There is a large literature on public-private-partnership, covering many different areas and aspects. This article deals with a specific but important aspect: the decision-making mechanisms to choose the management of PPP enterprises. In this sector, a suitable choice of managers is of particular importance because the persons chosen must balance the public and private interests. This is often difficult to achieve. Two new procedures are discussed, “Directed Random Choice” and “Rotating CEOs”. In each case, the advantages and disadvantages of the procedure of choosing the managers of PPP enterprises are discussed and evaluated. It is concluded that the two novel mechanisms should be seriously considered when choosing the managers of PPP enterprises.

For five different regions in Kırklareli province, heavy metals; such as Pb, Ni, Cu, Mn, Cd, Cr, Co, Zn, Mo, and Fe in the mixture of leaves and flowers from linden trees (Tilia tomentosa L.) were analyzed by using flame atomic absorption spectroscopy after the samples were dissolved with microwave method. Also, organochloride pesticides; such as ∑BHC: [α-BHC, β-BHC, γ-BHC, and δ-BHC], ∑DDT: [4,4’-DDD, 4,4’-DDE, and 4,4’-DDT], α-Endosulfan, β-Endosulfan, Endosulfan sulfate, Heptachlor, Heptachlor-endo-epoxide, Aldrin, Dieldrin, Endrin aldehyde, Endrin ketone, Endrin and Methoxychlor in these samples were determined by utilizing gas chromatography mass spectroscopy after the samples were prepared for analyses by using QuEChERS method. The metal concentrations in the samples were in the range of 45.3 to 268 mg/kg for Mn, 0.25 to 18.8 mg/kg for Cu, 11.5 to 46.1 mg/kg for Zn, 128 to 1310 mg/kg for Fe, 10.4 to 38.6 mg/kg for Mo, 0.82 to 1.34 mg/kg for Cd, 0 to 6.45 mg/kg for Ni, 0 to 19.2 mg/kg for Pb, and 0 to 8.25 mg/kg for Cr. Moreover, the concentrations of organochloride pesticides in samples were usually determined to be lower than their maximum residue level values given the pesticide residue limit regulation of Turkish Food Codex. 

The performance of five cauliflower cultivars in conventional and alternative phytosanitary management—without the use of synthetic pesticides—was evaluated. Two experiments were conducted at Epagri, Ituporanga Experimental Station in February 2018 and 2019. A randomized block design with four repetitions was adopted, with twenty plants of each cultivar as plots. The seedlings were transplanted on millet and mucuna straw at a spacing of 0.5 m × 0.8 m. We evaluated agronomic yield, inflorescence quality, pest damage and plant diseases, especially bacterial and fungal rots. The cauliflower hybrids Vera, Verona and Serena stood out in productivity and quality, being the most indicated for sowing in off-season crops, in the Alto Vale do Itajaí region. The most productive cultivars were less damaged by bacterial diseases and defoliating caterpillars and without interference of whitefly infestation on yield. The results also reveal that it is possible to control pests and diseases with phytosanitary products of lower toxicity, i.e., with lower residues of synthetic pesticides.

The properties of the beta batteries are compared, which are made on the basis of the different β-isotopes with beta decay. Tritium and Ni-63 make it possible to make β-sources of high activity, without harmful associated emissions, with low self-absorption, emitting high-energy β-electrons that penetrate deep into the semiconductor and generate a large number of electron-hole pairs. The efficiency of beta batteries needs to be analyzed based on the real energy distribution of β-electrons. It makes possible to obtain the real value of the energy absorbed inside the β-source, correctly estimate the amount of self-absorption of the β-electrons and part of the β-electronsthere is a penetrate into the semiconductor, the number of electrons and holes that are generated in the semiconductor, and the magnitude of the idling voltage. Formulas for these quantities are calculated in this paper.

This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.