Real Model Research Articles

SEEING THE INVISIBLE. ANALYTICAL DRAWINGS BY CONSTRUCTION HISTORY PIONEERS. RESEARCH FIELD OVERVIEW

Introduction: The history of construction is a discipline that began to take shape in the mid-18th century and throughout the 19th century. We as researchers need to pay particular attention to how drawing facilitated progress during this period. This article attempts to provide an overview of the above, which is currently lacking. Methods: In this study, two lines of investigation intersect: the history of construction and the history of drawing, specifically drawing for scientific and technical representation. The main goal is to identify the sources (authors, lines of investigation) relevant to this field, as well as to characterize the role of drawing in the authors’ work, and to describe the spread of drawing as nonverbal thinking. Results: We have identified a number of relevant authors, described their lines of research, and listed the functions fulfilled by drawing in each case. The functions include: hypothesizing about hidden structures, visualizing the construction processes, and providing a virtual definition for elements that make up a vault. We also review how some drawings acted as a visual model of the constructive reality, or how parallel drawings served as a reflection of the different buildings’ size and scale. Discussion: This overview adjusts some points of reference for a general picture. For having a complete understanding of the subject, it will be necessary to identify more sources and to extend the geographical scope of this search in the future. There is still much research to be done on the spread of the drawings in question.

A Phenology Model for Simulating Oobius agrili (Hymenoptera: Encyrtidae) Seasonal Voltinism and Synchrony With Emerald Ash Borer Oviposition.

In North America, the emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), continues to spread, and its egg parasitoid, Oobius agrili Zhang and Huang (Hymenoptera: Encyrtidae), is being released for emerald ash borer biocontrol well beyond their endemic climatic ranges in China. We developed a multiple cohort rate summation model to simulate O. agrili F0, F1, and F2 generations, and emerald ash borer oviposition for examining host-parasitoid synchrony across a north-south gradient from Duluth, MN (latitude 46.8369, longitude -92.1833) to Shreveport, LA (latitude 32.4469, longitude -93.8242). Temporal occurrences of critical day length for O. agrili diapause induction were integrated into the model. We used O. agrili and emerald ash borer trapping data from south central and northwestern Lower Michigan for model validation. Simulations demonstrated that 1) F0 adult emergence consistently occurred 2-5 d before emerald ash borer oviposition began; 2) F1 adult emergence was most synchronized with peak emerald ash borer oviposition compared with other generations; and 3) emerald ash borer oviposition was complete, or near so, when F2 adult emergence was predicted across the north-south gradient. Comparison of O. agrili trap captures with model simulations demonstrated that primarily two adult O. agrili generations (F0 and F1) emerged per year in Michigan and almost all F2 larvae entered diapause despite day lengths longer than critical day length in south central Michigan. Critical day length varied temporally across the north-south gradient during emergence of O. agrili generations. Determining day lengths perceived by O. agrili larvae in the field should improve model realism for examining spatiotemporal variation in O. agrili population dynamics.

Comparison of error tree analysis and TRIPOD BETA in accident analysis of a power plant industry using hierarchical analysis

Introduction: Due to the importance and necessity of accident analysis, it is necessary to use the proper technique for precise accident analysis and provide corrective and preventive measures to prevent an accident's recurrence. Materials and Methods: In this descriptive-analytical paper, the most important criteria for investigating and selecting accident investigation and analysis techniques and selecting the best accident analysis method were identified in critical industrial accidents in the construction phase, were identified and analyzed. In this study, the most important criteria for selecting an accident analysis method were identified using previous research and gathering expert opinions. Then, two critical power plant accidents were analyzed using TRIPOD BETA and FTA accident analysis methods. Then the pairwise comparisons matrix was formed based on the strengths and weaknesses of the models. Finally, the prioritization of these two methods was done using the hierarchical analysis decision-making method. Results: In this paper, seven key factors, model realism, model descriptive, systematic modeling, run time, required training courses, ability to quantify, and visibility of events, were identified as the most important criteria for selecting an incident analysis method. Conclusion: The TRIPOD BETA method has been introduced as an optimal method for investigating specific events due to its capabilities.

