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Snow and ice on roads often lead to increased rolling resistance that makes roads less accessible and less attractive for cyclists. Introducing a minimum requirement for rolling resistance in winter maintenance of cycleways may increase the attractiveness of winter cycling. To control the rolling resistance level, an objective measurement method is needed. This article presents a new method for measuring rolling resistance for cyclists by using an instrumented bicycle. The new method utilizes measurements of pedaling power and resistive forces from gravitation, acceleration, and air drag to estimate the rolling resistance. Test results show that the method can measure the coefficient of rolling resistance, Crr, with a precision, represented as the standard error of the mean, between ±0.005 (1 Hz, n=9) and ±0.001 (1 Hz, n=220). The accuracy of the method was verified in a test with known rolling resistance and the results yielded a mean accuracy of 96.5%. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) offers a novel approach to supplement traditional surveys and provide increased spatial and temporal information on species detection, and it can be especially beneficial for detecting at risk or threatened species with minimal impact on the target species. The transport of eDNA in lotic environments is an important component in providing more informed descriptions of where and when a species is present, but eDNA transport phenomena are not well understood. In this study, we used species-specific assays to detect eDNA from two federally endangered mussels in two geographically distinct rivers. Using the eDNA concentrations measured from field samples, we developed a one-dimensional (1D) hydrodynamic transport model to predict the downstream fate and transport of eDNA. We detected eDNA from both federally endangered mussels across several seasons and flow rates and up to 3.5 km downstream from the source populations, but the detection rates and eDNA concentrations were highly variable across and within rivers and study reaches. Our 1D transport models successfully integrated the variability of the eDNA field samples into the model predictions and overall model results were generally within ±1 standard error of the eDNA field concentration values. Overall, the results of this study demonstrate the importance of optimizing the spatial locations from where eDNA is collected downstream from a source population, and it highlights the need to improve understanding on the shedding mechanisms and magnitude of eDNA from source populations and biogeomorphic processes that influence eDNA transport. [ABSTRACT FROM AUTHOR]

Ocean mesoscale eddies are often poorly represented in climate models, and therefore, their effects on the large scale circulation must be parameterized. Traditional parameterizations, which represent the bulk effect of the unresolved eddies, can be improved with new subgrid models learned directly from data. Zanna and Bolton (2020), https://doi.org/10.1029/2020gl088376 (ZB20) applied an equation‐discovery algorithm to reveal an interpretable expression parameterizing the subgrid momentum fluxes by mesoscale eddies through the components of the velocity‐gradient tensor. In this work, we implement the ZB20 parameterization into the primitive‐equation GFDL MOM6 ocean model and test it in two idealized configurations with significantly different dynamical regimes and topography. The original parameterization was found to generate excessive numerical noise near the grid scale. We propose two filtering approaches to avoid the numerical issues and additionally enhance the strength of large‐scale energy backscatter. The filtered ZB20 parameterizations led to improved climatological mean state and energy distributions, compared to the current state‐of‐the‐art energy backscatter parameterizations. The filtered ZB20 parameterizations are scale‐aware and, consequently, can be used with a single value of the non‐dimensional scaling coefficient for a range of resolutions. The successful application of the filtered ZB20 parameterizations to parameterize mesoscale eddies in two idealized configurations offers a promising opportunity to reduce long‐standing biases in global ocean simulations in future studies. Plain Language Summary: This research focuses on improving the accuracy of ocean models by addressing the challenges of representing the mesoscale eddies on coarse grids. These eddies play a crucial role in the Earth's climate system, but traditional climate models struggle to capture their effects. Here, we implemented a new data‐driven parameterization simulating the physics of the mesoscale eddies into the state‐of‐the‐art ocean model. The parameterization is interpretable and captures key physical processes related to the mesoscale eddies known as energy backscatter. We tested this parameterization in two idealized ocean scenarios and found that it significantly improves the biases in the representation of the mean state and energetics. We propose new filtering schemes which improve the physical and numerical properties of the parameterization. Accurate representation of the mesoscale eddies by the present scheme has the potential to resolve long‐standing biases present in global ocean models and thus allow for more reliable climate simulations. Key Points: A data‐driven mesoscale eddy parameterization is implemented and evaluated in different configurations of the GFDL MOM6 ocean modelWe introduce filtering schemes to reduce the generation of grid‐scale noise and enhance the large‐scale backscatterThe subgrid parameterization improves the representation of the energy distributions and the climatological mean state [ABSTRACT FROM AUTHOR]

