Assembling a physical model helps students grasp human somatosensory pathways.

Mastering the complexity of the nervous system is essential for education programs in physiology, anatomy, and neuroscience. Students often struggle when learning somatosensory pathways, which convey information from sensory neurons to the somatosensory cortex in the brain. Active learning activities incorporating physical models have been shown to increase content comprehension as well as enjoyment of the learning process. Here, we present a three-dimensional physical model of somatosensory pathways constructed of durable, affordable, and widely available materials. In an upper level human physiology lab, students assembled the model and then used it to complete case study questions connecting damage to the spinal cord to resulting sensory deficits. This model-based activity was highly effective as indicated by significant increases in content knowledge and positive responses to survey questions on the effectiveness of the activity. This activity incorporates many evidence-based teaching practices that have been shown to increase engagement, inclusion, and mastery of content and provides an effective and fun way for students to learn a challenging topic.NEW & NOTEWORTHY This model-building activity for learning somatosensory neural pathways increases students' content knowledge and is an enjoyable way to learn a complex system. This activity adds to an ever-growing collection of evidence-based learning activities for human physiology courses.

Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method.

In this study, we propose a meticulous method for the three-dimensional modeling of slope models using structured light, a swift and cost-effective technique. Our approach aims to enhance the understanding of slope behavior during landslides by capturing and analyzing surface deformations. The methodology involves the initial capture of images at various stages of landslides, followed by the application of the structured light method for precise three-dimensional reconstructions at each stage. The system's low-cost nature and operational convenience make it accessible for widespread use. Subsequently, a comparative analysis is conducted to identify regions susceptible to severe landslide disasters, providing valuable insights for risk assessment. Our findings underscore the efficacy of this system in facilitating a qualitative analysis of landslide-prone areas, offering a swift and cost-efficient solution for the three-dimensional reconstruction of slope models.

Understanding Colloidal Quantum Dot Device Characteristics with a Physical Model.

Colloidal quantum dots (CQDs) are finding increasing applications in optoelectronic devices, such as photodetectors and solar cells, because of their high material quality, unique and attractive properties, and process flexibility without the constraints of lattice match and thermal budget. However, there is no adequate device model for colloidal quantum dot heterojunctions, and the popular Shockley-Quiesser diode model does not capture the underlying physics of CQD junctions. Here, we develop a compact, easy-to-use model for CQD devices rooted in physics. We show how quantum dot properties, QD ligand binding, and the heterointerface between quantum dots and the electron transport layer (ETL) affect device behaviors. We also show that the model can be simplified to a Shockley-like equation with analytical approximate expressions for reverse saturation current, ideality factor, and quantum efficiency. Our model agrees well with the experiment and can be used to describe and optimize CQD device performance.

Ciona embryonic tail bending is driven by asymmetrical notochord contractility and coordinated by epithelial proliferation.

Ventral bending of the embryonic tail within the chorion is an evolutionarily conserved morphogenetic event in both invertebrates and vertebrates. However, the complexity of the anatomical structure of vertebrate embryos makes it difficult to experimentally identify the mechanisms underlying embryonic folding. This study investigated the mechanisms underlying embryonic tail bending in chordates. To further understand the mechanical role of each tissue, we also developed a physical model with experimentally measured parameters to simulate embryonic tail bending. Actomyosin asymmetrically accumulated at the ventral side of the notochord, and cell proliferation of the dorsal tail epidermis was faster than that in the ventral counterpart during embryonic tail bending. Genetic disruption of actomyosin activity and inhibition of cell proliferation dorsally caused abnormal tail bending, indicating that both asymmetrical actomyosin contractility in the notochord and the discrepancy of epidermis cell proliferation are required for tail bending. In addition, asymmetrical notochord contractility was sufficient to drive embryonic tail bending, whereas differential epidermis proliferation was a passive response to mechanical forces. These findings showed that asymmetrical notochord contractility coordinates with differential epidermis proliferation mechanisms to drive embryonic tail bending.This article has an associated 'The people behind the papers' interview.

Implications of a New Test Facility for Fragmentation Investigations on Virgin (Micro)plastics.