A grey seasonal least square support vector regression model for time series forecasting

Seasonality is a fundamental and common property of most time series in the real world. In this article, we propose a grey seasonal least square support vector regression, abbreviated as GSLSSVR, by combining the dummy variables, framework of the LSSVR model, and grey accumulation generation operation to reflect seasonal variations in functional forms, variables, and parameters. Our framework provides an intuitive and simple set up of arbitrary seasonality in any feature, which considerably enhances model realism. Further, the regulation method is introduced to increase the stability and generalization of the newly proposed model. Using the Lagrange multipliers algorithm, the model parameters are obtained by solving a set of linear equations. In addition, the last block evaluation is developed, which has the same size in the validating and testing data, to identify the hyperparameters of this novel model. For verification purposes, four real seasonal time series having various characteristics are employed in this work, including quarterly electricity consumption, monthly cargo throughput, monthly crude oil production, and monthly gasoline production in China. Experimental results demonstrate that our proposed model can provide for analysis of seasonal regulatory measures and is validated to be superior to other prevalent forecasting models referring to the SGM(1,1), SFGM(1,1), LSSVR, SARIMA-GARCH, and BPNN models. Ultimately, our model is highly recommended for addressing issues with periodic and nonlinear features.

A modeling exercise to show why population models should incorporate distinct life histories of dispersers

AbstractDispersal is an important form of movement influencing population dynamics, species distribution and gene flow between populations. In population models, dispersal is often included in a simplified manner by removing a random proportion of the population. Many ecologists now argue that models should be formulated at the level of individuals instead of the population level. To fully understand the effects of dispersal on natural systems, it is therefore necessary to incorporate individual‐level differences in dispersal behavior in population models. Here, we parameterized an integral projection model, which allows for studying how individual life histories determine population‐level processes, using bulb mites, Rhizoglyphus robini, to assess to what extent dispersal expression (frequency of individuals in the dispersal stage) and dispersal probability affect the proportion of successful dispersers and natal population growth rate. We find that allowing for life‐history differences between resident phenotypes and disperser phenotypes shows that multiple combinations of dispersal probability and dispersal expression can produce the same proportion of leaving individuals. Additionally, a given proportion of successful dispersing individuals result in different natal population growth rates. The results highlight that dispersal life histories, and the frequency with which disperser phenotypes occur in the natal population, significantly affect population‐level processes. Thus, biological realism of dispersal population models can be increased by incorporating the typically observed life‐history differences between resident phenotypes and disperser phenotypes, and we here present a methodology to do so.

ICT competence formation model of a future primary school teacher

Problem and purpose. The article is devoted to the problem of the formation of ICT competence in future primary school teachers. In the context of global mass communication, the most valuable resource today is the ability to analyze, systematize, and interpret information. Global informatization naturally affects the education process and the main task of the education system is to identify current trends in the development of society and introduce pedagogical technologies into the educational process that form positive experience and reflect modern social changes, leading the educational process into an ordered, controlled system. The aim of the study is to find effective ways of manifesting information activities, building a model that promotes the development of ICT competence in future primary school teachers by means of mathematical cycle disciplines. Methodology. During the study, an analysis of approaches to the creation of educational models was carried out, ways of developing ICT competence of future primary school teachers by means of mathematical cycle disciplines were revealed. The main conceptual idea of the model, contributing to the solution of the didactic problems (epistemological, axiological, praxeological, professional-personal, communicative), is the reflection of mathematics in the information field as an instrument of humanization of the modern information society and personality. The basic aspects of fragmented subject modeling of pedagogical reality is the application of an integrated approach to the conceptual, criteria and quantification of the model. Results. A model for the development of ICT competence of future primary school teachers has been developed. The technological component of the model is disclosed, the criterion component of which is represented by the matrix of conjugation of levels (elementary, sufficient, advanced) and components of ICT competency (epistemological, axiological, praxiological, professional-personal, communicative). Each component is revealed through the prism of knowledge, skills and experience. Conclusion. The developed model for the development of ICT competence of future primary school teachers by means of the mathematical cycle disciplines justifies itself in practice and needs further research and quantitative analysis.

