Algorithmic correspondence and completeness in modal logic. I. The core algorithm SQEMA

Modal formulae express monadic second-order properties on Kripke frames, but in many important cases these have first-order equivalents. Computing such equivalents is important for both logical and computational reasons. On the other hand, canonicity of modal formulae is important, too, because it implies frame-completeness of logics axiomatized with canonical formulae. Computing a first-order equivalent of a modal formula amounts to elimination of second-order quantifiers. Two algorithms have been developed for second-order quantifier elimination: SCAN, based on constraint resolution, and DLS, based on a logical equivalence established by Ackermann. In this paper we introduce a new algorithm, SQEMA, for computing first-order equivalents (using a modal version of Ackermann's lemma) and, moreover, for proving canonicity of modal formulae. Unlike SCAN and DLS, it works directly on modal formulae, thus avoiding Skolemization and the subsequent problem of unskolemization. We present the core algorithm and illustrate it with some examples. We then prove its correctness and the canonicity of all formulae on which the algorithm succeeds. We show that it succeeds not only on all Sahlqvist formulae, but also on the larger class of inductive formulae, introduced in our earlier papers. Thus, we develop a purely algorithmic approach to proving canonical completeness in modal logic and, in particular, establish one of the most general completeness results in modal logic so far.Comment: 26 pages, no figures, to appear in the Logical Methods in Computer Scienc

When the clinic is not yet built … the Avian Park Service Learning Centre story

The Ukwanda Centre for Rural Health (UCRH) opened in 2001, followed 10 years later by the establishment of the Ukwanda Rural Clinical School in one of the rural health districts of the Western Cape. This paper relates the journey of the Faculty with the underserviced community of Avian Park through the provision of healthcare services aimed at addressing needs identified by the local community. It attempts to substantiate the meaning of the word Ukwanda, translated ‘to grow’ and ‘develop within the community’ in order to reach the primary goal of being an ‘engaged institution’. The Avian Park Service Learning Centre (APSLC) is the culmination of the aspirations of a number of stakeholders who wanted to respond to the community needs for access to basic healthcare while providing learning opportunities for students. Initially only patients with chronic diseases of lifestyle, tuberculosis (TB) and HIV/AIDS were seen by community care-workers (CCWs). Through a number of service-learning initiatives in Avian Park, a variety of health services have developed in the community. CCWs have become teachers, community developers and an integral part of the health service team. They enhance access to the residents, community projects and networking within the community.The APSLC improves the opportunities to integrate theoretical academic work with practical application, providing students with a unique opportunity to be involved in healthcare service design and development (as active participants, not observers) based on community-identified needs. University and community collaboration has been purposeful and aims to strengthen community engagement, while up-skilling residents and affording community-based education opportunities for health professions

The role of educational strategies to reverse the inverse performance spiral in academically-isolated rural hospitals

The importance of continuous professional development for health care workers is widely acknowledged, but the identification of optimal implementation strategies remains a challenge, particularly in academically isolated rural areas. We report the results of a qualitative study that evaluated the effect of an educational intervention aimed at rural doctors in the Western Cape Province, South Africa. We also present a conceptual framework for developing best practice educational strategies to reverse the inverse performance spiral in academically isolated rural hospitals. Doctors felt that participation in relevant learning activities improved their competence, increased the levels of job satisfaction they experienced, increased their willingness to stay in a rural environment, and impacted positively on the quality of services provided. However, the success of educational strategies is heavily dependant on the local environment (context), as well as the practical applicability and clinical relevance of the activities (process). Successful educational strategies may help to reverse the inverse performance spiral previously described in academically isolated rural hospitals, however, this requires effective local leadership that creates a positive learning environment and supports clinically relevant learning activities. The study findings also indicate the need for health care providers and institutions of higher education to join forces to improve the quality of rural health care. South African Family Practice Vol. 49 (7) 2007: pp. 1

Geographic range extension of Speke's Hinge-back Tortoise Kinixys spekii Gray, 1863

Kinixys spekii has a wide distribution range across sub-Saharan Africa, having been reported from Angola, Botswana, Burundi, the Democratic Republic of the Congo, eSwatini, Kenya, Malawi, Mozambique, Namibia, South Africa, Tanzania, Zambia, and Zimbabwe. Kinixys spekii inhabits savannah and dry bushveld habitats and was previously considered an inland species. However, recent records suggest a more extensive geographical distribution. Here, we provide genetically verifed records for Angola, South Africa, and Mozambique, and discuss reliable sightings for Rwanda. These new records extend the range signifcantly to the east and west, and provide evidence for the occurrence of this species along the coast of the Indian Ocean in South Africa and Mozambique.© 2019 Ihlow et al. This is an open access article distributed under the terms of the Creative Commons Attribution License [Attribution 4.0 International (CC BY 4.0): https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The official and authorized publication credit sources, which will be duly enforced, are as follows: offcial journal title Amphibian & Reptile Conservation; official journal website: amphibian-reptile-conservation.org

A surrogate model for the economic evaluation of renewable hydrogen production from biomass feedstocks via supercritical water gasification

