Higher Level Of Description Research Articles

TRACER STUDY ON THE EMPLOYABILITY OF ELEMENTARY EDUCATION GRADUATES FROM ACADEMIC YEAR 2019 TO 2023

Tracer study is used to determine the needs for improvement of a program in colleges and university by measuring the employability and the effectivity of the quality education provided by the institution to its graduates. This tracer study aims to determine the employment rate and status of graduates from 2019 to 2023 of the program Bachelor in Elementary Education – Generalist of a local college in Kapalong, Davao del Norte. The study used a descriptive method with a total number of 172 respondents and was conducted online using Google Forms. The result of the tracer study reveals that the employment rate of the graduates is 51.16% in which 30.81% practiced the teaching profession while 20.35% are in non-teaching field. The survey also revealed that 22.67% of the employed graduates earned within Php21,000 to Php30,000 per month, and 20.93% have secured their first job within 4 to 8 months. Attitude to work, quality education provision, and skills and abilities development both obtained a very high level of description which signifies that these are always manifested by the graduates. Thus, it is recommended that the institution should improve its partnerships with local industry partners and community linkages and establish graduates and employability coordinator to trace and help graduates informed for more opportunities for work. KEYWORDS: tracer study, elementary education, employability, teacher education

Multi-scale random walk models for reactive transport processes in fracture-matrix systems

Random walk methods are particularly well suited for modeling (anomalous) transport processes in complex systems, from heterogeneous porous domains to fractured rocks. Taking full advantage of their multi-scale attributes, these methods can be integrated into multi-scale modeling strategies where they are used for (i) performing small-scale simulations with a high level of description of the heterogeneities, (ii) defining statistical functions that describe these heterogeneities at a larger scale, and (iii) providing upscaled descriptions of the processes while taking into account the impact of the small-scale heterogeneities. In this work, we define such a strategy considering (i) structural heterogeneities with heterogeneous porosity fields incorporated into fracture-matrix systems and (ii) the reactivity of the system with chemical reactions that are not restricted to linear first-order reactions as it is the case in existing upscaled formulations. To this end, we develop two new modeling methods: the Reactive-Time Domain Random Walk (R-TDRW) and Upscaled Reactive TDRW (UR-TDRW) approaches at small and large scale, respectively. The numerical methods and multi-scale strategy are presented with a general formulation and applied to single-species transport and reaction in fracture-matrix systems. We analyze the impact of different levels of structural heterogeneities, and the impact of the reactivity, on the breakthrough curves computed at both scales and on the statistical functions that are used in the multi-scale strategy. This strategy is validated by demonstrating the good agreement between the results obtained at different scales, showing promising applications for future work in large-scale fracture networks.

Special-Science Counterfactuals

AbstractOn the standard analysis, a counterfactual conditional such as “If P had been the case, then Q would have been the case” is true in the actual world if, in all nearest possible worlds in which its antecedent (P) is true, its consequent (Q) is also true. Despite its elegance, this analysis faces a difficulty if the laws of nature are deterministic. Then the antecedent could not have been true, given prior conditions. So, it is unclear what the relevant “nearest possible worlds” are. David Lewis suggested that they are ones in which a local breach of the laws occurred: a “small miracle.” Others have suggested that they are ones in which the initial conditions were different (“backtracking”). I propose another response. It builds on the idea that the special sciences, where counterfactual reasoning is most common, operate at a higher level of description from fundamental physics, and that the world may behave indeterministically at higher levels even if it behaves deterministically at the fundamental physical one. The challenge from determinism can then be bypassed for many special-science counterfactuals.

Validation Strategy of Reduced-Order Two-Fluid Flow Models Based on a Hierarchy of Direct Numerical Simulations

Whereas direct numerical simulation (DNS) have reached a high level of description in the field of atomization processes, they are not yet able to cope with industrial needs since they lack resolution and are too costly. Predictive simulations relying on reduced order modeling have become mandatory for applications ranging from cryotechnic to aeronautic combustion chamber liquid injection. Two-fluid models provide a good basis in order to conduct such simulations, even if recent advances allow to refine subscale modeling using geometrical variables in order to reach a unified model including separate phases and disperse phase descriptions based on high order moment methods. The simulation of such models has to rely on dedicated numerical methods and still lacks assessment of its predictive capabilities. The present paper constitutes a building block of the investigation of a hierarchy of test-cases designed to be amenable to DNS while close enough to industrial configurations, for which we propose a comparison of two-fluid compressible simulations with DNS data-bases. We focus in the present contribution on an air-assisted water atomization using a planar liquid sheet injector. Qualitative and quantitative comparisons with incompressible DNS allow us to identify and analyze strength and weaknesses of the reduced-order modeling and numerical approach in this specific configuration and set a framework for more refined models since they already provide a very interesting level of comparison on averaged quantities.

