Miracle-dz/UniFAR-FTUs huggingface dataset:
Tissue-Level Regeneration and Remodeling Dynamics are Driven by Mechanical Stimuli in the Microenvironment in a Post-Bridging Loaded Femur Defect Healing Model in Mice

Bone healing and remodeling are mechanically driven processes. While the generalized response to mechanical stimulation in bone is well-understood, much less is known about the mechanobiology-regulating tissue-scale bone formation and resorption during the reparative and remodeling phases of fracture healing. In this study, we combined computational approaches in the form of finite element analysis and experimental approaches by using a loaded femoral defect model in mice to investigate the role of mechanical stimulation in the microenvironment of bone. Specifically, we used longitudinal micro-computed tomography to observe temporal changes in bone at different densities and micro-finite element analysis to map the mechanics of the microenvironment to tissue-scale formation, quiescence (no change in bone presence between time points), and resorption dynamics in the late reparative and remodeling phases (post bridging). Increasing levels of effective strain led to increasing conditional probability of bone formation, while decreasing levels of effective strain led to increasing probability of bone resorption. In addition, the analysis of mineralization dynamics showed both a temporal and effective strain level-dependent behavior. A logarithmic-like response was displayed, where the conditional probability of bone formation or resorption increased rapidly and plateaued or fell rapidly and plateaued as mechanical strain increased.
Theme-Based Block Play Intervention Facilitates Chinese Preschoolers’ Language Development: A Quasi-Experiment

This study investigated the role of theme-based blocks play in enhancing Chinese children’s language capacity with a quasi-experiment. Altogether 61 young children were assigned to the experiment group (Mage = 5.83, SD = 0.25, 56.25% girls) and the control group (Mage = 5.87, SD = 0.28, 51.72% girls). The experiment group was engaged in a 12-week theme-based block play intervention programs, whereas the control group received no interventions but free block play during the parallel time sessions. All the children were tested with the Language Assessment for Preschool Children (LAPC) before and after the intervention. The ANCOVA results indicated that the experimental group significantly improved in LAPC test, whereas the control group showed no significant change. The educational implications of these findings are discussed.
A Comparison of Plyometric and Jump Rope Training Programs for Improving Punching Performance in Junior Amateur Boxers

Improving lower extremity sports performance may contribute to punching performance in boxers. We compared the effects of two typical boxing routines for developing lower extremity sports performance and subsequent punching performance. Twenty-four high school amateur boxers between the ages of 12 and 18 performed training at least 3 days per week. All Athletes had 3–5 years of experience in boxing training. The participants separated into two groups to receive an 8-week plyometric or jump rope training program. They performed each training program for 30 min on 3 days/week. Lower extremity sports performance in countermovement jump (leg stiffness, jump power, and rate of force development) and jab-cross punching performance (punch velocity, punch force, reaction time, movement time, and ground reaction force) were assessed at pre-and post-training. The data were analyzed using a two-way mixed-design analysis of variance (ANOVA) (group × time). Both training programs improved the rate of force development in countermovement jump, the reaction time of punch, the peak ground reaction force of the rear leg during the jab punch, and the velocity of the jab punch. There were no group differences and interaction effects in all variables analyzed. It is concluded that 8 weeks of plyometric and rope jumping programs had a similar impact on improving lower extremity strength and punching performance. Both training programs may improve muscle strength and power, rate of force development, and reaction time. These improvements may contribute to lower extremity strength for driving a punch at the target with excellent performance.
Intelligent Traffic Monitoring System through Auto and Manual Controlling using PC and Android Application

Traffic congestion in cities is a major problem mainly in developing countries. In order to counter this, many models of traffic systems have been proposed by different scholars. Different ways have been proposed to make the traffic system smarter, reliable and robust. A model is proposed to develop an Intelligent Traffic Monitoring System (ITMS) which uses infrared proximity sensors and a centrally placed microcontroller and uses vehicular length along a lane to implement auto controlling of the traffic. The model also provides mean to control the traffic manually through a PC software and an Android application.
Improving the signal processing path for online heartbeat estimation by using Ultra Wideband radar

