Cracking resistance of AlMg4.5Mn alloy TIG welded joints

In this paper the AlMg4.5Mn TIG welded joints have been tested in order to investigate their cracking resistance. Testing plates, size of 500×250×12 mm, are welded by TIG procedure in a horizontal-vertical position. Various mixtures of inert gases are prepared and supplied by MESSER TEHNOGAS AD, Smederevo (Serbia), including Ar, Ar + 0.015% N 2 , Ar + 15% He + 0.015% N 2 , Ar + 30% He + 0.015% N 2 , Ar + 50% He + 0.015% N 2 . Nondestructive testing is used to check joint defects, primarily porosity, as typical for this type of alloys. The Charpy specimens, with the notch positioned in different regions of the welded joint, are tested using instrumented pendulum to separate crack initiation and growth energy. Crack resistance is evaluated by using static (KIc) and dynamic testing (Paris law - fatigue crack growth)

Geometric deformation analysis in free geodetic networks: case study for Fruska Gora in Serbia

The deformation measurements are performed for the purpose of obtaining information concerning ground movement and objects on the ground within given time intervals. For the purpose of improving conventional models of deformation analysis (CDA) it is desirable to use several different methods and also implement alternative procedures as a further improvement, such as the concept of robust geodetic networks and strain analysis, aimed at obtaining objective information about the movements. In the present paper, in addition to the CDA methods, we also analyze the robust methods in deformation detecting and the method of the strain analysis based on elasticity theory as a supplement to the conventional geometric deformation methods (CDA). The mentioned methods are applied and analysed for the case of a test example of Fruska Gora in Serbia, for which there exist geological and geophysical studies of recent tectonic movements. The measuring results for two measuring epochs concern the GNSS vectors measured by applying the fast static method within closed polygons over a ten-year interval, where only the horizontal movement component is analysed. The efficiency of the applied CDA and robust methods is measured by applying a mean success rate (MSR) by applying Monte Carlo simulations in order to investigate the efficiency of a given methods for a given control network

Environmentally Friendly Packaging Materials Based on Thermoplastic Starch

Low-density polyethylene (LDPE) is extensively used as packaging material, and as such has a short service life, but long environmental persistence. The alternative to reducing the impact of LDPE as packaging material on the environment is to blend it with carbohydrate-based polymers, like starch. Therefore, the focus of this investigation was to prepare bio-based blends of LDPE and thermoplastic starch (TPS) containing different amounts of TPS using a Brabender kneading chamber. Due to incompatibility of LDPE/TPS blends, a styrene–ethylene/butylene–styrene block copolymer, grafted with maleic anhydride (SEBS-g-MA) containing 2 mol % anhydride groups, was added as a compatibilizer. The effect of the biodegradable, hydrophilic TPS, its content, and the incorporation of the compatibilizer on the properties of LDPE/TPS blends were analysed. The characterization was performed by means of thermogravimetric analysis (TG), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and water absorption (WA). Based on the results of the morphological structure, a good dispersion of the TPS phase in LDPE matrix was obtained with the incorporation of compatibilizer, which resulted in better thermal and barrier properties of these materials

Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis

The goals of this study were to examine whether machine-learning algorithms outper-form multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to in-vestigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Fi-nally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response

Development and validation of a prognostic multivariable model to predict insufficient clinical response to methotrexate in rheumatoid arthritis

Objective The objective was to predict insufficient response to 3 months methotrexate (MTX) in DMARD naïve rheumatoid arthritis patients. Methods A Multivariable logistic regression model of rheumatoid arthritis patients starting MTX was developed in a derivation cohort with 285 patients starting MTX in a clinical multicentre, stratified single-blinded trial, performed in seven secondary care clinics and a tertiary care clinic. The model was validated in a validation cohort with 102 patients starting MTX at a tertiary care clinic. Outcome was insufficient response (disease activity score (DAS)28 >3.2) after 3 months of MTX treatment. Clinical characteristics, lifestyle variables, genetic and metabolic biomarkers were determined at baseline in both cohorts. These variables were dichotomized and used to construct a multivariable prediction model with backward logistic regression analysis. Results The prediction model for insufficient response in the derivation cohort, included: DAS28>5.1, Health Assessment Questionnaire>0.6, current smoking, BMI>25 kg/m2, ABCB1 rs1045642 genotype, ABCC3 rs4793665 genotype, and erythrocyte-folate<750 nmol/L. In the derivation cohort, AUC of ROC curve was 0.80 (95%CI: 0.73–0.86), and 0.80 (95%CI: 0.69–0.91) in the validation cohort. Betas of the prediction model were transformed into total risk score (range 0–8). At cutoff of 4, probability for insufficient response was 44%. Sensitivity was 71%, specificity 72%, with positive and negative predictive value of 72% and 71%. Conclusions A prognostics prediction model for insufficient response to MTX in 2 prospective RA cohorts by combining genetic, metabolic, clinical and lifestyle variables was developed and validated. This model satisfactorily identified RA patients with high risk of insufficient response to MTX

Ancient chicken remains reveal the origins of virulence in Marek’s disease virus

The pronounced growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek’s disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the past century. Today, MDV infections kill >90% of unvaccinated birds, and controlling it costs more than US$1 billion annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens

Origins and genetic legacy of prehistoric dogs

Dogs were the first domestic animal, but little is known about their population history and to what extent it was linked to humans. We sequenced 27 ancient dog genomes and found that all dogs share a common ancestry distinct from present-day wolves, with limited gene flow from wolves since domestication but substantial dog-to-wolf gene flow. By 11,000 years ago, at least five major ancestry lineages had diversified, demonstrating a deep genetic history of dogs during the Paleolithic. Coanalysis with human genomes reveals aspects of dog population history that mirror humans, including Levant-related ancestry in Africa and early agricultural Europe. Other aspects differ, including the impacts of steppe pastoralist expansions in West and East Eurasia and a near-complete turnover of Neolithic European dog ancestry

Ancient chicken remains reveal the origins of virulence in Marek's disease virus

This is the author accepted manuscript. The final version is available from the American Association for the Advancement of Science via the DOI in this recordData and materials availability: All MDV sequence data generated have been deposited in GenBank under accession PRJEB64489. Code is available at GitHub (https://github.com/antonisdim/MDV) and archived at Zenodo (https://zenodo.org/records/10022436) (25).The pronounced growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek's disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the past century. Today, MDV infections kill >90% of unvaccinated birds, and controlling it costs more than US$1 billion annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens.European Research Council (ERC)Wellcome TrustOxford Martin School Pandemic Genomics ProgrammeArts and Humanities Research Council (AHRC)European Union Horizon 2020Biotechnology and Biological Sciences Research Council (BBSRC)Research Foundation–Flanders (Fonds voor Wetenschappelijk Onderzoek