Same action, different level: Descriptions of perceived or predicted actions depend on preceding temporal gaps in event streams.

Events and activities consist not only of sequences of individual actions, but also they form hierarchies comprising chains of low-level actions grouped together to form higher level activities. Therefore, observers face the task of not only segmenting a continuous event stream into discrete units, but also processing these units on an appropriate level of aggregation. In 3 experiments, we show that for events observed in an incomplete, piecemeal manner, the temporal extension of event gaps influences the level of hierarchy at which an observer processes the presented event (Experiments 1a and 1b) and that the level of hierarchy is also transferred to an anticipated subsequent event (Experiment 2). Participants viewed film clips showing everyday activities with short or long temporal gaps between the successive shots presenting different aspects of the same activity. The participants' levels of processing were captured via the cued recall of their descriptions of what they had seen in the film clip or via the formulations they used when describing what they expected to happen next. Our findings suggest an extended model of event cognition: Viewers aim to represent events continuously and therefore extrapolate in the case of gaps by shifting to higher levels of description. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A new methodology based on sensitivity analysis to simplify the recalibration of functional-structural plant models in new conditions.

Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.

On Macrostates in Complex Multi-Scale Systems

A characteristic feature of complex systems is their deep structure, meaning that the definition of their states and observables depends on the level, or the scale, at which the system is considered. This scale dependence is reflected in the distinction of micro- and macro-states, referring to lower and higher levels of description. There are several conceptual and formal frameworks to address the relation between them. Here, we focus on an approach in which macrostates are contextually emergent from (rather than fully reducible to) microstates and can be constructed by contextual partitions of the space of microstates. We discuss criteria for the stability of such partitions, in particular under the microstate dynamics, and outline some examples. Finally, we address the question of how macrostates arising from stable partitions can be identified as relevant or meaningful.

Creating virtual exhibition rooms from emigration digital archives

In the context of a research and development project, the authors are cooperating with a municipal archive aiming at supporting the preservation of physical documents and at facilitating the information extraction and dissemination. Saving individual records, such as emigration documentation, it is important for end-users, and History or Social Sciences Researchers as they can know more about each individual and they can learn about society. Using the Internet resources, the information stored in digital format may be brought forward on web pages displaying it to the end-users and enabling them to learn and interact with the available information, creating knowledge. The long-term goal is to automatize the creation of these Web sites, so-called learning spaces, from high-level descriptions. This paper discusses the creation of virtual exhibition rooms (VER) from ontological descriptions of the emigration digital archives. It presents the data retrieved from documents and stored in a digital repository, and then proposes the use of the CIDOC Conceptual Reference Model (CIDOC-CRM) ontology (a standard in the area of museums knowledge representation). That ontology will provide a higher level of description, where concepts are enhanced (instead of data items and low-level relationships holding among them). SPARQL Protocol and RDF Query Language (SPARQL) is then used to query the Resource Description Framework (RDF) triple-storage; eXtensible Stylesheet Language Transformations (XSLT) and Cascading Style Sheets (CSS) allow to create templates that are used to automatically build the VER that is a conceptual navigator over the repository.

Identifying the Importance of Perceptual Cycle Concepts during Critical Decision making in the Cockpit

This paper applies a taxonomy based on the Perceptual Cycle Model (PCM) to analyse aeronautical critical decision making (ACDM) data. The PCM provides a process-oriented explanation of decision making, demonstrating how the combination of internally held mental schemata and externally available environmental information interact to produce decisions and actions. However, the PCM only provides a high level of description; previous research has developed a taxonomy based on the high level categories of schema, action and world, in order to increase the explanatory power of the PCM. The taxonomy was applied to analyse twenty ACDM interviews. Sociometric status (a metric of social network analysis) was computed for each concept to establish their relative importance when dealing with a critical incident. It is demonstrated that world-based concepts are more important than schema-based concepts for ACDM. However, limitations with the methodology may have influenced the results and these are discussed, along with potential methodological developments to enhance data collection of this nature.

