PROTOCOL: Effectiveness of public-private partnerships on educational access and quality of primary and secondary schooling in low- and middle-income countries: A systematic review.

This protocol serves as a guiding source for a Campbell registered systematic review aiming to assess the effectiveness of Public-Private Partnerships (PPPs) in education in Low- and Middle-Income Countries (LMICs). The primary question for this review is: What is known about the impact of PPPs on improving access (i.e., enrolment, attendance, drop-out, and completion) and quality (i.e., students' learning outcomes and teachers' teaching practices) of primary and secondary schooling in LMICs? Using a predefined search query, we will retrieve studies from various databases including Scopus, Campbell Library, EBSCO Education Research Complete, NBER, Dissertation and Theses Global (ProQuest), along with other sources of grey literature. Covidence will be used for screening and extraction. A bias assessment tool will be used for the included studies. A standardised mean difference (SMD) effect size of Hedges' g will be calculated for the outcome variables using RevMan. This review will provide updated evidence about the impact of PPP in school education across LMICs, which will be instrumental for policy and practice level decisions for education improvement.

DFT insights into LaFeO3 with Mn substitution: A promising path to energy-efficient magneto-optical applications.

In recent years, the demand for electronic materials has significantly increased, driven by industrial needs and the pursuit of cost-efficient alternatives. This comprehensive study investigates the effects of Mn substitution on LaFeO3 through the implementation of the GGA approach in density functional theory. The research findings demonstrate remarkable consistency with the experimental outcomes reported in the existing literature pertaining to the studied compounds. However, this study unveils novel insights into the mechanical and optical characteristics of the doped structures, which have not been previously reported. The structural stability is rigorously examined through multiple stability criteria, encompassing structural optimization, tests of elastic stability, and enthalpy of formation calculations. Furthermore, the electronic and optical properties of the compounds exhibit exceptional improvements in conductivity and reflectivity as a result of the doping process. The band structure analysis reveals the presence of a Moss-Burstein shift. Investigation of the magnetic properties indicates an increase in the magnetic moment value due to the Fe-Mn degeneracy resulting from increased Mn content. Mechanical analysis of the elastic moduli B, G, and Y demonstrates an enhanced strength and metal-like conductivity, attributed to the induced anharmonicity. Moreover, the internal strain factor suggests a higher degree of bond flexibility, implying potential applications of these compounds in flexible electronics.

Artificial Intelligence Modeling-Based Optimization of an Industrial-Scale Steam Turbine for Moving toward Net-Zero in the Energy Sector.

Augmentation of energy efficiency in the power generation systems can aid in decarbonizing the energy sector, which is also recognized by the International Energy Agency (IEA) as a solution to attain net-zero from the energy sector. With this reference, this article presents a framework incorporating artificial intelligence (AI) for improving the isentropic efficiency of a high-pressure (HP) steam turbine installed at a supercritical power plant. The data of the operating parameters taken from a supercritical 660 MW coal-fired power plant is well-distributed in the input and output spaces of the operating parameters. Based on hyperparameter tuning, two advanced AI modeling algorithms, i.e., artificial neural network (ANN) and support vector machine (SVM), are trained and, subsequently, validated. ANN, as turned out to be a better-performing model, is utilized to conduct the Monte Carlo technique-based sensitivity analysis toward the high-pressure (HP) turbine efficiency. Subsequently, the ANN model is deployed for evaluating the impact of individual or combination of operating parameters on the HP turbine efficiency under three real-power generation capacities of the power plant. The parametric study and nonlinear programming-based optimization techniques are applied to optimize the HP turbine efficiency. It is estimated that the HP turbine efficiency can be improved by 1.43, 5.09, and 3.40% as compared to that of the average values of input parameters for half-load, mid-load, and full-load power generation modes, respectively. The annual reduction in CO2 measuring 58.3, 123.5, and 70.8 kilo ton/year (kt/y) corresponds to half-load, mid-load, and full load, respectively, and noticeable mitigation of SO2, CH4, N2O, and Hg emissions is estimated for the three power generation modes of the power plant. The AI-based modeling and optimization analysis is conducted to enhance the operation excellence of the industrial-scale steam turbine that promotes higher-energy efficiency and contributes to the net-zero target from the energy sector.

Characterization of different biocatalyst formats for BVMO-catalyzed cyclohexanone oxidation.

Cyclohexanone monooxygenase (CHMO), a member of the Baeyer-Villiger monooxygenase family, is a versatile biocatalyst that efficiently catalyzes the conversion of cyclic ketones to lactones. In this study, an Acidovorax-derived CHMO gene was expressed in Pseudomonas taiwanensis VLB120. Upon purification, the enzyme was characterized in vitro and shown to feature a broad substrate spectrum and up to 100% conversion in 6 h. Furthermore, we determined and compared the cyclohexanone conversion kinetics for different CHMO-biocatalyst formats, that is, isolated enzyme, suspended whole cells, and biofilms, the latter two based on recombinant CHMO-containing P. taiwanensis VLB120. Biofilms showed less favorable values for KS (9.3-fold higher) and kcat (4.8-fold lower) compared with corresponding KM and kcat values of isolated CHMO, but a favorable KI for cyclohexanone (5.3-fold higher). The unfavorable KS and kcat values are related to mass transfer- and possibly heterogeneity issues and deserve further investigation and engineering, to exploit the high potential of biofilms regarding process stability. Suspended cells showed only 1.8-fold higher KS , but 1.3- and 4.2-fold higher kcat and KI values than isolated CHMO. This together with the efficient NADPH regeneration via glucose metabolism makes this format highly promising from a kinetics perspective.