The primary characteristic of ablative materials is their fire resistance. This study explored the development of cost-effective ablative materials formed into application-specific shapes by using a polymer matrix reinforced with ceramic powder. A thermoplastic (polypropylene; PP) and a thermoset (polyester; UPE) matrix were used to manufacture ablative materials with 50 wt% silicon carbide (SiC) particles. The reference composites (50 wt% SiC) were compared to those with 1 and 3 wt% short glass fibers (0.5 mm length) and to composites using a 1 and 3 wt% glass fiber mesh. Fire resistance was tested using a butane flame (900 °C) and by measuring the transmitted heat with a thermocouple. Results showed that the type of polymer matrix (PP or UPE) did not influence fire resistance. Composites with short glass fibers had a fire-resistance time of 100 s, while those with glass fiber mesh tripled this resistance time. The novelty of this work lies in the exploration of a specific type of material with unique percentages of SiC not previously studied. The aim is to develop a low-cost coating for industrial warehouses that has improved fire-protective properties, maintains lower temperatures, and enhances the wear and impact resistance. [ABSTRACT FROM AUTHOR]

A scanning acoustic microscopy (SAM) system is a common non-destructive instrument which is used to evaluate the material quality in scientific and industrial applications. Technically, the tested sample is immersed in water during the scanning process. Therefore, a robot arm is incorporated into the SAM system to transfer the sample for in-line inspection, which makes the system complex and increases time consumption. The main aim of this study is to develop a novel water probe for the SAM system, that is, a waterstream. During the scanning process, water was supplied using a waterstream instead of immersing the sample in the water, which leads to a simple design of an automotive SAM system and a reduction in time consumption. In addition, using a waterstream in the SAM system can avoid contamination of the sample due to immersion in water for long-time scanning. Waterstream was designed based on the measured focal length calculation of the transducer and simulated to investigate the internal flow characteristics. To validate the simulation results, the waterstream was prototyped and applied to the TSAM-400 and W-FSAM traditional and fast SAM systems to successfully image some samples such as carbon fiber-reinforced polymers, a printed circuit board, and a 6-inch wafer. These results demonstrate the design method of the water probe applied to the SAM system. [ABSTRACT FROM AUTHOR]

Gait monitoring using hip joint angles offers a promising approach for person identification, leveraging the capabilities of smartphone inertial measurement units (IMUs). This study investigates the use of smartphone IMUs to extract hip joint angles for distinguishing individuals based on their gait patterns. The data were collected from 10 healthy subjects (8 males, 2 females) walking on a treadmill at 4 km/h for 10 min. A sensor fusion technique that combined accelerometer, gyroscope, and magnetometer data was used to derive meaningful hip joint angles. We employed various machine learning algorithms within the WEKA environment to classify subjects based on their hip joint pattern and achieved a classification accuracy of 88.9%. Our findings demonstrate the feasibility of using hip joint angles for person identification, providing a baseline for future research in gait analysis for biometric applications. This work underscores the potential of smartphone-based gait analysis in personal identification systems. [ABSTRACT FROM AUTHOR]

Simulation of the flow in a Pelton turbine is a challenging task for mesh based methods due to the air/water mixture and the rotation of the runner. Meshless based methods are better suited for such flows and take advantage of the graphical power unit to speed up the calculation. Simulations of a Pelton turbine are carried out using the software Particleworks based on moving particle simulation, which is a meshless method. The efficiency drop due to the 'falaise' effect and the erosion of the splitter are computed and compared with either experimental measurements or the literature. The results show that this method is able to capture the tendency of the efficiency drop in agreement with the available data and at a lower computational cost than the mesh based methods. These encouraging results should motivate the community to test and validate such an approach. [ABSTRACT FROM AUTHOR]