Supercritical water gasification is a promising technology for renewable hydrogen production from high moisture content biomass. This work produces a machine learning surrogate model to predict the Levelised Cost of Hydrogen over a range of biomass compositions, processing capacities, and geographic locations. The model is published to facilitate early-stage economic analysis (doi.org/10.6084/m9.figshare.22811066). A process simulation using the Gibbs reactor provided the training data using 40 biomass compositions, five processing capacities (10–200 m3/h), and three geographic locations (China, Brazil, UK). The levelised costs ranged between 3.81 and 18.72 $/kgH2 across the considered parameter combinations. Heat and electricity integration resulted in low process emissions averaging 0.46 kgCO2eq/GJH2 (China and Brazil), and 0.37 kgCO2eq/GJH2 (UK). Artificial neural networks were most accurate when compared to random forests and support vector regression for the surrogate model during cross-validation, achieving an accuracy of MAPE: 0.99 on the test set

A Systematic Review of the Critical Factors for Success of Mobile Learning in Higher Education (University Students\u27 Perspective)

The phenomenon of the use of a mobile learning (m-Learning) platform in educational institutions is slowly gaining momentum. However, the enthusiasm with which mobile phones have been welcomed into every aspect of our lives is not yet apparent in the educational sector. To understand the reason, it is important to understand user expectations of the system. This article documents a systematic review of existing studies to find the success factors for effective m-Learning. Our systematic review collates results from 30 studies conducted in 17 countries, where 13 critical success factors were found to strongly impact m-Learning implementation. Using these results within the framework of the diffusion of innovation model for innovation adoption and the critical success factors together help us see what aspects of the innovation decision process are the likely causes of the reduced take-up of m-Learning by university students

Accurate ab initio spin densities

We present an approach for the calculation of spin density distributions for molecules that require very large active spaces for a qualitatively correct description of their electronic structure. Our approach is based on the density-matrix renormalization group (DMRG) algorithm to calculate the spin density matrix elements as basic quantity for the spatially resolved spin density distribution. The spin density matrix elements are directly determined from the second-quantized elementary operators optimized by the DMRG algorithm. As an analytic convergence criterion for the spin density distribution, we employ our recently developed sampling-reconstruction scheme [J. Chem. Phys. 2011, 134, 224101] to build an accurate complete-active-space configuration-interaction (CASCI) wave function from the optimized matrix product states. The spin density matrix elements can then also be determined as an expectation value employing the reconstructed wave function expansion. Furthermore, the explicit reconstruction of a CASCI-type wave function provides insights into chemically interesting features of the molecule under study such as the distribution of $\alpha$- and $\beta$-electrons in terms of Slater determinants, CI coefficients, and natural orbitals. The methodology is applied to an iron nitrosyl complex which we have identified as a challenging system for standard approaches [J. Chem. Theory Comput. 2011, 7, 2740].Comment: 37 pages, 13 figure

Isothermal vapor-liquid equilibrium data for the 1,1,2,2-tetrafluoroethene + 1,1,2,3,3,3-hexafluoroprop-1-ene binary system : measurement and modeling from (248 to 283) K

Isothermal vapor−liquid equilibrium data are presented for the 1,1,2,2-tetrafluoroethylene and 1,1,2,3,3,3-hexafluoroprop-1-ene binary system at (248.14, 263.01, and 282.89) K, with pressures ranging from (0.12 to 2.35) MPa. An apparatus based on the “static−analytic” method, equipped with a movable rapid online sampler−injector (ROLSI), was used to undertake the measurements. The combined expanded uncertainties are estimated at 0.11 K, 4 kPa, and 0.012 and 0.009 for the temperature, pressure, and the equilibrium liquid and vapor mole fractions, respectively. The experimental data were correlated with the Peng−Robinson equation of state using the Mathias −Copeman α function, together with the Wong−Sandler mixing rule utilizing the nonrandom two-liquid activity coefficient model.National Research Foundation of South Africa under the South African Research Chair Initiative of the Department of Science and Technology.http://pubs.acs.org/loi/jceaaxhb201

Isothermal vapor-liquid equilibrium data for the 1,1,2,3,3,3-hexafluoroprop-1-ene +1,1,2,2,3,3,4,4-octafluorocyclobutane binary system : measurement and modeling from (292 to 352) K and pressures up to 2.6 Mpa

Isothermal vapor–liquid equilibrium data are presented for the 1,1,2,2-tetrafluoroethylene and 1,1,2,3,3,3-hexafluoroprop-1-ene binary system at (248.14, 263.01, and 282.89) K, with pressures ranging from (0.12 to 2.35) MPa. An apparatus based on the “static–analytic” method, equipped with a movable rapid online sampler–injector (ROLSI), was used to undertake the measurements. The combined expanded uncertainties are estimated at 0.11 K, 4 kPa, and 0.012 and 0.009 for the temperature, pressure, and the equilibrium liquid and vapor mole fractions, respectively. The experimental data were correlated with the Peng–Robinson equation of state using the Mathias–Copeman α function, together with the Wong–Sandler mixing rule utilizing the nonrandom two-liquid activity coefficient model.National Research Foundation of South Africa under the South African Research Chair Initiative of the Department of Science and Technology.http://pubs.acs.org/loi/jceaax2016-03-31hb201