Sustainable approach for recycling construction and demolition waste into building material in Tanzania

Because it is desired to achieve sustainability in the construction industry, the recycled products should not only be measured by production costs, but by using economic, social and environmental criteria. Knowledge on how to precisely determine the sustainability of recycled building materials is still limited because most of the available sustainability assessment tools are developed to evaluate whole building components. This paper aims at investigating the possibility of recycling the construction and demolition (C&D) waste (mainly cementitious rubble) into building material such as concrete blocks that meet the requirements for structural walls in Tanzania in a sustainable manner. A sustainability tool was applied to determine which of the recycling recipes used to produce the qualified concrete blocks was sustainable. The findings showed the recipe which used sisal fibers (i.e., 0.25% amount of cement) in 100% recycled aggregates from C&D waste for concrete block production was found to be a more sustainable recipe than the others. This condition suggests that using 100% C&D waste into building materials contributes in conservation of resource of relatively the same amount of natural aggregates for future use which is in line with the sustainable construction concept. Therefore, it is possible to recycle 100% C&D waste into building materials in Tanzania using sisal fibers which are the locally produced materials.Keywords: Sustainable construction, recycling, C&D waste, building material, Tanzani

Minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis : predictive model based on machine learning

Very few data are available on predictors of minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis (PsA). Such data are crucial, since the therapeutic measures used to change the adverse course of PsA are more likely to succeed if we intervene early. In the present study, we used predictive models based on machine learning to detect variables associated with achieving MDA in patients with recent-onset PsA. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. The dataset contained data for the independent variables from the baseline visit and from follow-up visit number 1. These were matched with the outcome measures from follow-up visits 1 and 2, respectively. We trained a random forest-type machine learning algorithm to analyze the association between the outcome measure and the variables selected in the bivariate analysis. In order to understand how the model uses the variables to make its predictions, we applied the SHAP technique. We used a confusion matrix to visualize the performance of the model. The sample comprised 158 patients. 55.5% and 58.3% of the patients had MDA at the first and second follow-up visit, respectively. In our model, the variables with the greatest predictive ability were global pain, impact of the disease (PsAID), patient global assessment of disease, and physical function (HAQ-Disability Index). The percentage of hits in the confusion matrix was 85.94%. A key objective in the management of PsA should be control of pain, which is not always associated with inflammatory burden, and the establishment of measures to better control the various domains of PsA

Search for neutral MSSM Higgs bosons at LEP.

The four LEP collaborations, ALEPH, DELPHI, L3 and OPAL, have searched for the neutral Higgs bosons which are predicted by the Minimal Supersymmetric standard model (MSSM). The data of the four collaborations are statistically combined and examined for their consistency with the background hypothesis and with a possible Higgs boson signal. The combined LEP data show no significant excess of events which would indicate the production of Higgs bosons. The search results are used to set upper bounds on the cross-sections of various Higgs-like event topologies. The results are interpreted within the MSSM in a number of “benchmark” models, including CP-conserving and CP-violating scenarios. These interpretations lead in all cases to large exclusions in the MSSM parameter space. Absolute limits are set on the parameter cosβ and, in some scenarios, on the masses of neutral Higgs bosons