The Assessment of Organic Matter Young's Modulus Distribution With Depositional Environment and Maturity

AbstractQuantification of risk to seal integrity in CCS, or gas extraction from hydraulic fracturing, is directly affected by the accessibility of organic pores within organic rich mudrocks. Knowledge of the host organic matter's mechanical properties, which are influenced by depositional environment and thermal maturity, are required to reduce operational risk. In this study we address the effect of both depositional environment and maturity on organic matter Young's modulus by means of Atomic Force Microscopy Quantitative ImagingTM, which is a nondestructive technique capable of nanomechanical measurements. Shales from varying marine depositional environments covering kerogen Types II (Barnett), IIS (Tarfaya), and II/III (Eagle Ford/ Bowland) are analyzed to capture variance in organic matter. The findings show organic matter has a Young's modulus ranging between 0.1 and 24 GPa. These marine shales have a bimodal distribution of Young's modulus to some degree, with peaks at between 3–10 and 19–24 GPa. These shales exhibit a trend with maturity, whereby Young's modulus values of <10 GPa are dominant in immature Tarfaya shale, becoming similar to the proportion of values above 15 GPa within the oil window, before the stiffer values dominate into the gas window. These peaks most likely represent soft heterogeneous aliphatic rich kerogen and stiff ordered aromatic rich kerogen, evidenced by the increase in the stiffer component with maturity and correlated with 13C NMR spectrocopy. These findings enable increased realism in microscale geomechanical fracture tip propagation models and may allow direct comparison between Young's modulus and Rock‐Eval parameters.

Image transformation in the process of creative tasks solving by senior pupils

The conception of V. O. Molyako regarding the mental activity processes strategic organization is analyzed. The main components of the problem solving starting determinants are formulated, as well as the dominant function of strategy in the mental search for a problem solution. The general scheme of images transformation, arising during the construction, is considered. The role of problem understanding in the prototype formation is substantiated. Attention is focused on the functioning of the proto-prototype as a figurative-conceptual determinant of the prototype, as well as the role of the prototype in the formation of the reference image. The analysis of the considered problem is carried out in the most general coordinate system – from the standpoint of consistency, integrity, human interaction with the world. After all, the solution of the generalizing modern psychological knowledge problem is associated with the construction of an integral image of a person who cognizes reality and tries to create an adequate image of the researched objects, and, consequently, with the need to develop multi-vector and at the same time systemic models of mental reality. The expediency of tasks for free design implementation is substantiated in order to study the image transformation in the process of creative problems solving by senior pupils. The ratio of structural, functional and structural-functional constructing manifestations in the task solving search is analyzed. Attention is focused on the complexity of constructing the desired structure by means of structural and functional constructing. The task solutions performed using the strategies of analogy and combination are considered. The ratio of the different constructing tactics implementation frequency in order to build a solution project is given. The influence of mental mutagenesis on the success of the creative thinking activity of senior pupils is shown. It has been established that reference images in the task solving process for free construction are created and function with the dominance of personally significant information structures from the sphere of the student's experience and his motivational sphere. It was found that a necessary condition for the successful development of pupils’ creative thinking in the process of tasks solving is the availability of appropriate prognostically necessary information.

Study of critical manufacturing processes for the creation of 3D and fully transparent medical models of aneurysm and bronchi of the Lung

To support the training of neurosurgeons, innovative simulators associated with professional medical courses are needed. Virtual reality and 3D models have been making their way into surgical training facilities and medical schools for several years. However, both simulators cannot provide a hands-on and tactile experience of what it is like to see and feel in a real surgical procedure. Professor Pin-Chuan Chen of the Mechanical Engineering Department at the National Taiwan University of Science and neurosurgeon Dr Wei-Hsiu Liu of the National Defense Medical Center, are collaborating to design and create a new generation of lifelike medical simulators for neurosurgery training.

