Simple Conceptual Model Research Articles

Karlman Wasserman, MD, PHD, Physiologist and Physician-Scientist: 1927–2020

Karlman Wasserman, MD, PHD, Physiologist and Physician-Scientist: 1927–2020

Diurnal self-aggregation

Convective self-aggregation is a modelling paradigm for convective rain cell organisation over a constant-temperature tropical sea surface. This set-up can give rise to cloud clusters developing over timescales of weeks. In reality, sea-surface temperatures do oscillate diurnally, affecting the atmospheric state and influencing rain rates significantly. Over land, surface temperatures vary more strongly. Here, we carry out a suite of cloud-resolving numerical experiments, and find that qualitatively different dynamics emerge from modest surface temperature oscillations: while the spatial distribution of rainfall is homogeneous during the first day, already on the second day, the rain field is firmly structured. In later days, this clustering becomes stronger and alternates from day to day. We show that these features are robust to changes in resolution, domain size and mean surface temperature, but can be removed by a reduction of the amplitude of diurnal surface temperature oscillation, suggesting a transition from a random to a clustered state. Maximal clustering occurs at a scale of {l}_{max }approx 180 {rm{km}}, which we relate to the emergence of mesoscale convective systems. At {l}_{max }, rainfall is strongly enhanced and far exceeds the rainfall expected at random. Simple conceptual modelling helps interpret the transition to clustering, which is driven by the formation of mesoscale convective systems, and brings about day-to-day moisture oscillations. Our results may help clarify how continental extremes build up, and how cloud clustering over the tropical ocean could emerge as an instance of spontaneous symmetry breaking at timescales much faster than in conventional radiative–convective equilibrium self-aggregation.

Comparative morphosedimentary framework of small subtropical islands offshore Kuwait

Five small islands offshore of the State of Kuwait in the northern Arabian Gulf (Miskan, Awhah, Kubbar, Qaruh, and Umm Al-Maradem) occur in differing structural settings and have evolved in a dynamic environment of shifting fluvial depocenters, fluctuating Holocene sea level, and variable tidal conditions. As a first step in reconstructing the origin and evolution of the islands, bathymetric charts, historical photographs, topographic profiles, and sediment samples were used to investigate their geomorphology and sedimentary environments. The subaerial portion of the islands varies in area from 0.04 to 0.57 km2. The plan-shape ellipticity ranges from nearly circular (0.10) to oval-shaped (0.54). The northern two islands (Miskan and Awhah) experience mesotidal conditions and are situated on a shallow platform (<5 m below mean sea level), which is part of a larger Failaka Island structure. In contrast, the three southern sites have a microtidal regime and sit atop small isolated platforms of aggrading perched reef origin, which descend steeply to more than 20–30 m depth within 3 km of the islands. Topographic profiles indicate that island interiors are composed of beach-ridge sets, whereas modern shoreline consists of segments of beachrock platforms alternating with depositional salients and flying spits in areas of longshore transport convergence. The proportion of total shoreline length represented by exposed beachrock varies from 4 to 46%. Beach sediments consist of very coarse to medium sand and variable sorting, primarily due to the degree of attrition of bioclastic material. A simple conceptual model is proposed to describe the general evolutionary trajectory of end-member islands. Both their accretion during the Late Holocene sea-level stillstand and decadal-scale persistence of sediment transport convergence sites (salients) suggest a morphosedimentary stability of the islands in the near future.