This study provided a comprehensive understanding of the source process of the 1819 M 7.7 Kachchh Indian earthquake using physics‐based dynamic rupture modeling and strong ground motion simulations. We successfully simulated the spontaneous dynamic rupture along a curved non‐planar fault using the 3‐D curved‐grid finite‐difference method (CGFDM). The estimated earthquake magnitude is around 7.6, consistent with previous estimations. Our simulations accurately replicated macroscopic rupture patterns and surface deformation, showing agreement with observed data along the Allah Bund fault (ABF) with a maximum displacement ∼5.5 m at the Earth's surface. The maximum modeled coseismic slip on the fault was approximately 7.5 m. Notably, the ABF exhibited characteristics of a weak barrier (leaky barrier) at the bending part, allowing the rupture to propagate further. Despite limitations in surface deformation calculations, the modeled values aligned with the trend of surface fault slip, with a slight deviation in the epicenter toward the east compared to earlier studies. We observed a homogeneous principal stress oriented N25°E, consistent with the present day Indian plate motion. The estimated horizontal peak ground velocities (PGVh) and the maximum value of Intensity X+ aligns well with observations. Furthermore, conducting thorough case studies on significant earthquakes and potential seismic scenarios in stable continental regions is crucial. Such studies play a vital role in validating and improving dynamic rupture models. When combined with statistical methods, this research holds great promise for advancing seismic hazard assessments, earthquake engineering, and strategies for disaster management. Plain Language Summary: This paper is centered around the simulation of the dynamic rupture of the 1819 M 7.7 Kachchh earthquake in India. We have successfully replicated the earthquake's behavior using a three‐dimensional simulation method. The study's results demonstrate the significant influence of the local tectonic setting and non‐planar fault structure on earthquake generation and rupture progression. Although slight discrepancies exist between the simulation results and actual observations, the simulations capture significant trends and reproduce macroscopic rupture patterns. The estimated magnitude of the earthquake aligns well with previous studies. The study highlights the role of fault bending and its impact on surface deformation, contributing to a better understanding of seismic hazards and providing insights for seismic hazard assessments and earthquake source characterization. This work is valuable for comprehending earthquake sources, particularly from earthquake perspectives in the SCR region and other areas. Key Points: Dynamic rupture simulations of the 1819 Kachchh M 7.7 earthquake replicate co‐seismic fault slip, enhance our knowledge of the earthquake sourceWeak barrier characteristics observed at the bending part of the fault enabled further rupturing, influenced by SH and the nucleation pointContributes to understanding earthquake hazards, enhancing seismic assessment, engineering, and disaster management strategies [ABSTRACT FROM AUTHOR]

Underground transportation systems often involve multiple tunnels constructed closely together. Previous studies mainly focus on interaction between circular tunnels; by contrast, interaction mechanisms involving non-circular tunnels are not well understood. In this study, four physical three-dimensional centrifuge tests were performed in dry sand, simulating the response of existing circular and horseshoe-shaped tunnels to a newly excavated tunnel. Two different ratios between pillar depth and tunnel diameter (P/D) of 0.5 and 2.0 were considered. Furthermore, three-dimensional numerical back-analyses considering small-strain stiffness were undertaken. Results reveal that the ground settlement above an existing horseshoe-shaped tunnel is less sensitive to pillar depth than for circular ones. Furthermore, for P/D = 0.5, the existing horseshoe-shaped tunnel experiences both vertical and horizontal compression; more stress reduction occurs vertically than horizontally. A circular tunnel for the same pillar depth becomes compressed vertically but elongated horizontally; stress reduction around the existing circular tunnel is less vertically than horizontally. However, for P/D = 2.0, both types of tunnel become elongated vertically and compressed horizontally because of a larger reduction in vertical stresses than horizontal ones. These results demonstrate that both pillar depth and shape profoundly affect tunnel deformation mechanisms. [ABSTRACT FROM AUTHOR]

