Ordinal Trees and Random Forests: Score-Free Recursive Partitioning and Improved Ensembles

Existing ordinal trees and random forests typically use scores that are assigned to the ordered categories, which implies that a higher scale level is used. Versions of ordinal trees are proposed that take the scale level seriously and avoid the assignment of artificial scores. The construction principle is based on an investigation of the binary models that are implicitly used in parametric ordinal regression. These building blocks can be fitted by trees and combined in a similar way as in parametric models. The obtained trees use the ordinal scale level only. Since binary trees and random forests are constituent elements of the proposed trees, one can exploit the wide range of binary trees that have already been developed. A further topic is the potentially poor performance of random forests, which seems to have been neglected in the literature. Ensembles that include parametric models are proposed to obtain prediction methods that tend to perform well in a wide range of settings. The performance of the methods is evaluated empirically by using several data sets.

Measuring Mindfulness: Assessing the Utility of the FFMQ in the Older Veterans With Dementia and Their Caregivers

Mindfulness is increasingly popular as a low cost, convenient, and accessible way to address mental health and chronic health conditions. Despite its popularity, best practices in measuring mindfulness in clinical settings and intervention research are still being defined. The Five Facet Mindfulness Questionnaire (FFMQ-15) measures mindfulness traits; however, its use has been limited in older adults, those with dementia, and caregivers. Method: Caregivers (N=82) and veterans with dementia (N=62) enrolled in a randomized pilot intervention study completed the 15-item FFMQ at baseline, 6-month, and 12-month assessments. Veterans were mostly male (98%), White/Caucasian (65%), and living with a partner/spouse (79%). Caregivers (M=65 years old) were mostly female (89%) and White/Caucasian (66%). FFMQ response options were simplified to a 3-point Likert-scale for individuals with dementia (0=rarely true to 2=often true). Results Internal consistency statistics (Cronbach’s alphas) at the scale-level were acceptable among caregivers at baseline and 6-months (.71-.75) but questionably reliable at 12-months (.59, N=46). For individuals with dementia, the simplified version of the FFMQ (with 3 response options) achieved questionable reliability at baseline (.57, N=56) and 6-months (.67, N=32), but improved to acceptable at 12-month assessments (.75, N=15), after significant attrition. Conclusion Researchers should apply caution when using the FFMQ total score with caregivers and those with cognitive impairments. Though simplified response options eased administration, utility of the tool may be limited in those who are more impaired. Before mindfulness measures can be used meaningfully, reliability of available tools like the FFMQ-15 need to be examined in more diverse samples.

GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction

Metabolic network models are increasingly being used in health care and industry. As a consequence, many tools have been released to automate their reconstruction process de novo. In order to enable gene deletion simulations and integration of gene expression data, these networks must include gene-protein-reaction (GPR) rules, which describe with a Boolean logic relationships between the gene products (e.g., enzyme isoforms or subunits) associated with the catalysis of a given reaction. Nevertheless, the reconstruction of GPRs still remains a largely manual and time consuming process. Aiming at fully automating the reconstruction process of GPRs for any organism, we propose the open-source python-based framework GPRuler. By mining text and data from 9 different biological databases, GPRuler can reconstruct GPRs starting either from just the name of the target organism or from an existing metabolic model. The performance of the developed tool is evaluated at small-scale level for a manually curated metabolic model, and at genome-scale level for three metabolic models related to Homo sapiens and Saccharomyces cerevisiae organisms. By exploiting these models as benchmarks, the proposed tool shown its ability to reproduce the original GPR rules with a high level of accuracy. In all the tested scenarios, after a manual investigation of the mismatches between the rules proposed by GPRuler and the original ones, the proposed approach revealed to be in many cases more accurate than the original models. By complementing existing tools for metabolic network reconstruction with the possibility to reconstruct GPRs quickly and with a few resources, GPRuler paves the way to the study of context-specific metabolic networks, representing the active portion of the complete network in given conditions, for organisms of industrial or biomedical interest that have not been characterized metabolically yet.

A Survey of Ontologies and Their Applications in e-Learning Environments

Ontology technology has been investigated in a wide range of areas and is currently being utilized in many fields. In the e-learning context, many studies have used ontology to address problems such as the interoperability in learning objects, modeling and enriching learning resources, and personalizing educational content recommendations. We systematically reviewed research on ontology for e-learning from 2008 to 2020. The review was guided by 3 research questions: “How is ontology used for knowledge modeling in the context of e-learning?”, “What are the design principles, building methods, scale, level of semantic richness, and evaluation of current educational ontologies?”, and “What are the various ontology-based applications for e-learning?” We classified current educational ontologies into 6 types and analyzed them by 5 measures: design methodology, building routine, scale of ontology, level of semantic richness, and ontology evaluation. Furthermore, we reviewed 4 types of ontology-based e-learning applications and systems. The observations obtained from this survey can benefit researchers in this area and help to guide future research.