Decreto 9.283/2018 na perspectiva de criação de alianças estratégicas

A Lei de Inovação Tecnológica sob o número 10.973 de 02 de dezembro de 2004, foi promulgada com o intuito de promover medidas de incentivo à inovação e à pesquisa científica e tecnológica no ambiente produtivo, e assim alcançar o desenvolvimento econômico do país. Entretanto, as pesquisas que são realizadas em universidades apesar de ter adquirido um papel crucial no âmbito do conhecimento e do desenvolvimento de novas tecnologias, ainda é incipiente a sua aplicação no mercado. Dessa forma, o Decreto 9.283/2018 regulamenta a Lei 10.973, além de outras, cuja a finalidade é o alcance da autonomia tecnológica e o desenvolvimento do sistema produtivo nacional e regional. Partindo desses pressupostos, o artigo tem como objetivo analisar a Lei 9.283/2018 e compreender as conexões entre empresa e universidade, sob ponto de vista da percepção da criação de alianças estratégicas. A pesquisa tem um caráter exploratório qualitativo, no qual foi feito uma análise do Decreto 9.283/2018 sob a perspectiva de criação de alianças estratégicas que permita a cooperação entre universidade e empresa, como forma de desenvolvimento de novas tecnologias que possam ser comercializadas. Em termos metodológicos, foi feita uma coleta de dados secundários através do Formulário para Informações sobre a Política de Propriedade Intelectual das Instituições Científicas, Tecnológicas e de Inovação do Brasil (FORMICT), disponível no endereço eletrônico www.mctic.gov.br do Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC). Apresentando, assim, uma proposta de modelo conceitual simplificado de alianças estratégicas para as Instituições de Ciência e Tecnologia.

Self-sustained oscillations and global climate changes

The periodic changes of atmospheric CO2 and temperature over the last 5 Myr reveal three features that challenge current climate research, namely: (i) the mid-Pleistocene transition of dominant 41-kyr cycles to dominant 100-kyr cycles, (ii) the absence of a strong precession signal of approximately 20 kyr, and (iii) the cooling through the middle and late Holocene. These features are not directly addressable by Earth’s orbital changes described by Milankovitch. Here we show that a closed photochemical system exposed to a constant illumination source can sustain oscillations. In this simple conceptual model, the oscillations are intrinsic to the system and occur even in the absence of periodic radiative forcing. With proper adaptations to the Earth system, this oscillator explains the main features of past climate dynamics. Our model places photosynthesis and the carbon cycle as key drivers of climate change. We use this model to predict the relaxation of a 1,000 PgC pulse of CO2. The removal of 50% of this CO2 will require one century, and will lead to a warmer and wetter future. However, more pronounced glaciation cycles emerge on the millennial timescale.

Applicability of Lumped Hydrological Models in a Data-Constrained River Basin of Asia

A representative of meteorological data-constrained basin, Ayeyarwady, in Myanmar, Southeast Asia, is set for flow simulation and forecasting at 15 locations using a range of hydrological modeling approaches: conceptual lumped (GR4J), hybrid-lumped [Identification of unit Hydrographs And Component flows from Rainfall Evapotranspiration and Streamflow Catchment Wetness Index (IHACRES CWI)], semidistributed [Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS)], and relatively distributed [Soil and Water Assessment Tool (SWAT)]. Using daily rainfall data from 51 surface rainfall stations (over an area of approximately 400,000 km2) and coarse monthly evaporation inputs from global sources, the models are calibrated (validated) against observed flows for 2001–2009 (2010–2014) using the performance indicators Nash-Sutcliffe efficiency (NSE), percentage bias (PBIAS), RMSE-observations standard deviation ratio (RSR), and volumetric efficiency . The developed models were then integrated with rainfall forecasts from the Weather Research and Forecasting Model for 2015–2018 and assessed for biases against observed flows. The NSE values were favorable for GR4J (median NSE=0.9), followed by IHACRES (NSE=0.86), SWAT (NSE=0.81) and HEC-HMS (NSE=0.77) during calibration and GR4J (NSE=0.87) and the latter three (NSE=0.83) during validation. Lumped models were found to have comparable, albeit better in simulating low, median, and high quantiles of flows during both calibration and validation periods, compared to other models of varying complexity set for the study basin. The hydrometeorological coupling also revealed that GR4J yielded the least while HEC-HMS yielded the highest biases (up to 30-fold at some stations) in daily flow forecasting. The analysis suggested that while process-based and relatively complex models may exhibit better performance in data-rich basins, simple conceptual models like GR4J are useful for daily flow simulation and forecasting in data-constrained basins of the region.