In river research, forecasting flow velocity accurately in vegetated channels is a significant challenge. The forecasting performance of various independent and hybrid machine learning (ML) models are thus quantified for the first time in this work. Utilizing flow velocity measurements in both natural and laboratory flume experiments, we assess the efficacy of four distinct standalone machine learning techniques—Kstar, M5P, reduced error pruning tree (REPT) and random forest (RF) models. In addition, we also test for eight types of hybrid ML algorithms trained with an Additive Regression (AR) and Bagging (BA) (AR-Kstar, AR-M5P, AR-REPT, AR-RF, BA-Kstar, BA-M5P, BA-REPT and BA-RF). Findings from a comparison of their predictive capabilities, along with a sensitivity analysis of the influencing factors, indicated: (1) Vegetation height emerged as the most sensitive parameter for determining the flow velocity; (2) all ML models displayed outperforming empirical equations; (3) nearly all ML algorithms worked optimal when the model was built using all of the input parameters. Overall, the findings showed that hybrid ML algorithms outperform regular ML algorithms and empirical equations at forecasting flow velocity. AR-M5P (R2 = 0.954, R = 0.977, NSE = 0.954, MAE = 0.042, MSE = 0.003, and PBias = 1.466) turned out to be the optimal model for forecasting of flow velocity in vegetated-rivers. [ABSTRACT FROM AUTHOR]

The Fermi bubbles and the eROSITA bubbles around the Milky Way Galaxy are speculated to be the aftermaths of past jet eruptions from a supermassive black hole in the galactic center. In this work, a 2.5D axisymmetric relativistic magnetohydrodynamic (RMHD) model is applied to simulate a jet eruption from our galactic center and to reconstruct the observed Fermi bubbles and eROSITA bubbles. High-energy non-thermal electrons are excited around forward shock and discontinuity transition regions in the simulated plasma distributions. The γ -ray and X-ray emissions from these electrons manifest patterns on the skymap that match the observed Fermi bubbles and eROSITA bubbles, respectively, in shape, size and radiation intensity. The influence of the background magnetic field, initial mass distribution in the Galaxy, and the jet parameters on the plasma distributions and hence these bubbles is analyzed. Subtle effects on the evolution of plasma distributions attributed to the adoption of a galactic disk model versus a spiral-arm model are also studied. [ABSTRACT FROM AUTHOR]

This study numerically investigates mixed convective cooling in a two‐dimensional horizontal channel containing periodically heated blocks by applying proportional (P), proportional‐integral (PI), and proportional‐integral‐derivative (PID) controllers. Three different controller configurations regulate the amount of cold air entering the chamber. The air's non‐dimensional temperature is continuously monitored at the set point to compare the controllers' performance, and the percentage of overshoot and the steady‐state error are analysed. The investigated chamber comprises one inlet and two exit ports, a temperature sensor, and two heated blocks that are isotherm heat sources. The Galerkin finite element approach computationally solves the equations of continuity, momentum, and energy to analyse the thermo‐fluid phenomena occurring within the chamber. Parametric simulation is carried for different values of the proportional gain (Kp = 0.005, 0.010, 0.050 m s−1 K−1), the integral gain (Ki = 0.05, 0.10, 0.15 m s−2 K−1), the derivative gain (Kd = 10−5, 10−4, 10−3 m K−1) to achieve a consistent and expeditious response. Variations of Reynolds, Richardson, and mean Nusselt numbers with time are plotted to compare the system's performance. The investigation indicates that the PI controller produces a comparable level of performance with the PID controller, reducing the necessity to add a derivative controller. [ABSTRACT FROM AUTHOR]