Littered plastics are partly introduced into water bodies, ultimately transporting this waste to the shores and oceans. At the shore, ultraviolet (UV) radiation (also present in other environmental compartments) and wave breaking cause plastics to degrade and fragment into smaller particles, called microplastics, if below 5 mm. Since these plastics' surfaces can act as vectors for hydrophobic (toxic) chemical substances (e.g., per- and polyfluoroalkyl substances (PFAS)) and leach (toxic) chemicals into the water, the increase in the surface area through the fragmentation of plastics becomes relevant. Studies investigating different effects on the fragmentation of plastics have mostly disregarded a sufficient mechanical component for fragmentation, focusing on degradation by UV radiation. Therefore, this study investigated the impact of the mechanical fragmentation drivers, wave impact, and sediment abrasion on the fragmentation of expanded polystyrene (EPS), high-density polyethylene (PE-HD), and polyethylene terephthalate (PET) particles. In a newly designed test facility called Slosh-Box, the mentioned impacts were investigated concurrently. The results reveal that the mechanical impacts alone are sufficient for plastic fragmentation, and the test facility is suitable for fragmentation investigations. Furthermore, the increase in surface area was determined via scanning electron microscopy. For EPS, the surface area increased more than 2370-fold, while for PE-HD and PET, surface areas increased between 1 and 8.6 times. Concluding from the results, the new test facility is suitable for plastic fragmentation studies. In addition, sediment was revealed to be a relevant fragmentation driver, which should be included in every experiment investigating the fragmentation of plastic in a nearshore environment independent of other drivers like UV radiation.

Internal fluid pressure influences muscle contractile force.

Fluid fills intracellular, extracellular, and capillary spaces within muscle. During normal physiological activity, intramuscular fluid pressures develop as muscle exerts a portion of its developed force internally. These pressures, typically ranging between 10 and 250 mmHg, are rarely considered in mechanical models of muscle but have the potential to affect performance by influencing force and work produced during contraction. Here, we test a model of muscle structure in which intramuscular pressure directly influences contractile force. Using a pneumatic cuff, we pressurize muscle midcontraction at 260 mmHg and report the effect on isometric force. Pressurization reduced isometric force at short muscle lengths (e.g., -11.87% of P0 at 0.9 L0), increased force at long lengths (e.g., +3.08% of P0 at 1.25 L0), but had no effect at intermediate muscle lengths ∼1.1-1.15 L0 This variable response to pressurization was qualitatively mimicked by simple physical models of muscle morphology that displayed negative, positive, or neutral responses to pressurization depending on the orientation of reinforcing fibers representing extracellular matrix collagen. These findings show that pressurization can have immediate, significant effects on muscle contractile force and suggest that forces transmitted to the extracellular matrix via pressurized fluid may be important, but largely unacknowledged, determinants of muscle performance in vivo.

Research on Similarity Simulation Experiment of Mine Pressure Appearance in Surface Gully Working Face Based on BOTDA.

In order to study the mountain deflection characteristics and the pressure law of the working face after the mining of a shallow coal seam under the valley terrain, a geometric size of 5.0 × 0.2 × 1.33 m is used in the physical similarity model. Brillouin optical time domain analysis (BOTDA) technology is applied to a similar physical model experiment to monitor the internal strain of the overlying rock. In this paper, the strain law of the horizontal optical fiber at different stages of the instability of the mountain structure is analyzed. Combined with the measurement of the strain field on the surface of the model via digital image correlation (DIC) technology, the optical fiber strain characteristics of the precursor of mountain instability are given. The optical fiber characterization method of working face pressure is proposed, and the working face pressures at different mining stages in gully terrain are characterized. Finally, the relationship between the deflection instability of the mountain and the strong ground pressure on the working face is discussed. The sudden increase in the strain peak point of the horizontally distributed optical fiber strain curve can be used to distinguish the strong ground pressure. At the same time, this conclusion is verified by comparing the measured underground ground pressure values. The research results can promote the application of optical fiber sensing technology in the field of mine engineering.

A phenomenological-based model of the endometrial growth and shedding during the menstrual cycle.

