Walking with shorter stride length could improve knee kinetics of patients with medial knee osteoarthritis

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Time course measurements are used for many applications in biomedical research, ranging from growth curves to drug efficacy testing and high-throughput screening. Statistical methods used to analyze the resulting longitudinal data, such as t-tests or repea ...

Project-based learning (PBL), as one of the effective teaching and learning approaches in engineering education, can create opportunities for students to address problems with real-world applications, integrate and apply knowledge, and practice and develop ...

Challenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly increased, from pur ...

In this letter, we present a custom-designed and flexible readout circuitry for the characterization of flexible and planar electrolyte-gated carbon nanotube field-effect transistor-based biosensors for ammonium detection in sweat. We employed spray-deposi ...

A 4-story steel moment-frame building designed according to ASCE 7 was used in a numerical parameter study to assess the effects of modeling features on peak drift demands. Features studied included strength, stiffness, ductility, and degradation along wit ...

Sensor technologies empower Industry 4.0 by enabling integration of in-field and real-time raw data into digital twins (DTs). However, sensors might be unreliable due to inherent issues and/or environmental conditions. This article aims at detecting anomal ...

Unmanned aerial vehicles (UAVs) have broad applications including disaster response, transportation, photography, and mapping. A significant bottleneck in the development of UAVs is the limited availability of automatic tools for task-specific co-design of ...

Semantic segmentation is a well-addressed topic in the computer vision literature, but the design of fast and accurate video processing networks remains challenging. In addition, to run on embedded hardware, computer vision models often have to make compro ...

This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. ...

This study evaluates the efficiency of an explainable ensemble learning framework in precisely predicting the bond strength between steel sections with different surface treatments and various concrete types. Besides seven numerical features, two categoric ...

Succinct non-interactive arguments (SNARGs) enable verifying NP statements with lower complexity than required for classical NP verification. Traditionally, the focus has been on minimizing the length of such arguments; nowadays, researchers have focused a ...

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk o ...

Photonic integrated circuits are becoming increasingly more complex, especially with the emergence of programmable photonic circuits. These require many tunable photonic elements, such as electro-optic phase shifters and tunable couplers. We will discuss o ...

Stereo matching aiming to perceive the 3-D geometry of a scene facilitates numerous computer vision tasks used in advanced driver assistance systems (ADAS). Although numerous methods have been proposed for this task by leveraging deep convolutional neural ...

Multivariate time series forecasting poses challenges as the variables are intertwined in time and space, like in the case of traffic signals. Defining signals on graphs relaxes such complexities by representing the evolution of signals over a space using ...

Recent generative adversarial networks (GANs) are able to generate impressive photo-realistic images. However, controllable generation with GANs remains an open research problem. Achieving controllable generation requires semantically interpretable and dis ...

Walking with shorter stride length could improve knee kinetics of patients with medial knee osteoarthritis

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biogrowleR: Enhancing Longitudinal Data Analysis

Project-Based Learning Approach for an Engineering Course: Challenges and Learnings of Teaching Transversal Skills

Exploiting the diversity of modeling methods to probe systematic biases in strong lensing analyses

Flexible Sensor and Readout Circuitry for Continuous Ion Sensing in Sweat

Backbone curve variations on steel building seismic response

A Machine-Learning Architecture for Sensor Fault Detection, Isolation, and Accommodation in Digital Twins

Editorial: Regional and molecular fingerprint of adipogenesis in aging and disease

Automatic Co-Design of Aerial Robots Using a Graph Grammar

Borrowing from yourself: Faster future video segmentation with partial channel update

Editorial: Integration and optimization in the chemical process industry

Computational electrophysiology of the coronary sinus branches based on electro-anatomical mapping for the prediction of the latest activated region

Explainable ensemble learning model for predicting steel section-concrete bond strength

Succinct Non-Interactive Arguments via Linear Interactive Proofs

Modifying stride length could enhance ambulatory knee kinetics of patients with medial knee osteoarthritis

Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running

A 1GS/s 6-to-8b 0.5mW/Qubit Cryo-CMOS SAR ADC for Quantum Computing in 40nm CMOS

Low-Power Electro-Optic Actuators for Large-Scale Programmable Photonic Circuits

Adversarial Confidence Estimation Networks for Robust Stereo Matching

Traffic Signal Prediction on Transportation Networks Using Spatio-Temporal Correlations on Graphs

Unsupervised Controllable Generation with Self-Training