IPCBs (Intelligent Pseudolite Constellations based on high-altitude balloons) are a novel type of air-based pseudolite application with many advantages. Compared with ground-based pseudolites and traditional air-based pseudolites, IPCBs have a wider coverage and a lower energy requirement. Compared with LEO satellite constellations, IPCBs have a stronger signal, a lower cost, and a shorter deployment period. These merits give promising potential to IPCBs. In IPCB applications, one of the key factors is geometry configuration, which is deeply influenced by the balloon's unique features. The basic idea of this paper is to pursue a strategy to improve IPCB geometry performance by using diverse winds at different altitudes and balloons' capability of altering flight altitude intelligently. Starting with a brief introduction to IPCBs, this paper defines an indicator to assess IPCB geometry performance, an approach to adjust IPCB geometry configuration and an IPCB geometry configuration planning algorithm. Next, a series of simulations are implemented with an IPCB composed of six pseudolites in winds with/without a quasi-zero wind layer. Some IPCB geometry configurations are analyzed, and their geometry performances are compared. Simulation results show the effectiveness of the proposed algorithm and the influence of the quasi-zero wind layer on IPCB performance. [ABSTRACT FROM AUTHOR]

The classifier is an essential tool for the development of contemporary engineering technology. The application of classifiers is to categorize mixed-sized particles into multi-stage uniform particle sizes. In current studies, the particles in the classifier obtain their initial velocity when feeding. The classification effect is impacted by the inability to precisely control the initial state of the particles. To solve this problem, a pusher feed classifier was designed in this study, and a numerical simulation was performed to investigate its flow field characteristics and classification performance using the RNG-DPM method. A pusher is utilized to achieve particle feeding without initial velocity and to precisely control the initial state of the particles in the classification flow field. A newly developed two-way air inlet structure is designed to provide a superimposed flow field and enable the five-stage classification. Our results show that this pusher feed classifier has the best classification effect when the vertical airflow velocity is 10 m/s and the horizontal airflow velocity is 3 m/s. Meanwhile, the classification size ratio (CSR) from outlet 1 to outlet 5 was 1.24, 0.55, 0.45, 0.39, and 0.15, respectively. [ABSTRACT FROM AUTHOR]

The brushless direct current motors have gained popularity among the emerging technologies due to their increased efficiency, speed of operation, and density of flux. This paper presents a novel technique for controlling the speed of the brushless direct current motor by using hybrid algorithms. The Particle Swarm Optimization (PSO) algorithm is combined with the Takagi Sugeno adaptive fuzzy interference system and gravitational search algorithms to analyze the speed control of the brushless DC electric motor (BLDC) motors. The proposed model has designed multiple outputs prototype for BLDC motor with Takagi Sugeno fuzzy logic. Since the adaptive fuzzy logic system has three outputs, the final output is evaluated as the average value of all the outputs using the LMS algorithm. The speed control of the Brushless DC motor has also been analyzed using a combination of the gravitational search algorithm and the PSO algorithm. The motor parameters taken under consideration for the analysis have been tabulated. The different results obtained at the end of this study have been demonstrated through graphs and tables. [ABSTRACT FROM AUTHOR]

Marine animals equipped with sensors provide vital information for understanding their ecophysiology and collect oceanographic data on climate change and for resource management. Existing methods for attaching sensors to marine animals mostly rely on invasive physical anchors, suction cups, and rigid glues. These methods can suffer from limitations, particularly for adhering to soft fragile marine species such as squid and jellyfish, including slow complex operations, unreliable fixation, tissue trauma, and behavior changes of the animals. However, soft fragile marine species constitute a significant portion of ocean biomass (>38.3 teragrams of carbon) and global commercial fisheries. Here we introduce a soft hydrogel-based bio-adhesive interface for marine sensors that can provide rapid (time <22 s), robust (interfacial toughness >160 J m−2 ), and non-invasive adhesion on various marine animals. Reliable and rapid adhesion enables large-scale, multi-animal sensor deployments to study biomechanics, collective behaviors, interspecific interactions, and concurrent multi-species activity. These findings provide a promising method to expand a burgeoning research field of marine bio-sensing from large marine mammals and fishes to small, soft, and fragile marine animals. [ABSTRACT FROM AUTHOR]