Real Time Flow Forecasting in a Mountain River Catchment Using Conceptual Models with Simple Error Correction Scheme

Methods in operational hydrology for real-time flash-flood forecasting need to be simple enough to match requirements of real-time system management. For this reason, hydrologic routing methods are widely used in river engineering. Among them, the popular Muskingum method is the most extended one, due to its simplicity and parsimonious formulation involving only two parameters. In the present application, two simple conceptual models with an error correction scheme were used. They were applied in practice to a mountain catchment located in the central Pyrenees (North of Spain), where occasional flash flooding events take place. Several relevant historical flood events have been selected for calibration and validation purposes. The models were designed to produce real-time predictions at the downstream gauge station, with variable lead times during a flood event. They generated accurate estimates of forecasted discharges at the downstream end of the river reach. For the validation data set and 2 h lead time, the estimated Nash-Sutcliffe coefficient was 0.970 for both models tested. The quality of the results, together with the simplicity of the formulations proposed, suggests an interesting potential for the practical use of these schemes for operational hydrology purposes.

A novel and simple machine learning algorithm for preoperative diagnosis of acute appendicitis in children.

There is a tendency toward nonoperative management of appendicitis resulting in an increasing need for preoperative diagnosis and classification. For medical purposes, simple conceptual decision-making models that can learn are widely used. Decision trees are reliable and effective techniques which provide high classification accuracy. We tested if we could detect appendicitis and differentiate uncomplicated from complicated cases using machine learning algorithms. We analyzed all cases admitted between 2010 and 2016 that fell into the following categories: healthy controls (Group 1); sham controls (Group 2); sham disease (Group 3), and acute abdomen (Group 4). The latter group was further divided into four groups: false laparotomy; uncomplicated appendicitis; complicated appendicitis without abscess, and complicated appendicitis with abscess. Patients with comorbidities and whose complete blood count and/or pathology results were lacking were excluded. Data were collected for demographics, preoperative blood analysis, and postoperative diagnosis. Various machine learning algorithms were applied to detect appendicitis patients. There were 7244 patients with a mean age of 6.84 ± 5.31 years, of whom 82.3% (5960/7244) were male. Most algorithms tested, especially linear methods, provided similar performance measures. We preferred the decision tree model due to its easier interpretability. With this algorithm, we detected appendicitis patients with 93.97% area under the curve (AUC), 94.69% accuracy, 93.55% sensitivity, and 96.55% specificity, and uncomplicated appendicitis with 79.47% AUC, 70.83% accuracy, 66.81% sensitivity, and 81.88% specificity. Machine learning is a novel approach to prevent unnecessary operations and decrease the burden of appendicitis both for patients and health systems. III.

Understanding the evolution of interspecies interactions in microbial communities

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Characterizing fast herbicide transport in a small agricultural catchment with conceptual models

Herbicide pollution in headwater streams due to agricultural practices is a major environmental concern and is characterized by episodic peak concentrations from fast transport paths. We rely on previous experimental studies in a small (1.2km2) agricultural catchment in the Swiss Plateau, to model dynamic diffuse herbicide pollution with emphasis on fast transport paths in a conceptual modelling framework at the catchment scale. We show how experimentalists’ understanding of the fate of herbicides (perceptual model) can be translated into conceptual models considering sorption, degradation, and fast transport of water and chemicals facilitated by impervious surfaces, tile drains and artificial shortcuts. Different types of experimental data (streamflow, high-frequency concentration measurements, and soil–water distribution coefficients) are used in a joint Bayesian inference of model parameters. We assess the ability of different spatial configurations of hydrological response units in explaining observed heterogeneity in transport behaviour of two corn herbicides. Thereby, we find that (1) relatively simple conceptual models can provide a realistic description of herbicide fate in small agricultural catchments, (2) accounting for spray drift onto hard surfaces is necessary to avoid a severe model bias during the first rainfall event after application, and (3) including catchment-specific experimentalist knowledge about important elements like artificial shortcuts and tile drains leads to a reduction in uncertainty of 30% compared to the more conventional conception of the proximity to the stream as the dominant risk factor.