Non-normal-Mode Onset of Convection in a Vertical Porous Cylinder

This is the first study reporting a full three-dimensional (3D) non-normal-mode onset of convection in a porous medium. In this paper, the onset of thermal convection in a vertical porous cylinder is investigated theoretically. In particular, the contribution includes the following novelties. The homogeneous cylinder has a circular cross section. The eigenvalue problem is non-separable in space because of a constant heat flux condition at the upper boundary. In addition, a partly conducting cylinder wall is represented by a Robin parameter a. All boundaries are impermeable. The eigenvalue problem is solved numerically in the COMSOL Multiphysics environment. The critical Rayleigh number for the lowest onset modes is reported as a function of the ratio of the cylinder radius and its height. The only mode number, m, represents azimuthal dependency. The axisymmetric mode $$m=0$$ corresponds to the preferred mode of convection for a small-cylinder radii. The numerical onset criterion is validated with the well-known analytical limit case, $$a \rightarrow \infty$$ . Finally, we performed a visual comparison of the thermo-mechanical eigenfunctions against an established problem, where the only difference is the thermal condition at the upper boundary. The present 3D analysis is a step toward a full adequate modeling of experimental reality for convection onset, beyond the standard constraints of mathematical convenience.

Validity of a Novel Chicken and Porcine Model for Laparoscopic Neobladder Reconstruction.

Introduction: Simulation-based training in laparoscopic urology is essential, as these surgeries require a skill set different from routine urologic procedures. We aim to describe and validate the chicken and porcine intestine model for laparoscopic neobladder reconstruction. Materials and Methods: Prospective observational study was conducted at our institute. Twenty novice and 20 trained laparoscopic surgeons were included in the study. The relevant chicken anatomy and surgical steps were described to all the surgeons. The surgeons were asked to fill a nine-point questionnaire after completing the exercise comprising bowel organization, ability to do urethroneovesical anastomosis, suturing time, suturing similarity, quality of suturing, tissue feel, integrity of anastomosis, realism, and usefulness of model after finishing the procedure, and score it on a scale of 1-5. Time taken to perform the entire exercise was noted in addition. An independent expert observer retrospectively rated the urethroneovesical anastomosis on a scale of 1-5. Results: All the participants in the study gave a mean score of 3.5 or more to all the questions asked in the questionnaire. Both the groups rated the usefulness of the model highly with a mean score of 4.6 and 4.45, respectively. The mean score of the questionnaire was 35.9 and 36, respectively, for both the groups. The quality of urethroneovesical anastomosis as observed by an expert was better in the expert group (p = 0.001). Conclusion: The chicken and porcine model for laparoscopic neobladder reconstruction is a useful and effective training tool. This model has face, content, and construct validity to be used as a teaching and training tool in laparoscopic urology.

Interactive impacts of meteorological and hydrological conditions on the physical and biogeochemical structure of a coastal system

Abstract. The German Bight was exposed to record high riverine discharges in June 2013, as a result of flooding of the Elbe and Weser rivers. Several anomalous observations suggested that the hydrodynamical and biogeochemical states of the system were impacted by this event. In this study, we developed a biogeochemical model and coupled it with a previously introduced high-resolution hydrodynamical model of the southern North Sea in order to better characterize these impacts and gain insight into the underlying processes. Performance of the model was assessed using an extensive set of in situ measurements for the period 2011–2014. We first improved the realism of the hydrodynamic model with regard to the representation of cross-shore gradients, mainly through inclusion of flow-dependent horizontal mixing. Among other characteristic features of the system, the coupled model system can reproduce the low salinities, high nutrient concentrations and low oxygen concentrations in the bottom layers observed within the German Bight following the flood event. Through a scenario analysis, we examined the sensitivity of the patterns observed during July 2013 to the hydrological and meteorological forcing in isolation. Within the region of freshwater influence (ROFI) of the Elbe–Weser rivers, the flood event clearly dominated the changes in salinity and nutrient concentrations, as expected. However, our findings point to the relevance of the peculiarities in the meteorological conditions in 2013 as well: a combination of low wind speeds, warm air temperatures and cold bottom-water temperatures resulted in a strong thermal stratification in the outer regions and limited vertical nutrient transport to the surface layers. Within the central region, the thermal and haline dynamics interactively resulted in an intense density stratification. This intense stratification, in turn, led to enhanced primary production within the central region enriched by nutrients due to the flood but led to reduction within the nutrient-limited outer region, and it caused a widespread oxygen depletion in bottom waters. Our results further point to the enhancement of the current velocities at the surface as a result of haline stratification and to intensification of the thermohaline estuarine-like circulation in the Wadden Sea, both driven by the flood event.