To better understand processes involved in the evaporative drying of the soil, simulations on the dynamics of the evaporation zone, condensation zone, and dry surface layer (DSL) were conducted during a 10-day drying event under diurnal atmospheric conditions. Simulated water contents and soil temperatures matched well with the measured data in the lysimeter. Surface evaporation predominantly occurred during the early period each day, while subsurface evaporation dominated during the remaining part of the day. The evaporation zone presented a distinctly diurnal pattern, moving toward the deeper soil layer during the daytime and back toward the soil surface during the nighttime. The DSL and condensation zone, located immediately above and below the evaporation zone, respectively, also presented diurnal patterns following those of the evaporation zone. As soil drying progressed, both the position of the evaporation zone within the profile and the DSL width exhibited an overall increasing trend, reaching about 4.9 mm by the end of the study period. The occurrence of condensation zones was limited to the daytime when there was a downward surface temperature gradient present. Diurnal patterns observed in both evaporation zones and DSL could potentially be determined by quantifying changes in the near-surface profile's soil water content, relative humidity, pressure head, and vapor density. [ABSTRACT FROM AUTHOR]

To improve the cushioning performance of soft-landing systems, a novel origami-inspired combined cushion airbag is proposed. The geometry size, initial pressure, and exhaust vent area of the cushion airbags are designed preliminarily using a theoretical model. The finite element models, including the returnable spacecraft and cushion airbags, are established via the control volume method (CVM) to analyze the impact dynamic behavior and cushioning performance during the landing attenuation process. The cushioning performance of the cushion airbags in complex landing environments are studied to investigate the influence of horizontal velocity, lateral velocity and nonhorizontal landing surfaces. Four design parameters of the cushion airbags, including the initial pressure, venting threshold pressure, exhaust vent area and polygon edge number, are employed to study their influence on the cushioning performance. A multi-objective optimization model of the cushion airbags based on the neural network and multi-objective water cycle algorithm is established to realize the rapid optimization design. The Pareto front of the maximum overload and specific energy absorption is obtained. The analysis results show that the maximum overload of the proposed combined cushion airbags is 7.30 g. The system with the anti-rollover design can avoid rollover and achieve outstanding cushioning performance in complex landing environments. The maximum overload of the returning spacecraft is decreased by 16.4% from 7.30 g to 6.10 g after multi-objective optimizations. This study could provide the technical support for the soft-landing system design of returnable spacecrafts. [ABSTRACT FROM AUTHOR]

Characteristics of the sensitive unit of the aerogravimetric complex GT-1A (GT-2A) are examined on the basis of experimental material obtained during aerogravimetric surveys. The stability of the zero-point drift of this sensitive unit, the function of the approximation of zero-point drift, the stability of the initial indications on a particular airdrome reference point and the correspondence between the difference in initial readings at different airports and that of gravitation acceleration values according to the first-order State gravimetric network data are discussed. [ABSTRACT FROM AUTHOR]

The recent study is focused on discussion of heat transfer and magnetic field results of peristaltic flow of Rabinowitsch fluid model in an Inclined Channel. In this piece of research, peristalsis's fundamental problem with heat transfer in the presence of a magnetic field is checked. An incompressible Rabinowitsch fluid is present in an inclined channel, which is considered as the reference for this research. The solutions are devised with the assumptions of long wavelength and low Reynolds number approximations. The resulting equations are then solved exactly by implementing various command of MATHEMATICA subject to relevant boundary conditions. Results are discussed for various flow quantities like temperature, velocity, tangential stress, pressure gradient and rise, and friction force. Computational simulations are performed to determine the flow quantities. This investigation goes beyond mere calculations and examines particle motion to gain deeper insights into flow quantities. Furthermore, this investigates how magnetic field and heat transfer parameters influence these peristaltic flow phenomena. The outcomes of important parameters were plotted and scrutinized. There is amultitude of medical implementations derived from the current consideration, such as the depiction of the gastric juice motion in the small intestine when an endoscope is inserted through it. [ABSTRACT FROM AUTHOR]