A number of companies, research establishments and universities worldwide are currently researching the use of Ultra Wideband radar technology to conduct non-contact and non-invasive measurements of heartbeat. Both cardiac and respiratory activity cause a visible and measurable motion to the chest wall. When aiming a radar to a subject's chest, this motion can be recorded and processed to obtain the rates of respiration and heartbeat. This thesis looks into the processing of chest wall displacement data to improve heart rate measurements. At the rst stage of the signal processing, the low frequency, high amplitude respiration signal component must be separated from the much smaller heartbeat component. Traditionally, linear Finite Impulse Response (FIR) highpass lters have been used to remove the respiration component. FIR lters have a xed corner frequency. If the respiration rate is higher than this xed frequency, FIR ltering can not work. In addition, FIR lters must be quite long for su cient stopband attenuation, and thus they introduce a time delay to the system. Alternative signal processing techniques are based on cancellation of respiration harmonics, which eliminates the system delay and works at any respiration frequency. One such method from the literature was investigated, and this thesis presents a modi ed version that works better with actual radar data. After separation, the heart rate must be determined. Traditionally, frequency estimation of a sliding window has been used. A di erent method from the literature is based on adaptive ltering. It transforms the heartbeat signal into a train of unit pulses, each occurring at the start of a heartbeat. Instant heartbeat information is thus gathered, as opposed to the traditional method which yields the mean heart rate during the time window. Some system results were obtained for both constructed test signals and actual radar data. Generally FIR ltering performed better than harmonic cancellation, but the harmonic canceller outperformed FIR ltering when the respiration frequency tended towards the lter's corner frequency. Feasibility of a system that gives instant heart rate measurements in real-time was proven. The improvements on traditional systems are elimination of time delay, enabling separation at high respiration frequencies and giving the instant heart rate rather than an avereraged one.
Narrowing the LOCAL-CONGEST Gaps in Sparse Networks via Expander Decompositions

Many combinatorial optimization problems, including maximum weighted matching and maximum independent set, can be approximated within (1 ± ε) factors in poly(log n, 1/ε) rounds in the LOCAL model via network decompositions [Ghaffari, Kuhn, and Maus, STOC 2018]. These approaches, however, require sending messages of unlimited size, so they do not extend to the more realistic CONGEST model, which restricts the message size to be O(log n) bits. For example, despite the long line of research devoted to the distributed matching problem, it still remains a major open problem whether an (1-ε)-approximate maximum weighted matching can be computed in poly(log n, 1/ε) rounds in the CONGEST model. In this paper, we develop a generic framework for obtaining poly(log n, 1/ε)-round (1 ± ε)-approximation algorithms for many combinatorial optimization problems, including maximum weighted matching, maximum independent set, and correlation clustering, in graphs excluding a fixed minor in the CONGEST model. This class of graphs covers many sparse network classes that have been studied in the literature, including planar graphs, bounded-genus graphs, and bounded-treewidth graphs. Furthermore, we show that our framework can be applied to give an efficient distributed property testing algorithm for an arbitrary minor-closed graph property that is closed under taking disjoint union, significantly generalizing the previous distributed property testing algorithm for planarity in [Levi, Medina, and Ron, PODC 2018 & Distributed Computing 2021]. Our framework uses distributed expander decomposition algorithms [Chang and Saranurak, FOCS 2020] to decompose the graph into clusters of high conductance. We show that any graph excluding a fixed minor admits small edge separators. Using this result, we show the existence of a high-degree vertex in each cluster in an expander decomposition, which allows the entire graph topology of the cluster to be routed to a vertex. Similar to the use of network decompositions in the LOCAL model, the vertex will be able to perform any local computation on the subgraph induced by the cluster and broadcast the result over the cluster.
The Mobile Handset Industry in Transition: The PC Industry Revisited? Understanding the drivers of dynamic change and implications for firm strategy

