subject compliance with both the standard and protein-enriched MR strategy for weight loss may have obscured any effect of increased protein on weight loss demonstrated in prior weight loss studies using whole food diets.</p