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The composition of grapes for wine production is intricately linked to the water status of vineyards during the vegetative period, with water stress significantly impacting grape yield and quality. Current vineyard water status monitoring primarily relies on a variety of soil moisture sensors and remote thermal sensors. This study aims to present spatial vegetation index values derived from a handheld multispectral camera, specifically the Plant-O-Meter (POM), concerning diverse irrigation regimes within an organic vineyard near Belgrade, Serbia. Conducted in 2022, a year-long experiment involved four recordings using POM during different phenophases of the Panonia grape variety. POM utilizes a multispectral source emitting pulse trains of various wavelengths for plant analysis. Three irrigation treatments were applied based on the percentage of crop evapotranspiration (ETc): full irrigation (F - 100% ETc), deficit irrigation (D - 50% ETc), and rainfed (R - 0% ETc), with irrigation norms set at 30 mm for F and 15 mm for D. Soil moisture, measured through standard gravimetric and TDR methods, exhibited the highest values in the F treatment and the lowest in the R treatment. Vegetation indices NDVI (Normalized Difference Vegetation Index) and GNDVI (Green Vegetation Index Normalized Difference) displayed varying values across treatments. NDVI values were 0.68 (F), 0.74 (D), and 0.75 (R), while GNDVI values were 0.63 (F), 0.68 (D), and 0.70 (R). The results highlight the significant impact of irrigation regimes on soil moisture, coupled with unexpected vegetation index values per treatment. The study concludes that the Panonia grape variety demonstrates remarkable tolerance to water deficits, suggesting that some irrigation events during the experiment were unnecessary for the specific terroir conditions. However, considering the potential impacts of climate change, the obtained results may undergo alterations in the future.

Essential thrombocythemia (ET) and prefibrotic primary myelofibrosis (prePMF) initially have a similar phenotypic presentation with thrombocytosis. The aim of our study was to determine significant clinical-laboratory parameters at presentation to differentiate prePMF from ET as well as to develop and validate a predictive diagnostic prePMF model. This retrospective study included 464 patients divided into ET (289 pts) and prePMF (175 pts) groups. The model was built using data from a development cohort (229 pts; 143 ET, 86 prePMF), which was then tested in an internal validation cohort (235 pts; 146 ET, 89 prePMF). The most important prePMF predictors in the multivariate logistic model were age ≥ 60 years (RR = 2.2), splenomegaly (RR = 13.2), and increased lactat-dehidrogenase (RR = 2.8). Risk scores were assigned according to derived relative risk (RR) for age ≥ 60 years (1 point), splenomegaly (2 points), and increased lactat-dehidrogenase (1 point). Positive predictive value (PPV) for pre-PMF diagnosis with a score of ≥points was 69.8%, while for a score of ≥3 it was 88.2%. Diagnostic performance had similar values in the validation cohort. In MPN patients with thrombocytosis at presentation, the application of the new model enables differentiation of pre-PMF from ET, which is clinically relevant considering that these diseases have different prognoses and treatments.

In this study, we present and analyse the case of the Workshop titled “A Geometric Adven ture in the World of Grasshopper”, realised in September 2023, at the University of Belgrade, Faculty of Architecture, within the manifestation called “The Week with Architecture”. The content of the Workshop has been derived from the elective course “Parametric Modelling”, offered to the first year master students. After briefly explaining the teaching context in which the Workshop occurred, we present the content structure divided into four working days, three of which dedicated to introducing various programming techniques in the Rhino software and its well-known plug-in Grasshop per, and the fourth day left for the Workshop exhibition completing. Aimed at introducing programming beginners into basic techniques of algorithmic creation of architectural form, this Workshop started with an in-house developed Grasshopper definition producing various 2D geometric patterns. Based on this simple definition the students learned the fundamental elements of the visual algorithmic systems. As a result of first day they produced a range of different geometric patterns based on the p1 symmetry repetition of circles and polygons on a predefined rectangular grid. The second day of the Workshop was dedicated to the geometry of spatial curves, and required from the participating students considerably more programming understanding and an additional research of the field. The third Workshop day was character ized by an integration of the techniques of the first and the second Workshop day. In this final programming exercise the participants had to use the geometric grid, in terms of distribution of a chosen spatial curve. This teaching activity resulted in excellent geometric models created by participating stu dents, exhibited in the form of prints, the last day of the Workshop. All the Workshop commu nication and information exchange was supported and saved in the specially created TEAMS lea

This study investigated the hierarchical structure of physical characteristics in elite young (i.e., U17-U19) basketball players according to playing positions. In addition, their predictive value of physical characteristics was determined for the evaluation of players' physical preparedness. Sixty elite male basketball players performed 13 standardized specific field tests in order to assess the explosive power of lower limbs, speed, and change-of-direction speed. They were divided into three groups according to playing positions (guard [n = 28], forward [n = 22], center [n = 10]). The basic characteristics of the tested sample were: age = 17.36 ± 1.04 years, body height = 192.80 ± 4.49 cm, body mass = 79.83 ± 6.94 kg, and basketball experience = 9.38 ± 2.10 years for guards; age = 18.00 ± 1.00 years, body height = 201.48 ± 3.14 cm, body mass = 90.93 ± 9.85 kg, and basketball experience = 9.93 ± 2.28 years for forwards; and age = 17.60 ± 1.43 years; body height = 207.20 ± 3.29 cm, body mass = 104.00 ± 9.64 kg, and basketball experience = 9.20 ± 1.62 years for centers. For all playing positions factor analysis extracted three factors, which cumulatively explained 76.87, 88.12 and 87.63% of variance, respectively. The assessed performance measures were defined as significant (p < 0.001), with regression models of physical performance index (PPINDEX). PPINDEX of guards = -6.860 + (0.932 × t-test) - (1.656 × Acceleration 15 m) - (0.020 × Countermovement jump); PPINDEX of forwards = -3.436 - (0.046 × Countermovement jump with arm swing) - (1.295 × Acceleration 15 m) + (0.582 × Control of dribbling); PPINDEX of centers = -4.126 + (0.604 × Control of dribbling) - (1.315 × Acceleration 15 m) - (0.037 × Sargent jump). A model for the evaluation of physical performance of young basketball players has been defined. In addition, this model could be used as a reference model for selection procedures, as well as to monitor the efficacy of applied training programmes within the s