Abstract This article supports and extends upon other scholars’ examinations of the evolution of technological modularity, vertical specialization and the concepts of the drivers of change in the basis of competition through an analysis of the evolution of the mobile handset industry. It is the thesis of this article that the mobile handset industry value chain is in the process of deconstructing towards more horizontally stratified structures for some device segments. But unlike the PC industry, an industry which some researchers suggest provides a precedent for likely evolution of the mobile handset value chain, this trend will not be uniform or consistent across different product types. This will require mobile phone manufacturers to adapt their organisational structures and value chain approaches accordingly, and to rethink the basis for future competitive advantage. Keywords: Deconstruction, vertical integration, modularity, technological change, mobile phone, cellular phone JEL Classifications:
Scannende Infrarotdeflektometrie für die Inspektion diffus spiegelnder Oberflächen

Zusammenfassung Unter Infrarotdeflektometrie versteht man die Anwendung des Messprinzips der Deflektometrie im thermischen Infrarotspektrum. Dadurch lässt sich ausnutzen, dass vor allem raue, metallische Oberflächen in diesem Spektrum spiegelnd erscheinen und so eine deflektometrische Inspektion ermöglicht wird. Diese Arbeit befasst sich mit dem Problem der Erzeugung der notwendigen thermischen Codemuster und deren Auswertung. Es werden verschiedene Ansätze vorgestellt, um Oberflächen mit Hilfe eines Industrieroboters oder im Durchlauf zu inspizieren. Darüber hinaus wird zur Auswertung der Muster zu einer Registrierung ein neues Verfahren vorgestellt. Die Ergebnisse werden an praktisch relevanten Beispielen demonstriert.
A Multiscale Recurrent Neural Network Model for Long-Term Prediction of Geothermal Energy Production

Management and optimization of energy recovery from geothermal reservoirs rely on accurate prediction of energy production performance for alternative development scenarios. While physics-based reservoir simulation models are traditionally used as a comprehensive approach to predict the response of geothermal reservoirs to different production strategies, data-driven models can serve as efficient fit-for-purpose tools for rapid evaluation and screening of alternative production and development plans as well as for facilitating daily operation and surveillance decisions. We evaluate the use of recurrent neural networks (RNN), as machine learning architectures for representation and prediction of sequential/dynamic data, for long-term prediction of geothermal energy production. As a universal approximator that can capture complex and nonlinear trends in data, RNN has enjoyed great success in many applications. Since RNN primarily exploits statistical relations in training data to generate predictions, it can be challenged in applications where extrapolation beyond the training data range is needed. We explore new RNN architectures and training approaches to improve its generalization power for long-term prediction of geothermal reservoir performance. Since historical monitoring and performance observations in geothermal fields contain short-term and long-term patterns, we develop multiscale RNN architectures and the corresponding training implementations to learn both short-term and long-term trends in the data and use them for future predictions. We present the developed architecture and training process and show its application to simulated datasets from a field-scale model.
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE TPS DI SMA NEGERI 12 BANDA ACEH

Students are studying subjects that are required to play an active role in learning activities. The way that can be done to enable such students through the implementation of cooperative learning model, one of which is TPS. TPS application of cooperative learning in the learning of chemistry can stimulate students to express opinions or ideas, mutual cooperation, respect the opinions of others, helping to solve problems and develop students' creativity. Active student involvement in learning will lead to learning motivation that will have an impact on the improvement of learning outcomes
STROBE: The relationship between asthma and early menarche in Korean adolescents