Detecting, analysing, and modelling failed lane-changing attempts in traditional and connected environments

Lane-changing is a routine yet a complex driving task that has several negative impacts on both traffic flow efficiency and road safety, and thus, lane-changing models have become an indispensable part of microsimulation tools. The existing models only consider lane-changing manoeuvres that are successfully completed while failed lane-changing attempts (i.e., a lane-changing manoeuvre that is aborted after its initiation) are by and large ignored during calibration and validation of lane-changing models. This ignorance leads to structural incompleteness of lane-changing models. In addition, compared with successful lane-changing manoeuvres, failed lane-changing attempts are more likely to disrupt traffic flow and create safety hazards in both the current lane and the target lane, and thus, further warranting its consideration during lane-changing modelling. A connected environment can minimise these adverse effects by providing driving messages about surrounding traffic and subsequent gaps available in the target lane that drivers can utilise to make informed and safe lane-changing decisions. As such, this study investigates the impact of a connected environment on failed lane-changing attempts and addresses the issue of structural incompleteness of lane-changing models using three steps. First, a Wavelet Transform (WT)-based method is employed to detect failed lane-changing attempts from the real data. Second, the impact of failed lane-changing attempts is examined on both traffic flow efficiency and safety parameters such as average speed reduction and Deceleration Rate to Avoid a Crash (DRAC). Moreover, how a connected environment influences these parameters is also explored using a random parameters binary logistic model. Finally, failed lane-changing attempts are incorporated into the existing lane-changing models. At the first step, the WT-based method shows a reasonable accuracy in detecting failed lane-changing attempts when applied to NGSIM dataset and the driving simulator data collected in this study whereby drivers drove the CARRS-Q Advanced Driving Simulator and failed to complete a lane-changing manoeuvre in two randomised driving conditions: baseline (without driving messages) and connected environment (with driving messages). At the second step, we find that failed lane-changing attempts cause a higher speed reduction in both the current lane and the target lane compared to the successful ones. Similarly, a higher DRAC rate is required during failed lane-changing attempts compared to the successful lane-changing attempts, implying a higher crash risk during failed lane-changing attempts. Furthermore, the connected environment has shown to reduce not only the frequency of failed lane-changing attempts but also their negative impacts on surrounding traffic. Moreover, although the developed random parameters model reveals a significant heterogeneity at the individual level, suggesting that while the majority of the drivers tend to abort lane-changing manoeuvres with increase in the relative speed, this does not hold for a small portion of drivers. Finally, by incorporating failed lane-changing attempts into the existing lane-changing models, the predictive accuracy and realism of the lane-changing models have been enhanced.

Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model

Abstract. This study assesses the impact of different sea ice thickness distribution (ITD) discretizations on the sea ice concentration (SIC) variability in ocean stand-alone NEMO3.6–LIM3 simulations. Three ITD discretizations with different numbers of sea ice thickness categories and boundaries are evaluated against three different satellite products (hereafter referred to as “data”). Typical model and data interannual SIC variability is characterized by K-means clustering both in the Arctic and Antarctica between 1979 and 2014. We focus on two seasons, winter (January–March) and summer (August–October), in which correlation coefficients across clusters in individual months are largest. In the Arctic, clusters are computed before and after detrending the series with a second-degree polynomial to separate interannual from longer-term variability. The analysis shows that, before detrending, winter clusters reflect the SIC response to large-scale atmospheric variability at both poles, while summer clusters capture the negative and positive trends in Arctic and Antarctic SIC, respectively. After detrending, Arctic clusters reflect the SIC response to interannual atmospheric variability predominantly. The cluster analysis is complemented with a model–data comparison of the sea ice extent and SIC anomaly patterns. The single-category discretization shows the worst model–data agreement in the Arctic summer before detrending, related to a misrepresentation of the long-term melting trend. Similarly, increasing the number of thin categories reduces model–data agreement in the Arctic, due to a poor representation of the summer melting trend and an overly large winter sea ice volume associated with a net increase in basal ice growth. In contrast, more thin categories improve model realism in Antarctica, and more thick ones improve it in central Arctic regions with very thick ice. In all the analyses we nonetheless identify no optimal discretization. Our results thus suggest that no clear benefit in the representation of SIC variability is obtained from increasing the number of sea ice thickness categories beyond the current standard with five categories in NEMO3.6–LIM3.