The human endometrium presents a remarkable growth dynamic with an outstanding regenerative capacity. This work aims to develop a phenomenological-based dynamic model to predict the volume changes in the functional layer of the endometrium in each phase of the menstrual cycle. This model considers changes in the endometrial tissue, the blood flow through the spiral arteries, the shedding of the endometrial cells, and the menstrual blood flow. The input variables are estrogen and progesterone; these hormone dynamics are taken from a pre-existing and validated model. Key parameters are modified in order to know their effect on the state variables. The model response was quantitatively assessed using the experimental data of the endometrial cycle reported in the literature. The proposed model provides a better insight into the interactions between ovarian hormones and the endometrial cycle by coupling both physiological processes.

The Large-Scale Physical Model Tests of the Passing Ship Effect on a Ship Moored at the Solid-Type Berth.

The paper presents experimental research on hydrodynamic forces generated on a ship moored at a long quay wall, modeling the solid-type berth, by a passing ship. The proper prediction of interactions between the moored and passing ships is important for design and operational purposes. The results of the presented parametric study are presented as a space-time series of the forces as the functions of passing ship velocity and transverse separation distance between the ships. The experimental test setup constructed on the lake and the large scale of the manned physical ship models enabled a simulation of the real maneuvering situation. The force measurements were taken on the moored ship model fixed to the pantographs rigidly attached to the wall. The twin pantographs were attached to force sensors on the deck of the model by a system of movable joints, enabling the measurement of surge and sway forces. The presented method was verified based on available experimental and numerical data, showing a good agreement with the results.

Generating Daily Soil Moisture at 16 m Spatial Resolution Using a Spatiotemporal Fusion Model and Modified Perpendicular Drought Index.

Soil moisture (SM) is an important parameter in land surface processes and the global water cycle. Remote sensing technologies are widely used to produce global-scale SM products (e.g., European Space Agency's Climate Change Initiative (ESA CCI)). However, the current spatial resolutions of such products are low (e.g., >3 km). In recent years, using auxiliary data to downscale the spatial resolutions of SM products has been a hot research topic in the remote sensing research area. A new method, which spatially downscalesan SM product to generate a daily SM dataset at a 16 m spatial resolution based on a spatiotemporal fusion model (STFM) and modified perpendicular drought index (MPDI), was proposed in this paper. (1) First, a daily surface reflectance dataset with a 16 m spatial resolution was produced based on an STFM. (2) Then, a spatial scale conversion factor (SSCF) dataset was obtained by an MPDI dataset, which was calculated based on the dataset fused in the first step. (3) Third, a downscaled daily SM product with a 16 m spatial resolution was generated by combining the SSCF dataset and the original SM product. Five cities in southern Hebei Province were selected as study areas. Two 16 m GF6 images and nine 500 m MOD09GA images were used as auxiliary data to downscale a timeseries 25 km CCI SM dataset for nine dates from May to June 2019. A total of 151 in situ SM observations collected on 1 May, 21 May, 1 June, and 11 June were used for verification. The results indicated that the downscaled SM data with a 16 m spatial resolution had higher correlation coefficients and lower RMSE values compared with the original CCI SM data. The correlation coefficients between the downscaled SM data and in situ data ranged from 0.45 to 0.67 versus 0.33 to 0.54 for the original CCI SM data; the RMSE values ranged from 0.023 to 0.031 cm3/cm3 versus 0.027 to 0.032 cm3/cm3 for the original CCI SM data. The findings described in this paper can ensure effective farmland management and other practical production applications.

Is Protein Folding a Thermodynamically Unfavorable, Active, Energy-Dependent Process?

The prevailing current view of protein folding is the thermodynamic hypothesis, under which the native folded conformation of a protein corresponds to the global minimum of Gibbs free energy G. We question this concept and show that the empirical evidence behind the thermodynamic hypothesis of folding is far from strong. Furthermore, physical theory-based approaches to the prediction of protein folds and their folding pathways so far have invariably failed except for some very small proteins, despite decades of intensive theory development and the enormous increase of computer power. The recent spectacular successes in protein structure prediction owe to evolutionary modeling of amino acid sequence substitutions enhanced by deep learning methods, but even these breakthroughs provide no information on the protein folding mechanisms and pathways. We discuss an alternative view of protein folding, under which the native state of most proteins does not occupy the global free energy minimum, but rather, a local minimum on a fluctuating free energy landscape. We further argue that ΔG of folding is likely to be positive for the majority of proteins, which therefore fold into their native conformations only through interactions with the energy-dependent molecular machinery of living cells, in particular, the translation system and chaperones. Accordingly, protein folding should be modeled as it occurs in vivo, that is, as a non-equilibrium, active, energy-dependent process.