Abstract We explored the relationship between asthma and early menarche in a representative sample of Korean adolescents. Web-based self-reported data collected from 2006 to 2015 by the Korean Youth Risk Behavior Web-based Survey were used. Menarche status was divided into “early” (<12 years of age, n = 69,520) and “not early” (≥12 years of age, n = 234,065). Adolescent girls with early menarche exhibited a higher incidence of asthma (8.1% vs 7.4%, P < .001), more frequent school absences because of asthma (10.8% vs 8.7%), and more frequent ≤4-day stretches of school absence (4.6% vs 2.4%) compared with girls with “not early” menarche (all P < .001). Multivariate analysis performed after adjusting for multiple confounders revealed a 1.04-fold (95% confidence interval [CI] 1.00–1.07) greater likelihood of asthma in the early menarche than not early menarche group. In addition, the odds ratios for missing school due to asthma for 1 to 3 and ≥4 days per year in the early menarche group were 1.00 (95% CI 1.00–1.02) and 1.21 (95% CI 1.01–1.46), respectively. Adolescents with early menarche exhibited increased incidences of asthma and severe asthma.
EUV Optical Testing

The goal of creating lithographic-quality EUV imaging systems has pushed researchers to develop the most accurate wavefront aberration measurement techniques ever created. During the development of EUV lithography (EUVL) technology, at-wavelength optical testing has proven valuable as a tool for understanding chromatic aberrations and multilayer (ML) influences on performance, and also as a highly deterministic independent measurement for comparison with visible-light interferometry. Because of the perceived trade-offs among complexity, cost, and necessity, no universal conclusion has yet been reached on the role at-wavelength testing will play as EUVL transitions to production. EUV interferometric measurements have achieved accuracy levels of 0. 4â1.0 A rms for primary aberration terms (verified by lithographic imaging), with state-of-the-art visible-light testing methods only slightly behind. Measurement precision levels have been higher still, with researchers claiming uncertainty levels on the order of 0.05 A rms or below. But precision and accuracy are separate concerns: precision relies only on the measurement stability, while accuracy requires that the measurements be correct. Despite the substantial effort needed to achieve these levels, these techniques are not widely practiced, and it is generally acknowledged that some progress is still needed to meet the demands of commercial lithography tools. Over the past several decades, interferometry has become the cornerstone measurement method in the development of high-accuracy, diffraction-limited optical systems. With countless varieties and variations in its implementation, interferometry refers to the class of wavefront measurement techniques that rely on the ability of coherent light to interfere and produce measurable intensity fluctuations. When well-controlled coherent light is passed through a test lens, it can be made to interfere with delayed, displaced, or filtered versions of the same wave packet in such a manner that an optical system's wavefront aberrations or wavefront slope errors can be revealed through an interference pattern, or interferogram. In this way, the light wavelength becomes the fundamental unit of measurement. In modern interferometers, the interferograms are recorded digitally on a light-sensitive charge-coupled device (CCD) camera, and many individual interferograms can be combined to form a single measurement.
Application of adaptive dynamic relaxation to highly nonlinear geotechnical problems

In this paper, an adaptive dynamic relaxation technique is proposed as an efficient method for large scale nonlinear geotechnical problems. Dynamic relaxation is a numerical method to solve static problems involving highly nonlinear differential equations. Extremely simple implementation and cheap computation resulting from the underlying explicit time integration scheme make this method an attractive candidate for large scale problems. However, for highly nonlinear problems it may require large number of iterations. As a remedy, an adaptive time stepping approach is proposed to deal with changes in stiffness due to nonlinearity. Moreover, the proposed algorithm is incorporated within a 2D and 3D finite element code where analytical solution of the local governing equations, as well as global expression of the strain-displacement matrix, is utilized in order to compensate the slow convergence and enhance the performance of the algorithm. The efficiency of the proposed algorithm is verified by presenting some numerical results from 2D and 3D elastoplastic analysis of bearing capacity of circular footing with von Mises plasticity model. The results show that apart from a competitive performance for a multiple load increment procedure, this approach is capable of providing a good approximation of the failure load in a single load step.
How to make a tuna burst : the role of angle of attack in the production of thrust