Using and communicating uncertainty for the effective control of invasive non‐native species

AbstractEstimates of quantities needed to plan invasive species control, such as population size, are always uncertain; this is an issue that can become a problem when mishandled in ecological science and its communication. The complexities of incorporating uncertainty into sophisticated decision‐support tools may be a barrier to their use by decision makers, leading to decisions being made without due regard to uncertainty and risking misplaced certainty of predicted outcomes. We summarise ways in which uncertainty has been incorporated into and used to advise decisions on the management of invasive non‐native species and other problem species, and offer a simple conceptual model for accommodating and using uncertainty at the planning stage. We also demonstrate how frequently uncertainty has been misused and miscommunicated in the wildlife management literature. We contend that uncertainty in estimates of natural quantities must be acknowledged, can inform decisions and can be made to derive decisions, and should not be ignored if invasive species policy is to be delivered effectively. Uncertainty must be communicated thoroughly and correctly by scientists if decision makers are to understand its consequences for planning and resourcing control programmes.

Shoreline change rates along Samborombón Bay, Río de la Plata estuary, Argentina

Samborombón Bay is an extensive microtidal wetland located in the outer Río de la Plata estuary. Shoreline change rates (erosion or accretion) were quantified at six control areas situated along the bay's coastal area. Digital Shoreline Analysis System 4.3 (DSAS) was used to process aerial photographs and high-resolution satellite images, aiming to quantify shoreline change. A larger ‘Total Period’ (the last 50 years) and a ’Recent Period’ (the last decade approximately) were considered for analyzing shoreline evolution. Erosion and accretion rates increased in five of the six control areas during the last decade. The alongshore (PlN) and the incident (Pi) wave energy fluxes were computed from numerical wave simulations. Highest mean annual Pi values were observed at the southern and northern sectors of the bay, and lower values were obtained at the center. Mean annual PlN shows a convergent pattern in Samborombón Bay. Some differences between adjacent locations regarding annual mean PlN were detected. These differences could generate a slight divergence in PlN, leading to mild coastal erosion. Pi presents generally positive trends along the bay. On the contrary, PlN only presents a significant trend in the southern part of the bay. Then, while the erosional capability (Pi) is increasing, transport capacity (PlN) is quite stable along the coastal area of the bay. Finally, the hydro-sedimentary processes at the coastal area of Samborombón Bay were interpreted by means of a simple conceptual model, which includes internal and external sources of sediments.

Comparison of rainfall-runoff models for climate change projection – case study of Citarum River Basin, Indonesia

Climate change affects temperature, rainfall and hydrological properties in the river basins. Projected rainfalls for several climate change models are widely available nowadays. However, in water resources planning and management, river discharges data is unfortunately more important. The information on climate change impact on river discharges is very limited. Conversion from the projected rainfall to the runoff in the rivers is needed. This study analyzes the performance of rainfall-runoff models: 1) Empirical Model that defines the discharge as a function of rainfall, evaporation, and temperature, widely applied by climate scientist; and 2) simple lump conceptual model of NRECA. These two rainfall-runoff models are applied during the control period in the year of 2006 to 2015 of the rainfall projections from the seven CMIP5 Global Circulation Models with the worst scenario, RCP 8.5. The ground station river discharge data selected is Nanjung river gauging station at Citarum River, situated just upstream of Saguling Reservoir, the uppermost of the cascade of three reservoirs Saguling-Cirata-Jatiluhur, with the catchment area of 1, 675 square kilometers. The results show that the simple conceptual model NRECA significantly gives better fitted to the observation data than the Empirical Model, especially during the dry season.

