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Kidney failure is a common disease prevailing in the present generation. Renal disfunction inflict adverse effects on human health that are much fatal. Kidney failure has attracted great attention among the present scientific community. Thus, it is desirable to develop an implantable device to replace the failed kidney that could be partially possible with Kidney-on-Chip technology. This paper presents a Kidney-on-Chip model where size-dependent re-absorption of the kidney is majorly investigated by considering the implications of hydrostatic pressure. The device is comprised of two blood tubules separated by a main tubule in the Centre. The main tubule connects both the blood tubules by the means of transporting channels. The transporting channel allows the flow of solutes from the main tubule to blood tubules depending on size of the solutes. The hydrostatic effect can alter the functioning of the kidney by effecting the cytoskeleton arrangement of kidney cells. Employing hydrostatic effects into the device will make the model more compact and realistic. The analysis was made by employing hindrance in the form of bars arranged in zig–zag fashion in the main tubule forming stepwise structure. Simulation results of presented design have produced an outflow velocity of 9.12 × 10−5 m/s which is greater than 8.2 × 10−5 m/s without hydrostatic effect. The re-absorption rate has been improved from 50 to 55% which is desirable. The mathematical analysis was made to support the simulation results. Different studies were conducted on the device performance by changing the parameters that affect fluid flow such as inflow velocity, density, viscosity, capillary forces, and surface tension. The presented work can produce a bio-reactor for kidney-on-Chip applications with more realistic results. [ABSTRACT FROM AUTHOR]

In recent years, the field of education has challenged researchers and practitioners to incorporate computing as an essential focus of K-12 STEM education. Integrating computing within K-12 STEM supports learners of all ages in codeveloping and using computational thinking in existing curricular contexts alongside practices essential for developing mathematical and scientific expertise. In this paper, we present findings from a design-based, microgenetic study in which an agent-based programming and computational modeling platform—ViMAP—was integrated with existing elementary science and math curricula through lessons co-designed and taught by the classroom teacher across a period of seven months. We present a dialogical re-positioning of coding, where disciplinarily grounded meanings of code emerge through the construction of computational utterances––i.e., computer models as well as complementary conversations and physical models that serve as mathematical and scientific explanations––through the use of socio-mathematical norms. [ABSTRACT FROM AUTHOR]

Studies of scientific practice demonstrate that the development of scientific models is an enactive and emergent process (e.g., Pickering 1995; Chandrasekharan and Nersessian 2017). Scientists make meaning through processes such as perspective taking, finding patterns, and following intuitions. In this paper, we focus on how a group of fourth grade learners and their teacher engaged in interpretation in ways that align with core ideas and practices in kinematics and computing. Cycles of measuring and modeling––including computer programming––helped to support classroom interactions that highlighted the interpretive nature of modeling and participation in model construction as a knowledge-building process. We draw on literature from the history and philosophy of science in order to analyze the students' interpretive actions as forms of epistemic and representational agency, constituting a construct we term disciplined interpretation. We demonstrate how students' disciplined interpretative moves help to position them as owners of their own design decisions and their rights to interpret the phenomena they were modeling, data collected from those phenomena, and the scientific and computational models themselves. We present four extended episodes that characterize the nature of activity in the classroom and the development of students' disciplined interpretations in terms of learning to recognize scientific patterns amid complex perceptual fields, and to represent them in ways that support sensemaking. [ABSTRACT FROM AUTHOR]

The flow in the nephron tubules regulates the blood homeostasis, secretion, excretion and reabsorption of solutes. Flow induces fluid shear stress (FSS) on walls of tubules which has substantial effect on kidney functioning. Modelling of FSS mimicking structures is critical for their optimization. In this paper, a compact structure for kidney-on-chip devices is proposed for exact reconstruction of FSS and temperature effect in tubules considering the nephron tubule dimensions for modelling. The proposed system is compartmentalized basically into three parts ultra filter, device structure and reactor. The FSS is analysed for different inflow rates, proving the proposed structure is helpful in balancing the tubuloglomerulo feedback system mimicking. The structure is analysed for different structural changes in benchmark FEM tool COMSOL Multiphysics to optimize it to suite the kidney-on-chip purpose. Pressure achieved at the cell site is 0.1 Pa, which is the pressure applied by FFS on kidney tubules cells. The temperature effect of the human body is considered and the findings are presented. Temperature has an inverse relationship with FSS. At absolute temperature the pressure is 9.7 Pa and reached 3.77 Pa at body temperature, showing a decrease in pressure. The reaction of sodium and calcium is presented to show common reabsorption happening the kidney. The fabrication process flow is implemented in Intellisuite tool which is incorporated here to indicate the device fabrication cost will be low. The proposed Kidney-on-Chip structure finds astounding results make it to use in potential transplantable devices. [ABSTRACT FROM AUTHOR]

Students from middle school to college have difficulties in interpreting and understanding complex systems such as ecological phenomena. Researchers have suggested that students experience difficulties in reconciling the relationships between individuals, populations, and species, as well as the interactions between organisms and their environment in the ecosystem. Multi-agent-based computational models (MABMs) can explicitly capture agents and their interactions by representing individual actors as computational objects with assigned rules. As a result, the collective aggregate-level behavior of the population dynamically emerges from simulations that generate the aggregation of these interactions. Past studies have used a variety of scaffolds to help students learn ecological phenomena. Yet, there is no theoretical framework that supports the systematic design of scaffolds to aid students' learning in MABMs. Our paper addresses this issue by proposing a comprehensive framework for the design, analysis, and evaluation of scaffolding to support students' learning of ecology in a MABM. We present a study in which middle school students used a MABM to investigate and learn about a desert ecosystem. We identify the different types of scaffolds needed to support inquiry learning activities in this simulation environment and use our theoretical framework to demonstrate the effectiveness of our scaffolds in helping students develop a deep understanding of the complex ecological behaviors represented in the simulation.. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) draws on concepts and practices that are fundamental to computing and computer science. It includes epistemic and representational practices, such as problem representation, abstraction, decomposition, simulation, verification, and prediction. However, these practices are also central to the development of expertise in scientific and mathematical disciplines. Recently, arguments have been made in favour of integrating CT and programming into the K-12 STEM curricula. In this paper, we first present a theoretical investigation of key issues that need to be considered for integrating CT into K-12 science topics by identifying the synergies between CT and scientific expertise using a particular genre of computation: agent-based computation. We then present a critical review of the literature in educational computing, and propose a set of guidelines for designing learning environments on science topics that can jointly foster the development of computational thinking with scientific expertise. This is followed by the description of a learning environment that supports CT through modeling and simulation to help middle school students learn physics and biology. We demonstrate the effectiveness of our system by discussing the results of a small study conducted in a middle school science classroom. Finally, we discuss the implications of our work for future research on developing CT-based science learning environments. [ABSTRACT FROM AUTHOR]

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term 'agent' in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection-species differentiation and population change-through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test. [ABSTRACT FROM AUTHOR]

Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research on educational computing. We present a new Logo-based visual programming language-ViMAP-and, a sequence of learning activities involving programming and modeling, designed specifically to support seamless integration between programming and learning kinematics. We describe relevant affordances of the ViMAP environment that supports such seamless integration. We then present ViMAP-MoMo, a curricular unit designed in ViMAP for modeling kinematics, for a wide range of students (elementary-high school). Finally, we describe in detail a sequence of learning activities in three phases, discuss the underlying rationale for each phase, and where relevant, report results in the form of observational data from two studies. [ABSTRACT FROM AUTHOR]