A review on the characterization of signals and systems by power law distributions

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.

Choosing between the long and short informational routes to psychological explanation

Following recent work by Don Ross (Ross, 2000; Ross & Spurrett, 2004), I contrast the influential theories of Daniel Dennett and Paul Churchland in information-theoretic terms. Dennett makes much of the fact that the morphological shorthand which emerges before a witness as she looks upon cohesive aggregates of matter commands some measure of predictive power. This, for him, speaks against eliminating recourse to an intentional vocabulary. By contrast, the eliminative materialism defended by Churchland does not gloss such informational compressibility as an explanatory desideratum, and thus regards the informational noise which accrues at higher levels of description as patently unacceptable. Yet, since it is unlikely, as Ross, Ladyman, and Collier (2007) have recently suggested, that anything remains once we subtract the appeal to patterns, I argue that the ubiquity of informational compression in scientific explanation seriously undermines the claim that talk of the mental could be eliminated.

Synthesis of CMOS analog circuit VHDL-AMS descriptions using parameterizable macromodels

SUMMARY Some of the advantages of very high speed integrated circuits hardware description language for analog and mixed signal (VHDL-AMS) when used to describe analog circuits are its modeling capability and the speed of simulations, in comparison with device level simulators. However, VHDL-AMS does not allow one to complete in a systematic way the synthesis of an analog circuit from higher description levels of the design hierarchy to lower ones. This is due to the lack of CAD tools and methods for analog circuits, contrary to the situation of pure digital circuits. This is a serious drawback because it is an obstacle to its success in analog CAD tools. The proposal described in this article, on the basis of the use of parameterizable macromodels, allows a systematic and rapid translation from a VHDL-AMS description of analog circuits to schematic level-sized descriptions. Copyright © 2011 John Wiley & Sons, Ltd.

A Model for Plant Invasions: the Role of Distributed Generation Times

An analytical model consisting of adult plants and two types of seeds (unripe and mature) is considered and successfully tested using experimental data available for some invasive weeds (Echium plantagineum, Cytisus scoparius, Carduus nutans andCarduus acanthoides) from their native and exotic ranges. The model accounts for probability distribution functions (pdfs) for times of germination, growth, death and dispersal on two dimensions, so the general life-cycle of individuals is considered with high level of description. Our work provides for the first time, for a model containing all that life-cycle information, explicit relationship conditions for the invasive success and expressions for the speed of invasive fronts, which can be useful tools for invasions assessment. The expressions derived allow us to prove that the different phenotypes showed by the weeds in their native (exotic) ranges can explain their corresponding non-invasive (invasive) behavior.

Petri net modelling of gene regulation of the Duchenne muscular dystrophy

Searching for therapeutic strategies for Duchenne muscular dystrophy, it is of great interest to understand the responsible molecular pathways down-stream of dystrophin completely. For this reason we have performed real-time PCR experiments to compare mRNA expression levels of relevant genes in tissues of affected patients and controls. To bring experimental data in context with the underlying pathway theoretical models are needed. Modelling of biological processes in the cell at higher description levels is still an open problem in the field of systems biology. In this paper, a new application of Petri net theory is presented to model gene regulatory processes of Duchenne muscular dystrophy. We have developed a Petri net model, which is based mainly on own experimental and literature data. We distinguish between up- and down-regulated states of gene expression. The analysis of the model comprises the computation of structural and dynamic properties with focus on a thorough T-invariant analysis, including clustering techniques and the decomposition of the network into maximal common transition sets (MCT-sets), which can be interpreted as functionally related building blocks. All possible pathways, which reflect the complex net behaviour in dependence of different gene expression patterns, are discussed. We introduce Mauritius maps of T-invariants, which enable, for example, theoretical knockout analysis. The resulted model serves as basis for a better understanding of pathological processes, and thereby for planning next experimental steps in searching for new therapeutic possibilities. Availability: Free availability of the Petri net editor and animator Snoopy and the clustering tool PInA via http://www-dssz.informatik.tu-cottbus.de/∼wwwdssz/. The Petri net models used can be accessed via http://www.tfh-berlin.de/bi/duchenne/.