Projection decomposition via univariate optimization for dual-energy CT.

Dual-energy computed tomography (DECT) acquires two x-ray projection datasets with different x-ray energy spectra, performs material-specific image reconstruction based on the energy-dependent non-linear integral model, and provides more accurate quantification of attenuation coefficients than single energy spectrum CT. In the diagnostic energy range, x-ray energy-dependent attenuation is mainly caused by photoelectric absorption and Compton scattering. Theoretically, these two physical components of the x-ray attenuation mechanism can be determined from two projection datasets with distinct energy spectra. Practically, the solution of the non-linear integral equation is complicated due to spectral uncertainty, detector sensitivity, and data noise. Conventional multivariable optimization methods are prone to local minima. In this paper, we develop a new method for DECT image reconstruction in the projection domain. This method combines an analytic solution of a polynomial equation and a univariate optimization to solve the polychromatic non-linear integral equation. The polynomial equation of an odd order has a unique real solution with sufficient accuracy for image reconstruction, and the univariate optimization can achieve the global optimal solution, allowing accurate and stable projection decomposition for DECT. Numerical and physical phantom experiments are performed to demonstrate the effectiveness of the method in comparison with the state-of-the-art projection decomposition methods. As a result, the univariate optimization method yields a quality improvement of 15% for image reconstruction and substantial reduction of the computational time, as compared to the multivariable optimization methods.

How head shape and substrate particle size affect fossorial locomotion in lizards.

Granular substrates ranging from silt to gravel cover much of the Earth's land area, providing an important habitat for fossorial animals. Many of these animals use their heads to penetrate the substrate. Although there is considerable variation in head shape, how head shape affects fossorial locomotor performance in different granular substrates is poorly understood. Here, head shape variation for 152 species of fossorial lizards was quantified for head diameter, slope and pointiness of the snout. The force needed to penetrate different substrates was measured using 28 physical models spanning this evolved variation. Ten substrates were considered, ranging in particle size from 0.025 to 4 mm in diameter and consisting of spherical or angular particles. Head shape evolved in a weakly correlated manner, with snouts that were gently sloped being blunter. There were also significant clade differences in head shape among fossorial lizards. Experiments with physical models showed that as head diameter increased, absolute penetration force increased but force normalized by cross-sectional area decreased. Penetration force decreased for snouts that tapered more gradually and were pointier. Larger and angular particles required higher penetration forces, although intermediate size spherical particles, consistent with coarse sand, required the lowest force. Particle size and head diameter effect were largest, indicating that fossorial burrowers should evolve narrow heads and bodies, and select relatively fine particles. However, variation in evolved head shapes and recorded penetration forces suggests that kinematics of fossorial movement are likely an important factor in explaining evolved diversity.

Phenomenological-based model of glucose transport from liver to abdominal subcutaneous adipose tissue.

BACKGROUND: A good treatment for type 1 diabetes mellitus (T1DM) requires accurate measurements of blood glucose levels. Continuous glucose monitors (CGM) measure the glucose concentration in the interstitial fluid of the abdominal subcutaneous adipose tissue. However, glucose measured in the abdominal interstitial fluid does not represent blood glucose concentrations accurately due to the complex blood transport through the body and glucose diffusion in interstitial fluid. METHODS: To gain insight into this problem, a phenomenological-based semiphysical model (PBSM) of glucose transport by volumetric flow and diffusion from the bloodstream to interstitial fluid was constructed. A published 10-step modeling procedure was used to obtain a model for glucose transport time through the blood vessels and from the blood capillaries to the interstitial fluid, glucose diffusion within the interstitial fluid, and glucose diffusion through the semipermeable coating of the sensor needle. For this model, a healthy person is considered at rest with average parameters. RESULTS: The simulations performed using the PBSM allow obtaining the glucose transport time from the liver to the sensor needle. In this way, it is possible to reconstruct an accurate dynamic measurement of blood glucose from the measurements in the interstitial fluid of the abdominal subcutaneous adipose tissue. CONCLUSIONS: PBSMs with parameters interpretability illustrate the connection of glucose concentrations in the interstitial fluid with that currently in the blood. Implementing this model in a CGM will result in more reliable measurements of blood glucose levels for T1DM treatment.

