Cities in late medieval Europe: the promise and curse of modernity

This article examines how modern historiography has developed quite differentiated views on the way medieval cities have given expression to renewal and to creativity. 'National' traditions have played a highly influential role in modifying the general views articulated in the major syntheses produced by scholars such as Max Weber and Henri Pirenne at the beginning of the twentieth century. An almost jubilant way of looking at the city as the hotbed of modernity gave room, in the decades after the Great War, to pessimism and a negative view on urbanity, before a more nuanced and positive view has been re-established after World War II and in the course of recent paradigmatic changes

Sustainability and consumer responses: The effect of bad industry reputation and fit

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and EconomicsThis work project investigates how consumers’ responses to sustainability activities of organisations are influenced by the bad reputation of the industry they are operating in. Specifically, it tested how consumers’ attributions about the motives behind companies’ engagement are affected and whether the fit of the cause with companies’ core business influences this attributional processing. Surveying 299 participants, the study provides support that a high fit program provokes values-driven attributions, which likewise im-prove consumers’ trust, corporate reputation and image, rendering companies’ sustaina-bility investments effective, even in bad reputation industries. Furthermore, theoretical and practical implications together with future research suggestions are provided

The contribution of diet and genotype to iron status in women:a classical twin study

This is the first published report examining the combined effect of diet and genotype on body iron content using a classical twin study design. The aim of this study was to determine the relative contribution of genetic and environmental factors in determining iron status. The population was comprised of 200 BMI- and age-matched pairs of MZ and DZ healthy twins, characterised for habitual diet and 15 iron-related candidate genetic markers. Variance components analysis demonstrated that the heritability of serum ferritin (SF) and soluble transferrin receptor was 44% and 54% respectively. Measured single nucleotide polymorphisms explained 5% and selected dietary factors 6% of the variance in iron status; there was a negative association between calcium intake and body iron (p = 0.02) and SF (p = 0.04)

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

Hermeneutics and Nature

This paper contributes to the on-going research into the ways in which the humanities transformed the natural sciences in the late Eighteenth and early Nineteenth Centuries. By investigating the relationship between hermeneutics -- as developed by Herder -- and natural history, it shows how the methods used for the study of literary and artistic works played a crucial role in the emergence of key natural-scientific fields, including geography and ecology

Clinical sequencing: is WGS the better WES?

Current clinical next-generation sequencing is done by using gene panels and exome analysis, both of which involve selective capturing of target regions. However, capturing has limitations in sufficiently covering coding exons, especially GC-rich regions. We compared whole exome sequencing (WES) with the most recent PCR-free whole genome sequencing (WGS), showing that only the latter is able to provide hitherto unprecedented complete coverage of the coding region of the genome. Thus, from a clinical/technical point of view, WGS is the better WES so that capturing is no longer necessary for the most comprehensive genomic testing of Mendelian disorders

Managing AI in Manufacturing Systems - Solving the Data Bottleneck

The Data Bottleneck refers to the challenge of ensuring the availability of the right data at the right time in AI-driven projects. Early stages often involve uncertainty about when, how, and how much data will be required. The proposed approach focuses on estimating data requirements and determining when the data is needed at each phase of the AI lifecycle. This includes identifying critical data dependencies, ensuring data quality, managing imbalanced datasets, and implementing post-deployment monitoring to adapt to data shifts. By addressing these issues, organizations can enhance fairness, accuracy, and adaptability while sustaining model performance. Effective data bottleneck management empowers organizations to unify their data, improving trust, accessibility, and control. This approach supports key business objectives while enabling the development of reliable, scalable, and adaptable AI systems