The Role of CO2 in Carbonate Acidizing at the Field Scale – A Multi-Phase Perspective

Most lab-scale acidizing experiments are performed in core samples with 100% water saturation conditions and at pore pressures around 1100 psi. However, this is seldom the case on the field, where different saturation conditions exist with high temperature and pressure conditions. Carbon-di-Oxide (CO2), a by-product evolved during the acidizing process, is long thought to behave inertly during the acidizing process. Recent investigations reveal that the presence of CO2 dynamically changes the behavior of wormhole patterns and acid efficiency. A compositional simulation technique was adopted to understand the process thoroughly. A validated compositional numerical model capable of replicating acidizing experiments at the core-scale level, in fully aqueous environments described in published literature was utilized in this study. The numerical model was extended to a three-phase environment and applied at the field scale level to monitor and evaluate the impacts of evolved CO2 during the carbonate acidizing processes. Lessons learned from the lab-scale were tested at the field-scale scenario via a numerical model with radial coordinates. Contrary to popular belief, high pore pressures of 1,000 psi and above are not sufficient to keep all the evolved CO2 in solution. The presence of CO2 as a separate phase hinders acid efficiency. The reach or extent of the evolved CO2 is shown to exist only near the damage zone and seldom penetrates the reservoir matrix. Based on the field scale model's predictions, this study warrants conducting acidizing experiments at the laboratory level, at precisely similar pressure, temperature, and salinity conditions faced in the near-wellbore region, and urges the application of compositional modeling techniques to account for CO2 evolution, while studying and predicting matrix acidizing jobs.

5/7-POINT “LIKERT SCALES” AREN’T ALWAYS THE BEST OPTION Their validity is undermined by lack of reliability, response style bias, long completion times and limitations to permissible statistical procedures

Some research methods are used by default. Even if they undermine the validity of conclusions, authors no longer justify the use of default approaches and reviewers no longer query them. One such default is the use of bipolar ordinal 5/7-point survey answer formats, often incorrectly referred to as 5/7-point “Likert scales”. This Viewpoint argues that default answer formats should be replaced by thorough assessments of the benefit-to-cost ratio of alternative answer formats for every survey question asked. Benefits of answer formats include enabling respondents to meaningfully express themselves, while keeping respondent burden low. Costs include reducing data quality by introducing bias or over-burdening respondents, or by collecting data at a scale level that limits permissible statistical procedures.

Consciousness as a new form of the matter’s state

The article discusses the physical model of the implicative form of Consciousness in the form of a holographic wave matrix, for which the material basis is directly the phase environment that fills the entire Space. It is shown that a similar form of Consciousness that exists outside the human brain can be represented as a kind of software shell that controls all forms of matter by implementing a fractal cyclic iterative algorithm. The condition for the completion of each iterative cycle at each scale level is the observance of the laws of symmetry that ensure the survival of the object in the process of copying-incarnation.

Nanotechnologies of Strength Control of Materials

The strength of materials is determined by their atomic molecular structure and the process of decay of atomic molecular bonds, which must be taken into account when optimizing materials strength control technologies. The fracture photomicrograph of metal microdamage of welded joint at various moments of time, a multilevel model of flow of acoustic emission signals of materials are presented. The physical meaning, the scale level of parameters included in the model are revealed. The structure of the mathematical model of the flow of AE signals with components of its informative elements of different scale level by strength characteristics of structural materials and resource of technical objects is shown. The multilevel model of the AE signal flow is hierarchically structured, obtained by generalizing deterministic-statistical variability. It describes the process of randomly recording deterministic accumulated damages in the material both before and after the formation of a crack at the stage of waiting for its next leap. It is shown that the proposed nanotechnology of strength control of materials is reduced to non-destructive determination of parameters of prognostic homogeneous destruction, identification of which is based on multilevel modeling of time dependence of micro-crack formation, formulation of criterion of strength homogeneity, registration of AE parameters related to the model of a specific product, which can be automated processing of registration results and determination of universal strength nanoconstants from already published reference data of fatigue tests of standard material samples.