A phenomenological-based semi-physical model of the kidneys and its role in glucose metabolism.

The kidneys play an important role in glucose homeostasis in three ways: Via endogenous glucose production from non-carbohydrate precursors (e.g. glutamine, lactate, alanine, glycerol) during both postprandial and post-absorptive states; via glucose filtration and reabsorption by the glomerulus and proximal tubule, respectively; and via glucose utilization and the elimination of its excess in the urine when glucose levels exceed 180mg/dl. The renal release of glucose into the circulation occurs mainly in the renal cortex and results from the glucose phosphorylating capacity of those renal cells, meaning that, cells in the renal cortex can form glucose-6-phosphate. Considering glucose filtration and reabsorption, the kidneys filtrate and reabsorb all circulating glucose, rendering the urine virtually glucose-free in a healthy person. Finally, the kidneys take up glucose from the circulation for energetic self-supply. Besides their role in glucose metabolism, the kidneys are the major site of insulin clearance from the systemic circulation, removing approximately 50% of peripheral insulin. In this regard, insulin clearance by kidneys occurs by degradation in the proximal tubule after being filtered in the glomerulus. All the aforementioned mechanisms affect the glucose concentration levels in the blood, preventing the parametrization of a mathematical model for patients with diabetes mellitus, in the implementation of an artificial pancreas. Aiming for a complete physiological model of the glucose homeostasis, a physiological submodel of the kidneys is presented in a way not described in the literature so far. This submodel is a phenomenological-based semi-physical model with a basic structure rooted in the conservation law and for which the parameters are interpretable. The model's results coincide well with the available clinical data reported for kidney functions associated with glucose and insulin.

Interactive Metabolism, a simple and robust active learning tool that improves the biochemistry knowledge of undergraduate students.

Advances in physiology and other fields are strongly associated with a solid base knowledge of biochemistry and cell metabolism. On the other hand, the complex and abstract nature of metabolic pathways, the traditional lecture method, and other factors made the teaching-learning process of biochemistry a challenging endeavor. To overcome this, we developed and tested a novel active learning tool called Interactive Metabolism (iM-tool). The iM-tool was developed with simple and low-cost materials. We used it for interactive teaching of several metabolic pathways and physiological mechanisms for students enrolled in the Biochemistry subject belonging to different undergraduate courses. The results of evaluation tests showed that the iM-tool significantly (ANOVA, P < 0.01) and consistently improved the biochemistry knowledge of students in classrooms with up to 50 students for 7 different and consecutive academic semesters. A survey intended to mine students' opinions on the tools showed significant satisfaction with the teaching using the iM-tool over traditional lecture-based teaching, and the iM-tool contributed to collaborative learning among students. Therefore, our results showed that the iM-tool improves the biochemistry and cell metabolism teaching-learning process in a more attractive and interactive manner.

Measurement of Axial Strain of Geogrid by Optical Sensors.

In recent years, the technology of optical fibers has rapidly gained ground in many areas of science and industry, including the construction industry. In this article, the technology of optical fibers based on a fiber Bragg grating (FBG) was used to determine tensile forces acting in a basal reinforcement of a scaled down physical model, which included piled embankment and basal reinforcement. Installing FBG sensors on the geogrid made monitoring of axial strains possible, thus allowing determination of the behavior of the basal reinforcement of the piled embankment. On the basis of three tests performed on the physical model, numerical model calibration with the physical model was carried out using the software PLAXIS 3D Tunnel 2.4. The results showed accurate predictions, especially for the low and middle part of the measured deformations where the numerical analysis proposed a solution that can be considered as safe. Installing FBG sensors on biaxial geogrids was a bold idea that was not easy to implement. However, other possibilities have been successfully tested, such as high-frequency measurements of the response of reinforced soil structure under dynamic loading.

Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line's Digital Twin by Using Color Sensor.

This paper deals with the design and implementation of a universal cyber-physical model capable of simulating any production process in order to optimize its logistics systems. The basic idea is the direct possibility of testing and debugging advanced logistics algorithms using a digital twin outside the production line. Since the digital twin requires a physical connection to a real line for its operation, this connection is substituted by a modular cyber-physical system (CPS), which replicates the same physical inputs and outputs as a real production line. Especially in fully functional production facilities, there is a trend towards optimizing logistics systems in order to increase efficiency and reduce idle time. Virtualization techniques in the form of a digital twin are standardly used for this purpose. The possibility of an initial test of the physical implementation of proposed optimization changes before they are fully implemented into operation is a pragmatic question that still resonates on the production side. Such concerns are justified because the proposed changes in the optimization of production logistics based on simulations from a digital twin tend to be initially costly and affect the existing functional production infrastructure. Therefore, we created a universal CPS based on requirements from our cooperating manufacturing companies. The model fully physically reproduces the real conditions of simulated production and verifies in advance the quality of proposed optimization changes virtually by the digital twin. Optimization costs are also significantly reduced, as it is not necessary to verify the optimization impact directly in production, but only in the physical model. To demonstrate the versatility of deployment, we chose a configuration simulating a robotic assembly workplace and its logistics.

A combined experimental and computational approach to evaluate microclimate control at the support surface interface.

Temperature and humidity conditions at the interface between a support surface and the skin, termed microclimate, has been implicated in the development of pressure ulcers. Support surface technologies have been developed to control microclimate conditions, although only a few standard test methods exist to evaluate their performance. This study describes a combined experimental-computational approach to analyzing microclimate control systems. The study used a modified physical model protocol to evaluate two specific support surface systems involving a spacer fabric cover with i) no air flow and ii) an active fan. The physical model deposited moisture at a controlled rate for 25 min, and the microclimate conditions under the model and the surrounding area were monitored for 24 h. Using the experimental data as boundary conditions, a finite element model was developed using mass transport principles, which was calibrated using experimental results. Model inputs included mass density and mass diffusivity, resulting in an estimated absolute humidity change over time. The physical model tests revealed distinct differences between the support surfaces with and without active airflow, with the former having little effect on local humidity levels (RH>75% for 24hr). By contrast, there was a spatial and temporal change in microclimate with the active fan, with sensors positioned towards the source of airflow reaching ambient conditions within 24hr. The computational model was refined to produce comparable results with respect to both the spatial distribution of microclimate and the change in values over time. The combined experimental and computation approach was able to distinguish distinct difference in microclimate change between two support surface designs. The approach could enable the efficient evaluation of different mattress design principles to aid decision making for personalized support surface solutions, for the prevention of pressure ulcers.

Effect of single nanoparticle-nanopore interaction strength on ionic current modulation.

Solid-state nanopores are rapidly emerging as promising platforms for developing various single molecule sensing applications. The modulation of ionic current through the pore due to translocation of the target molecule has been the dominant measurement modality in nanopore sensors. Here, we focus on the dwell time, which is the duration taken by the target molecule or particle to traverse the pore and study its dependence on the strength of interaction of the target with the pore using single gold nanoparticles (NPs) as targets interacting with a silicon nitride (SiN) nanopore. The strength of interaction, which in our case is electrostatic in nature, can be controlled by coating the nanoparticles with charged polymers. We report on an operating regime of this nanopore sensor, characterized by attractive interactions between the nanoparticle and the pore, where the dwell time is exponentially sensitive to the target-pore interaction. We used negatively and positively charged gold nanoparticles to control the strength of their interaction with the Silicon Nitride pore which is negatively charged. Our experiments revealed how this modulation of the electrostatic force greatly affects the dwell time. Positively charged NPs with strong attractive interactions with the pore resulted in increase of dwell times by 2-3 orders of magnitude, from 0.4 ms to 75.3 ms. This extreme sensitivity of the dwell time on the strength of interaction between a target and nanopore can be exploited in emerging nanopore sensor applications.