Sim2Real Predictivity: Does Evaluation in Simulation Predict Real-World Performance?

Does progress in simulation translate to progress on robots? If one method outperforms another in simulation, how likely is that trend to hold in reality on a robot? We examine this question for embodied PointGoal navigation, developing engineering tools and a research paradigm for evaluating a simulator by its sim2real predictivity. First, we develop Habitat-PyRobot Bridge (HaPy), a library for seamless execution of identical code on simulated agents and robots, transferring simulation-trained agents to a LoCoBot platform with a one-line code change. Second, we investigate the sim2real predictivity of Habitat-Sim for PointGoal navigation. We 3D-scan a physical lab space to create a virtualized replica, and run parallel tests of 9 different models in reality and simulation. We present a new metric called Sim-vs-Real Correlation Coefficient (SRCC) to quantify predictivity. We find that SRCC for Habitat as used for the CVPR19 challenge is low (0.18 for the success metric), suggesting that performance differences in this simulator-based challenge do not persist after physical deployment. This gap is largely due to AI agents learning to exploit simulator imperfections, abusing collision dynamics to 'slide' along walls, leading to shortcuts through otherwise non-navigable space. Naturally, such exploits do not work in the real world. Our experiments show that it is possible to tune simulation parameters to improve sim2real predictivity (e.g. improving $SRCC_{Succ}$ from 0.18 to 0.844), increasing confidence that in-simulation comparisons will translate to deployed systems in reality.

ФАЗОВЫЙ ОБЪЕМ ВОСПРИЯТИЯ РЕАЛЬНОСТИ: ДЕТЕРМИНАНТЫ И СРЕДСТВА ВЫРАЖЕНИЯ 2

The article is devoted to problem of revision of the borders of the range (the phase volume) and adequacy of the perception of the world in speaker long disheveled locks of universe-social evolution of the man. It is shown that in man’s perception volume is conditioned by the physiological organization as well as by its place in the cosmos and the Earth biosphere. The accent is made on discovery determinant conditioning given range of the perception and facility of the expression available perception to information. It is revealed that the modeling of reality becomes more abstract and clear, but less concrete, adequate to the «ultimate reality» with its blurred forms.

Exploring Hydrologic Model Process Connectivity at the Continental Scale Through an Information Theory Approach

AbstractExploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as “transfer entropy” (TE) to systematically quantify the transfer of information among major HM components. To test and demonstrate the benefits of TE, we use the Framework for Understanding Structural Errors (FUSE) model to mimic and compare four commonly used HM structures, VIC, PRMS, SACRAMENTO, and TOPMODEL, across 671 catchments spanning a variety of hydrologic regimes in the conterminous United States. We explore connections between HM components and catchment landscape characteristics (e.g., climate, topography, soil, and vegetation) and characterize their nonlinear associations using distance correlation and Spearman correlation coefficients. Our results indicate that while the information transferred from precipitation to runoff is similar across model structures (likely as a result of calibration), the information transferred among other components can vary significantly from a FUSE structure to another. We find that aridity, precipitation duration and frequency, snow fraction, mean elevation, forest area, and leaf area index are often significantly associated with TE between the main HM components. We propose that the presence of meaningful nonlinear associations can be used to diagnose process representation in HMs. Our results highlight the necessity to enhance the conventional streamflow‐only calibration approach for a more realistic representation of water dynamics in the models.