A high-performance H2 gas sensor system based on capacitive electrodes and a volumetric analysis technique were developed. Coaxial capacitive electrodes were fabricated by placing a thin copper rod in the center and by adhering a transparent conductive film on the exterior surface of a graduated cylinder. Thus, H2 from a polymer specimen lowered the water level in the cylinder between the two electrodes, producing measurable changes in capacitance that allowed for the measurement of the H2 concentration emitted from the specimen enriched by H2 under high-pressure conditions. The sensing system detected diffused/permeated hydrogen gas from a specimen and hydrogen gas leaks caused by imperfect sealing. The hydrogen gas sensor responded almost instantly at 1 s and measured hydrogen concentrations ranging from 0.15 to 1500 ppm with controllable sensitivity and a measurable range. In addition, performance tests with polymer specimens used in hydrogen infrastructure verified that the sensor system was reliable; additionally, it had a broad measurement range to four decimal places. The sensor system developed in this study could be applied to detect and characterize pure gases (He, N2, O2 and Ar) by real time measurement. [ABSTRACT FROM AUTHOR]

This research investigates the double tracking control problem for the complex dynamic network (CDN) with an unavailable link state. Firstly, from the angle of a large-scale system, the dynamical model of CDN is described by the vector differential equations, which consists of node dynamic subsystem (NDS) and link dynamic subsystem (LDS), in which the weighted-values of links are regarded as the state variables of LDS. Secondly, to realise the double tracking control (DT-Control) of CDN, the presented DT-Control scheme in this paper includes the synthesis of controller for NDS and the coupling term in LDS, which can ensure that the two subsystems track the given reference targets. The tracking of NDS contains the synchronisation of nodes as the special case, and the tracking of LDS shows that the eventual topologic structure of CDN will be determined only by the given link reference signal. Due to the economic and technological limitations of sensors in the practice applications, this paper assumes that the state variables of LDS are unavailable in the DT-Control scheme. Finally, the engineering simulation example is given to verify the validity of DT-Control scheme proposed in this paper. [ABSTRACT FROM AUTHOR]

The natural convection from a vertical hot plate with radiation and constant flux is studied numerically to know the velocity and temperature distribution characteristics over a vertical hot plate. The governing equations of the natural convection in two-dimension are solved with the implicit finite difference method, whereas the discretized equations are solved with the iterative relaxation method. The results show that the velocity and the temperature increase along the vertical wall. The influence of the radiation parameter in the boundary layer is significant in increasing the velocity and temperature profiles. The velocity profiles increase with the increase of the radiation parameter. The temperature profiles near the wall plate parallel each other due to the constant heat flux applied to the wall. The influence of the radiation parameter is significant either in velocity or temperature characteristics. At the same time, the effect of the Prandtl number greater than 0.71 is not sensitive to the velocity and temperature variations elsewhere. [ABSTRACT FROM AUTHOR]

In this paper, the effect of magnetic field on two ephase flow of Jeffrey and non-Jeffrey fluids in an inclined medium is investigated. The flow in both medium is assumed to be set in motion by constant pressure gradient. The electrical conductivity in the non-Jeffrey fluid in phase I is considered to be zero, so that the constant magnetic field strength Bo in the transverse direction only affects the Jeffrey fluid in phase II. The equations governed the flow of the fluid were solved using perturbation method. The effect of magnetic field, Jeffrey and thermal slip parameters on the temperature and velocity profile were examined through several graphs. It is noticed that the increase in magnetic field, decreased the fluid velocity and increased the temperature profile in phase II while it has partial effect in the velocity and decreased the temperature of phase I. Also, the increase in the thermal slip parameter has no effect on the velocity of both phases but, decreased the temperature profile of the non-Jeffrey fluid in phase I and increased that of the Jeffrey fluid in phase II. [ABSTRACT FROM AUTHOR]