ii Preface . iv Table of contents . v List of tables. viii List of figures . ix List of symbols and abbreviations . xi Acknowledgements . xiii Dedication . xv Chapter 1: Introduction . 1 Chapter 2: Research chapter . 7 2.1 Theory . 9 2.1. 1 Swimming kinematics . 10 2.1. 2 Flow conditions, the choice of swimming speed and tail scaling . 14 2.1. 3 Motion regime summary . 17 2.1. 4 Strouhal number and the heave waveform. 18 2.1. 5 Pitch waveform and angle of attack profile . 20 2.1. 6 Phase angle. 23 2.1. 7 Tail material and stiffness . 25 2.2 Methods. 27 2.2.1 Tail model design . 27 2.2.2 Rod effect model . 30 2.2.3 Tail apparatus . 31 vi 2.2.4 Flow channel . 34 2.2. 5 Motion system . 36 2.2. 6 Force measurement . 39 2.2. 7 Post-processing and analysis. 40 2.2. 8 Ink-flow visualisation . 43 2.2. 9 Laser PIV visualisation . 49 2.3 Results . 50 2.3.1 Statics . 50 2.3.2 Dynamics: Direct measurement . 52 2.3. 3 Dynamics: Flow visualisation . 62 2.3. 4 Effect of apparatus . 69 2.4 Discussion . 73 2.4. 1 Mechanics of angle of attack and Strouhal number . 73 2.4. 2 Muscular implications of angle of attack control . 76 2.4. 3 Flow characteristics of αmax . 83 2.4. 4 Comparison with similar studies . 90 Chapter 3: Conclusion . 94 3.1 Future improvements and directions . 94 3.2 Concluding remarks . 98 Bibliography . 100 Appendices . 106 Appendix A Equipment details . 106 A.1 VeroWhitePlus RGD835 material properties . 106 vii A.2 Water tunnel . 106 A.3 Load cell datasheet . 107
The impact of charging plug-in hybrid electric vehicles on the distribution grid

Alternative vehicles based on internal combustion engines (ICE), such as the hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV) and the fuel-cell electric vehicle (FCEV), are becoming increasingly popular. HEVs are currently commercially available and PHEVs will be the next phase in the evolution of hybrid and electric vehicles. The batteries of the PHEVs are designed to be charged at home, from a wall socket in the garage, or on a corporate car park. These extra electrical loads have an impact on the distribution grid. First, the amount of electrical energy the distribution grid has to deliver for recharging the batteries of a PHEV fleet for the period 2003-2050 for Belgium is estimated. The TREMOVE model [1] provides the vehicle-kilometres and the number of passenger vehicles. For 2030, this electrical energy is at maximum 5.1% of the generated electricity in Belgium, assuming that all HEVs are PHEVs and depending on the scenarios of the PRIMES model [2]. This gives a first indication of the potential for PHEV. Secondly, this research aims to analyze the voltage profile and power losses due to PHEV recharging in a residential network representing a selection of streets. Uncontrolled power consumption on a local scale can lead to grid problems.
Frequency Response Design of Controlled Structures

The installation of optimal control systems has been shown to be effective in reducing the vibration responses of structures. In addition to the effectiveness, there are many factors that should be taken into consideration in the design of linear control systems. In general, closed-loop systems with time delays in the loop will be subjected to more stability problems than systems without delays. The stability condition may be deteriorated as the time delay increased. This investigation examine the frequency responses of the control system and try to establish the design strategy of the controlled structures.
Analysis of Coherent Structure of Turbulent Flows in the Rectangular Open-Channel Using LES

This study presented numerical simulations of smooth-bed flows in the rectangular open-channel using the source code by OpenFOAM. For the analysis of the turbulent flow, Large Eddy Simulations were carried out and the dynamic sub-grid scale model proposed by Germano et al. (1991) is used to model the residual stress term. In order to analyze the coherent structure, the uw quadrant method proposed by Lu and Willmarth (1973) is used and the contribution rate and the fraction time of the instantaneous Reynolds stress are obtained in the Reynolds stress. The results by the present study are analyzed and compared with data from previous laboratory studies and direct numerical simulations. It is found that the contribution rate of the ejection events is larger than that of sweep events over the buffer layer in the open-channel flow over the smooth bed, however, the frequency of the sweep event is higher than that of the ejection events.