A cohort projection method to follow deb-structured populations with periodic, synchronized and iteroparous reproduction

The need to follow structured populations, as opposed to unstructured ones, is well-recognized. The most detailed category of population models are the individual-based population models (IBMs), also called agent-based population models (ABMs). Their analysis is generally by simulation in time followed by statistical analysis of the numerical results. A less detailed method is the physiologically structured population model approach (PSPMs) leading originally to continuous-time partial differential equations (pdes) for the p(opulation)-states such as number(-density) with respect to time and i(ndividual)-state such as age and/or size and later to a delay equation formulation. Their mathematical analysis and computational methods are generally complex. Discrete-time matrix population models (MPMs) are much simpler to analyse in all respects, but the applicability is limited due to stringent modelling assumptions made. We discuss here a class of models we call the Cohort Projection Models (CPMs), which were formerly introduced as a special case of PSPMs with pulsed reproduction. CPMs follow cohorts of identical individuals in a Lagrangian way of which the changes of their i-states such as, size, energy reserves and maturity, are described by age dependent ordinary differential equations (ode)s from DEB theory. Simultaneously the p-states, such as number of individuals are described by time dependent odes obeying conservation laws. The population is subdivided in generations on the assumption that seasonal cycles synchronize reproduction events among cohorts and all eggs that are produced by different generations are the same. Feedback from the environment can be included via specification of food dynamics that accommodates competition. Temperature follows a specified periodic trajectory in time. This allows for the definition of a projection map of i-states and p-states, from one reproduction event to the next. The projection interval is typically one year for seasonal variability. The properties of the map can be studied using nonlinear dynamical system theory, such as existence and stability of fixed points and, thereby, the long-term dynamics of the food-population system. We demonstrate this using deb parameter values from the Add-my-Pet (AmP) collection for over 2000 animal species, which were estimated from empirical data. CPMs are meant to match the relative simplicity of the analysis of MPMs with the realism of the deb models for the dynamics of the population individuals.

Qualitative Acceptance Model of Augmented Reality from the Perspective of Personalists

Smart devices and the corresponding new technologies have established themselves within our society. Since the release of the smartphone game Pokémon Go, the field of augmented reality (AR) - the enrichment of reality with information, realized by smart devices such as tablets, data glasses or smartphones - has been experiencing an upswing. Additionally, the industry is starting to integrate AR applications to increase efficiency. In this respect, HR managers play a key role in the implementation of such technology. They maintain direct contact with employees, have an overview of the entire company and thus are often responsible for change processes. The paper analyses the potential of AR within a company from a personalist’s point of view and discusses critical factors both in theory and practice. The paper validates the technological possibilities and shows results from a qualitative analysis from focus group discussions. The qualitative acceptance model displays factors influencing the implementation of AR.

Stepwise modeling and the importance of internal variables validation to test model realism in a data scarce glacier basin

Model realism is of vital importance in science of hydrology, in terms of realistic representation of hydrological processes and reliability of future prediction. Here, we employed a stepwise modeling approach that leverages flexible model structures and multi-source observations for robust streamflow simulation and internal variables validation with improved model realism. This framework is demonstrated in Yigong Zangbu River (YZR) basin, a data scarce glacier basin in the upper Brahmaputra River. We designed six experiments (Exp1–6) to use modeling as a tool to understand hydrological processes in this remote cold basin with extremely high altitude. In Exp1, we started with a distributed rainfall-runoff model (FLEXD) - representing the case that snow and glacier processes were ignored. Then, we stepwisely added snow and glacier processes into FLEXD, denoted as FLEXD-S (Exp2) and FLEXD-SG (Exp3), respectively, and such improvement of model structure led to significantly improved streamflow estimates. To explore the impact of different precipitation forcing on model performance, FLEXD-SG was driven by Theissen average (Exp3) and three individual stations’ precipitation (Exp4–6). The model realism was tested by observed hydrograph, snow cover area (SCA) and glacier mass balance (GMB). Results showed that a robust and realistic hydrological modeling system was achieved in Exp6. In this modeling study, we learned that: 1) stepwise modeling is effective in investigating catchment behavior, and snow and glacier melting are the dominant hydrological processes in the YZR basin; 2) internal variables validation is beneficial to test model realism in data scarce basin; 3) the FLEXD-SG model calibrated by only one year hydrograph is sufficient to reproduce snow and glacier variations; 4) precipitation of a single station as forcing data could outperform Theissen average; 5) based on the well tested model configuration in Exp6, we analyzed simulated results, and reconstructed the long term hydrography (1961–2013), to support the potential competence for decision making on water resources management in practice. The proposed framework may significantly improve our skills in hydrological modeling over data-poor regions.