Microformatos: web 2.0 para el Dublin Core

This paper describes the use of Dublin Core (DC) microformats that allow the DC Metadata Element Set to be marked up in a style commonly applied in web 2.0. Microformats allow the semantic expression inside xhtml pages to be displayed in a manner visible to the user, thereby enabling a high level of description for specific types of resources (business cards, events, etc.). This particular use of DC microformats offers great potential for resource description in general, and is especially suitable for describing bibliographic resources. Also presented in this paper is a simple way for encoding DC in microformats using the Dublin Core Metadata Gen software, as well as an application that allows information included in the microformats to be displayed using the Mozilla Firefox extension, created for this purpose.

Effect of Level of Problem Description on Problem Discovery Rates: Two Case Studies

The primary purpose of this analysis was to investigate the effect of changing the level of description of usability problems on the estimate of the problem discovery rate ( p). A secondary purpose was to describe a method for using p to estimate the number of problems remaining available for discovery given the constraints associated with a particular participant population, application, and set of tasks. The level of problem description influenced estimates of p, and the direction of influence was predictable, with higher levels of description producing higher estimates of p. Practitioners need a level of description that flows easily into recommendations for redesigning products, but to keep usability studies as efficient as possible, practitioners also need to seek a level of description that takes advantage of common patterns in observed usability problems. Managing this tradeoff is only one of the challenges of usability evaluation, but it is an important one.

Some issues related to growth and goal functions for continuum biological systems

The growth of biological tissues is described as the volumic production of mass of so-called germs, considered as potential sites for tissue renewal/resorption. The growth is characterized by a growth transformation gradient. The continuous change of the domain occupied by each germ during growth is analysed, hence, the mechanical balance laws are written considering the additional terms due to the domain variation. The principle of virtual power is then expressed, leading to the balance of momentum, assuming that the power of internal forces originates from both volumic and surfacic potentials. The equilibrium equations of the growing germ split into volumic, surfacic and lineic contributions. Viewing growth as an irreversible phenomenon, the writing of the second principle of thermodynamics for a germ continuously receiving matter due to transport phenomena allows to identify the driving forces linked to growth. In the second part, the growth and evolution are viewed as finding the best configuration of the growing solid in terms of its metric. Thereby, the four-dimensional space–time is structured in the form of isogrowth surfaces, the evolution of growth being described as a motion from one slice to the next. A Lagrangian formalism is established in the space of metric, whereby both the geometrical and physical contents of the growing solid are considered. Adopting this higher level of description, the stationnarity of the total action integral renders the dynamics of the metric field, while the kinematic compatibility condition prescribes its spatial form.

Less Is More in Modeling Large Genetic Networks

Will we ever be able to build predictive models of the complex genetic networks that determine function as well as malfunction of living cells? Studies of small cellular circuits that represent building blocks indicate that there might be a higher level of description that would reduce the vast complexity of genetic network models. In his Perspective, Bornholdt discusses the results reported in the same issue by Brandman et al . who characterize a frequent building block of cellular circuits. Such elements exhibit particularly simple dynamics and the hope is that models of large genetic networks become feasible when based on the dynamics of such simple building blocks.

Second order up-scaling: theory and an exercise with a complex photosynthesis model

Model objectives related to higher levels of description in general require the application of aggregation methods which shorten computation time but preserve the effect of fine scale variability. It is shown that in particular temporal up-scaling problems can be solved through a second order approximation of a statistical expectation operator. For the application of the second order up-scaling method one has to evaluate estimates of second order derivatives of the model functions as well as variances of fluctuating boundary conditions. Here, we propose to calculate second order derivatives on the base of look-up tables, which significantly reduces computational effort. This technique, however, should be used with care since round-offs of the model output largely affect second order terms. In order to obtain values of fine scale variances in external conditions one can simply correlate these with longer-term averages. The correctness of the correlation method is demonstrated for different irradiance and temperature time-series. After a more general derivation, the combination of methods is tested by aggregating a complex photosynthesis model in time. This exercise shows that computation time can be reduced by many orders of magnitude using the combined second order up-scaling technique. Other potentials as well as limitations of look-up tables, second order moment approximations and the statistical representation of daily climate fluctuations are discussed.

Eulerian and Lagrangian statistics in homogeneous stratified flows

The present work follows previous modelling efforts of homogeneous stratified turbulence, using a statistical Eulerian model, with a high level of description of anisotropy, and a kinematic simulation model for computing Lagrangian dispersion properties of turbulence. Here, both approaches are coupled, yielding results for the dispersion of a single passive particle. The first results obtained by our model qualitatively agree well with the one-particle dispersion ones obtained from Large Eddy Simulations of stationary stratified turbulence.