EVENT BASED FOG CHARACTERISTICS OF ÇARŞAMBA AIRPORT

In this study the characteristics of fog events were examined at Çarşamba International Airport in Turkey. Historical meteorological observations were used between the years of 2008 and 2017. Fog events were classified by a simple conceptual model on fog formation process. Fog types, visibility, duration, wind direction and speed, sea surface temperature were reviewed. Results show three main fog types; classified, radiation, advection and cloud base lowering. No fog events were observed between July and September, whereas the most foggy periods are between the beginning of January and the end of May. This corresponds with the advection fog period. Sea surface temperature and weather temperature during fog onset was found to highly correlate with each other. The return period of dense fog for two years was determined to be 8.27 hours. Light, calm and eastern directions of wind were detected during the most of the fog events. Fog onset and dissipation times were figured out in monthly scale and the effect of solar radiation is clearly seen with the onset and dissipation processes. Determined characteristics of fog in Çarşamba airport can be useful for future modeling studies.

Describing coseismic groundwater level rise using tank model in volcanic aquifers, Kumamoto, southern Japan

The change of groundwater levels after the 2016 Mw 7.0 Kumamoto crustal earthquake was evaluated using a simple conceptual hydrological model in an attempt to show the presence, intensity, and probable mechanism of water level rise observed in Kumamoto where a comprehensive observation-well network exists. A tank model was applied to verify 16 wells in the study field. In the model groundwater levels were first calibrated for the periods in ca. 2 years before the main shock using several hydrological parameters including precipitation, evapotranspiration, water recharge and discharge, and artificial recharge by irrigation. Water levels were then simulated by extrapolating this law of water fluctuating patterns for ca. 2.5 years after the main shock of the earthquake, without considering hydrogeological changes due to the earthquake. A difference in groundwater levels between observation and simulation results yields a degree of coseismic water level rises for each well. The coseismic abnormal water level increase was calculated to be ~11 m in 4–5 month after the main shock and was most significantly on the western slope of the Aso caldera rim mountains. The spatial distribution of the coseismic water increases clarified that the most dominate increasing anomalies prevail at mountain feet surrounding the plains, suggesting the occurrence of coseismic mountain water release resulting in the rise of water levels in downslope aquifers. Identified coseismic water level increases still continue up to 2.5 years after the earthquake, probably because changes in hydrogeological properties in mountain aquifers, i.e., permeability, are still sustained. Our forecasting water recovering trends require ca. 3.5–5 year after the earthquake for complete recovery to the original conditions. We demonstrated that our approaches are capable of describing coseismic water level changes and could potentially be applied to other fields.

Choosing best practices for managing impacts of trawl fishing on seabed habitats and biota

AbstractBottom trawling accounts for almost one quarter of global fish landings but may also have significant and unwanted impacts on seabed habitats and biota. Management measures and voluntary industry actions can reduce these impacts, helping to meet sustainability objectives for fisheries, conservation and environmental management. These include changes in gear design and operation of trawls, spatial controls, impact quotas and effort controls. We review nine different measures and actions and use published studies and a simple conceptual model to evaluate and compare their performance. The risks and benefits of these management measures depend on the extent to which the fishery is already achieving management objectives for target stocks and the characteristics of the management system that is already in place. We offer guidance on identifying best practices for trawl‐fisheries management and show that best practices and their likelihood of reducing trawling impacts depend on local, national and regional management objectives and priorities, societal values and resources for implementation. There is no universal best practice, and multiple management measures and industry actions are required to meet sustainability objectives and improve trade‐offs between food production and environmental protection.

