Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt–water mixtures

Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt–water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water–water and water–ion entropies contribute strongly. We show that the water–ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water–water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.

'Boundary Objects' in Archaeological Finds and Environmental Research: Using Bowker and Star's Concept of the 'Boundary Object' to Analyse and Interpret Disparate Archaeological Legacy Data

Is a big data analytical approach viable using archaeological artefact and ecofact data? In particular is it possible to use Bowker and Star's (1999) concept of the 'boundary object' to manage the issues caused by data scale, complexity, diversity and variable information standards when attempting to carry out this kind of research? This paper reviews the theoretical and methodological debates around archaeological big data as they impact upon research into assemblages of artefacts and ecofacts and presents a methodology for the construction and use of a large archaeological database of legacy artefact and ecofact data created as part of the English Landscapes and Identities Project at the University of Oxford.

Making a Difference: Planning for Engaged Participation in Environmental Research

Despite the rapid and accelerating rate of global environmental changes, too often research that has the potential to inform more sustainable futures remains disconnected from the context in which it could be used. Though transdisciplinary approaches (TDA) are known to overcome this disconnect, institutional barriers frequently prevent their deployment. Here we use insights from a qualitative comparative analysis of five case studies to develop a process for helping researchers and funders conceptualize and implement socially engaged research within existing institutional structures. The process we propose is meant to help researchers achieve societal as well as scientific outcomes relatively early in a project, as an end in itself or en route to greater engagement later. If projects that have a strong foundation of dialog and shared power wish to use TDA within current institutional and academic structures, we suggest that they focus on three process-based factors to increase their chances for success: (1) the maturity of relationships within a collaboration, (2) the level of context knowledge present within the collaborative team, and (3) the intensity of the engagement efforts within the project.

Controlling critical mistag-associated false discoveries in metagenetic data

Metagenetic methods are commonplace within ecological and environmental research. One concern with these methods is the phenomenon of critical mistagging, where sequences from one sample are erroneously inferred to have originated from another sample due to errors in the attachment, PCR replication or sequencing of sample-specific dual-index tags. For studies using PCR-based library preparation on large sample sizes, the most cost-effective approach to limiting mistag-associated false detections involves using an unsaturated Latin square dual-indexing design. This allows researchers to estimate mistagging rates during sequencing but the statistical procedures for filtering out detections using this mistag rate have received little attention. We propose a straightforward method to limit mistag-associated false discoveries during metabarcoding applications. We analyzed two Illumina metabarcoding datasets produced using unsaturated Latin square designs to explore the distribution of mistagged sequences across dual-index combinations on a per taxon basis. We tested these data for conformity to the assumptions that 1) mistagging follows a binomial distribution [i.e., X ~ B(n, p)] where p, the probability of a sequence being mistagged, varies minimally across taxa and 2) mistags are distributed uniformly across dual-index combinations. We provide R functions that estimate the 95th percentile of expected mistags per dual-index combination for each taxon under these assumptions. We show that mistagging rates were consistent across taxa within the datasets analyzed and that modelling mistagging as a binomial process with uniform distribution across dual-index combinations enabled robust control of mistag-associated false discoveries. We propose that this method of taxon-specific filtering of detections based on the maximum mistags expected per dual-index combination should be broadly accepted during metagenetic analysis, provided that experimental and control sequence abundances per taxon are strongly correlated. When this assumption is violated, data may be better fit by assuming that the distribution of mistags across combinations follows Poisson characteristics [i.e., X ~ Pois(𝜆)], with 𝜆 empirically estimated from the abundance distribution of mistags among control samples. We provide a second R function for this case, though we have yet to observe such a dataset. Both functions and demonstrations associated with this work are freely available at https://github.com/RTRichar/ModellingCriticalMistags.

Peran Lingkungan Madrasah Dalam Pembentukan Karakter Siswa MIM 2 Slinga Kaligondang Purbalingga

The study, entitled the role of the madrasah environment in the character building of students at MI Muhammadiyah 2 Slinga kaligondang purbalingga has the aim of providing an overview of how the role of the madrasah environment can shape the character of MI Muhammadiyah 2 Slinga students. This paper is a deductive paper, the result of research with environmental research subjects at MI Muhammadiyah 2 Slinga. The results showed that the character of the students at MIMuhammadiyah 2 Slinga could be shaped by the interaction between students and stakeholders in the madrasah environment and the situation in the madrasah environment.