We present the theoretical argument that the use of mathematics in physics can be productively conceptualized as using a language and that learning to make sense of physics equations and appropriating them into novel scientific inquiry can be understood as a process of learning to read fluently with a high level of reading comprehension and to express one's thoughts in writing. The data are drawn from a longitudinal ethnographic account of a high school student's year-long research apprenticeship, in which a significant part of the work required the derivation and interpretation of an advanced physics equation (the phase velocity of waves in liquids). The analysis examines in different timescales the extended learning process as a complex activity system. The findings illustrate empirically how this type of learning can be productively analyzed by researchers and instructionally implemented by teachers or mentors as engagement in practices, a perspective that complements more standard cognitivist accounts of mathematical sensemaking. We highlight productive pedagogical and discursive instructional moves that facilitated this process and explicitly connect them to the learning they induced in terms of change in the student's participation. While constrained by the scope of this case study, the concrete, microanalytic account of the learning process concretizes some of what physicists do with equations and suggests pathways to teaching students to meaningfully participate in this practice. [ABSTRACT FROM AUTHOR]

Optimization is a common phenomenon that we encounter in our daily routine, which involves selecting the best option from a set of alternatives. A lot of algorithms have been developed, including metaheuristics algorithms, which aim to find solutions close to optimal to solve optimization problems. Many metaheuristic algorithms have been inspired by the behavior of natural phenomena, animals, and biological sciences. This paper proposes a novel nature-based metaheuristic optimization algorithm called Adaptive Fox Optimization (AFOX) Algorithm, which is inspired by the hunting behavior of foxes. The proposed algorithm enhances the FOX algorithm by balancing the exploration and exploitation phases, speeding up convergence to the global solution, and avoiding local optima. The efficacy of the AFOX algorithm was tested on eight classical benchmark functions, the functions of CEC2018, and the functions of the CEC2019 Benchmarks. Moreover, AFOX was applied to solve real-world optimization problems, such as prediction and engineering design problems, and compared with a wide range of metaheuristic algorithms such as variant versions of FOX, the Dragon-Fly Algorithm, particle swarm optimization, Fitness Dependent Optimizer, Grey Wolf Optimization, Whale Optimization Algorithm, Chimp Optimization Algorithm, Butterfly Optimization Algorithm, and Genetic Algorithm. The results demonstrate the effectiveness of the AFOX algorithm in finding optimal solutions with higher accuracy and faster convergence. Thus, the AFOX algorithm is deemed to be highly efficient in solving real-world optimization problems with accuracy and speed. [ABSTRACT FROM AUTHOR]

River bank erosion of alluvial rivers is one of the major challenges for river management. This paper deals with the prediction of the fluvial erosion rate along the left bank of Jamuna River in Bangladesh using the excess shear stress method. Surface water modelling systems i.e. SMS and SRH-2D, were used to estimate the hydrodynamic effects on the riverbank along the 8.21 km reach of the river. Riverbank along the selected reach of Jamuna River consists of two layers of soil type. The upper layer soil is sandy silt with a median size of D50 = 0.028 mm and the bottom layer is silty sand with D50 = 0.167 mm. Results of the present analysis show that shear stress along the riverbank attains its maximum and initiates the bank erosion, when the flow rate is about 45,000 m3/s. Based on the results obtained from model run and empirical analysis, riverbank materials have been categorized as 'erodible' to 'very erodible', as far as erodibility parameters are concerned. Critical shear stress of bank soil is found to be varied between 0.15 and 0.22 Pa using erodibility co-efficient ranges between 5.05 and 6.03 cm3/N s. From this study, the maximum bank erosion rates have been estimated as 51.95 m/year to 69.82 m/year. However, average erosion rates have been estimated which range between 38.65 and 40.57 m/y. It is hoped that the results obtained from the study will be helpful in determining the riverbank stability for the implementation of appropriate river protective measures along the riverbank of Jamuna River. [ABSTRACT FROM AUTHOR]

In recent years, levitated particles of optical traps in vacuum have shown the enormous potential for precision sensor development and new physics exploration. However, the accuracy of the sensor is still hampered by the uncertainty of the calibration factor relating the detected signal to the absolute displacement of the trapped particle. In this paper, we suggest and experimentally demonstrate a novel calibration method for optical tweezers based on free-falling particles in vacuum, where the gravitational acceleration is introduced as an absolute reference. Our work provides a calibration protocol with a great certainty and traceability, which is significant in improving the accuracy of precision sensing based on levitated optomechanical systems. [ABSTRACT FROM AUTHOR]