Seasonal variation in growth, consumption and growth efficiency in overwintering juvenile steelhead

AbstractFood availability and thermal regimes can largely govern growth opportunities in fishes. In temperate regions, streams can exhibit summer temperatures that exceed the optima for coolwater‐adapted species relative to the amount of available food, and therefore, spring and fall may confer better growing conditions, especially for larger size classes. We examined the relationship between growth, consumption and growth efficiency across seasons in juvenile steelhead (Oncorhynchus mykiss) in their natal streams in Idaho, USA. Subyearling (0+) growth rates were higher in summer, whereas yearlings exhibited no statistically significant difference in growth between seasons. Consumption rates were overall lower in winter–spring but constituted a higher proportion of maximum consumption compared with summer and fall, indicating better food availability relative to metabolic demands. Net growth efficiencies were higher in winter–spring, but substantially more so than the proportion of maximum consumption. This suggests that overwinter growth performance was driven at least partly by higher growth efficiency, and the effect was most pronounced for yearling steelhead. The low proportions of maximum consumption for both age classes suggest that food was an overall limiting factor to growth, especially in summer when metabolic demands were highest. We discuss how temperature‐based models can overestimate growth in the warmest parts of the year and develop a simple conceptual model for the seasonal timing of juvenile growth. In anadromous populations, the outmigration of presmolts in spring can reduce the level of competition. For the individuals that remain in the river, growth in this period can be particularly important.

Probabilistic flood prediction for urban sub-catchments using sewer models combined with logistic regression models

ABSTRACTThis paper proposes a hybrid modelling approach for early urban flood warning and forecasting purpose. The hybrid model structure proposed combines a deterministic sewer model with a probabilistic logistic regression model. By varying the sewer model structures from complex hydrodynamic models to simple conceptual models, different hybrid models are constructed in order to accommodate different levels of available knowledge and data about the urban hydrological system. The hybrid models are optimized using crowdsourced flooding records. They can predict the probability of flooding at the urban sub-catchment scale. The proposed methodology is tested for two cases in Antwerp, Belgium. Promising results show its potential in making fast and reliable urban flood predictions. Reasonable predictions are made even by the simplest model form, indicating the method could work also for sub-catchments with limited information. It also shows that the proposed methodology allows identifying the most dominant hydrological processes explaining urban flooding.

Strategies for inclusive and safe education using virtual reality: from the digital library perspective

PurposeThis paper aims to propose the development of formal (scientific content) and informal (content for science communication) educational activities in an inclusive and safe way, involving two essential elements, virtual reality (VR) and the digital library; as well as the implications for its enforcement such as educational strategies in the university setting and for the encouragement of scientific culture in society.Design/methodology/approachFor the integration of content, a simplified conceptual model was designed first, in which universities and research centers are seen as complex systems where different subsystems, from which processes and information resources are derived, converge. To cover the model’s elements, a descriptive documentary review was developed, looking to synthesize each element’s contexts and implications.FindingsThe need to establish transdisciplinary relationships between the VR and the digital library is determined with the goal to integrate educational activities using technology, with the purpose of studying contents from the scientific point of view, as well as with the possibility of transforming them into contexts of general access for society, with the objective of social appropriation of knowledge, citizen science and social innovation. In the conclusion section, some implications in the implementation of this type of initiatives are presented.Originality/valueThe aspects that set this paper apart are: treating VR as emerging documents tending to measure their direct impact, not as isolated elements of a collection; identifying the digital library’s social influence actions through VR; and generating processes to encourage the creation of contents with a differentiated focus according to the population served.

A Braitenberg Vehicle Based on Memristive Neuromorphic Circuits

The Braitenberg vehicle as a simple conceptual model to characterize the response behaviors of animals or insects under a stimulus is widely used to develop autonomous vehicles able to adapt to the varying environments. Considerable effort has been devoted to building neuromorphic processors with the software in the vehicles; however, there has been no demonstration of Braitenberg vehicle with neuromorphic hardware so far. Herein, a Braitenberg vehicle with simple memristive neuromorphic circuits is built for the first time. This vehicle exhibits adaptive behaviors in the supervised learning process and is eventually trained to conduct the task of tracking path. Moreover, the memristive circuit in the vehicle demonstrates a very short response latency (≈56 ns) to input sensory information. Herein, an alternative promising solution to build self‐adaptive robots and pave the way for the realization of autonomous robots based on memristive neuromorphic circuits is offered.