Synthesis of macro-mesoporous Titania (Titanium dioxide-TiO₂) nanospheres was successfully achieved using a modified template-free methodology to incorporate macroporous channels into a mesoporous TiO₂ framework to form mixed macro-mesoporous TiO₂ spheres (MMPT), which were doped with carbon dots (C-dots) to form improved nanocomposites (C-dots@MMPT). Elemental composition, surface bonding and optical properties of these nanocomposites were characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR) and ultraviolet-visible absorption spectroscopy (UV-VIS). Evaluation of photocatalytic activity for each (C-Dots@MMPT) sample was performed via degrading the Methylene Blue (MB) dye compared with bare samples (MMPT) under visible light irradiation using 300 Watt halogen lamp.

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.

By reviewing US state-level panel data on infrastructure spending and on per capita income inequality from 1950 to 2010, this paper sets out to test whether an empirical link exists between infrastructure and inequality. Panel regressions with fixed effects show that an increase in the growth rate of spending on highways and higher education in a given decade correlates negatively with Gini indices at the end of the decade, thus suggesting a causal effect from growth in infrastructure spending to a reduction in inequality through better access to education and opportunities for employment. More significantly, this relationship is more pronounced with inequality at the bottom 40 percent of the income distribution. In addition, infrastructure expenditures on highways are shown to be more effective at reducing inequality. By carrying out a counterfactual experiment, the results show that those US states with a significantly higher bottom Gini coefficient in 2010 had underinvested in infrastructure during the previous decade. From a policy-making perspective, new innovations in finance for infrastructure investments are developed, for the US, other industrially advanced countries and also for developing economies.

This study examines conditions that impact PPP delivery success or failure in the roadways sector in India using Qualitative Comparative Analysis. QCA is well-suited for problems where multiple factors combine to create pathways leading to an outcome. Past investigations have compared PPP and non-PPP project delivery performance, but this study examines performance within PPPs by uncovering a set of conditions that combine to influence the success or failure road PPP project delivery in India. Based on data from 21 cases, pathways explaining project delivery success or failure were identified. Specifically, PPPs with high concessionaire equity investment and low regional industrial activity led to project delivery success. Projects with lower concessionaire equity investment and low reliance on toll revenue and with either: (a) high project technical complexity or (b) high regional industrial activity, led to project delivery failure. The pathways identified did not have coverage values that they were extremely strong. Coverage strength was hindered by lack of access to information on additional conditions that could be configurationally important. Further, certain characteristics of the Indian market limit generalization. Identification of combinations of conditions leading to PPP project delivery success or failure improves knowledge of the impacts of structure and characteristics of these complex arrangements. This study is one of the first to use fuzzy QCA to understand project delivery success/failure in road PPP projects. Moreover, this study takes into account factors specific to a sector and delivery mode to explain project delivery performance.

In this paper, an improved mathematical model for flashover behavior of polluted insulators is proposed based on experimental tests. In order to determine the flashover model of polluted insulators, the relationship between conductivity and salinity of solution pollution layer of the insulator is measured. Then, the leakage of current amplitude of four common insulators versus axial, thermal conductivity and arc constants temperature was determined. The experimental tests show that top leakage distance (TLd) to bottom leakage distance (BLd) ratio of insulators has a significant effect on critical voltage and current. Therefore, critical voltage and current were modeled by TLd to BLd ratio Index (M). Also, salinity of solution pollution layer of the insulators has been applied to this model by resistance pollution parameter. On the other hand, arc constants of each insulator in new model have been identified based on experimental results. Finally, a mathematical model is intended for critical voltage against salinity of solution pollution layer of different insulators. This model depends on insulator profile. There is a good agreement between the experimental tests of pollution insulators obtained in the laboratory and values calculated from the mathematical models developed in the present study.

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.