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Your search for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins The process was smooth and quick..yeUb" yielded 78816 hits

Clinical versus MRI grading of the medial collateral ligament in acute knee injury

Sensitivity, specificity, and agreement between clinical and magnetic resonance imaging (MRI) gradings of the medial collateral ligament (MCL) after acute knee injury were evaluated in 362 patients. Ninety-seven per cent were injured during sports/recreation. Sensitivity and specificity of MRI for grade II or III MCL injury was 68% (95% CI 58–77%) and 90% (95% CI 86–93%), respectively. Weighted Ka

Multi-conjugate Adaptive Optics for the Swedish ELT Investigation of the Effects of Laser Guide Stars at a finite Distance.

In a recent paper we presented a procedure for optimal analyticalcontrol of several deformable mirrors based on only the measured guidestar wavefronts. The expected performance was evaluated for variousguide star configurations using up to three deformable mirrors. Forsimplicity the guide stars were assumed to be infinitely distant. Inthis paper we address the effect of using laser guide stars in

Surveillance of Disease Outbreaks Using Unsupervised Uni-Multivariate Anomaly Detection of Time-Series Symptoms

Effectively identifying deviations in real-world medical time-series data is a critical endeavor, essential for early surveillance of disease outbreaks. This paper demonstrates the integration of time-series anomaly detection techniques to develop surveillance systems for disease outbreaks. Utilizing data from Sweden's telephone counseling service (1177), we first illustrate the trends in physical

Optogenetics for controlling seizure circuits for translational approaches

The advent of optogenetic tools has had a profound impact on modern neuroscience research, revolutionizing our understanding of the brain. These tools offer a remarkable ability to precisely manipulate specific groups of neurons with an unprecedented level of temporal precision, on the order of milliseconds. This breakthrough has significantly advanced our knowledge of various physiological and pa

Velocities of a spatial-temporal stochastic field with embedded dynamics

The paper investigates further an approach to modeling dynamically changing Gaussian spatio-temporal fields. In that approach, the dynamics are introduced by embedding deterministic velocities into a stochastic spatio-temporal Gaussian model. In this way, a dynamically inactive stochastic field with given spatial and temporal covariance structure gains dynamics that in general follow a determinist

Branded applications - Function triumphs Brand? -An exploratory study of branded applications’ role in the brand building process

Abstract Title: Branded applications - Function triumphs Brand? -An exploratory study of branded applications’ role in the brand building process Date of the Seminar: 2013.05.29 Course: BUSN29, Degree project in Global marketing Authors: Vukcevic, Lidia and Willgottson, Malin Supervisor: Elg, Ulf Keywords: Brand building process, High/low involvement brands, Mobile marketing, Branded applica

Högerpopulism - en fallstudie över Finland och Ungern

This master thesis discusses the growth of radical right wing political parties in Europe. The point of departure is the theoretical framework, which consists of four chosen theories, trying to explain the reason behind the increasing support for radical right wing parties among the voters in Finland and Hungary. The theories are postindustrial developments, a legitimacy crisis for political insti

Structural and functional diversity of toxin-antitoxin-chaperone systems

Toxin-antitoxin-chaperone (TAC) systems are three-part gene clusters encoding a toxin, antitoxin, and specialized SecB-like chaperone (SecB TA) with emerging roles in phage defense. To identify and classify SecB homologs and associated TACs across bacteria, we surveyed the full RefSeq database. Phylogenetic and gene neighborhood analyses reveal three major SecB subfamilies: two housekeeping groups

Lightweight personalisation for MEMS-based wearables : a padel stroke recognition case study

This work investigates lightweight personalisation of micro-electro-mechanical systems (MEMS)-based wearables using a public padel database as a case study. We compare a centralised CNN model, single-user models and two fine-tuning schemes (full and last-layer) on wrist-worn IMU data from 23 players and 13 stroke classes. Personalised models with data augmentation achieve weighted F1-scores above

Efficient On-Device Machine Learning with a Biologically-Plausible Forward-Only Algorithm

The training of the state-of-the-art Deep Neural Networks (DNNs) consumes massive amounts of energy, while the human brain learns new tasks with remarkable efficiency. Currently, the training of DNNs relies almost exclusively on Backpropagation (BP). However, BP faces criticism due to its biologically implausible nature, underscoring the significant disparity in performance and energy efficiency b

Binary Forward-Only Algorithms

Today, the overwhelming majority of Internet of Things (IoT) and mobile edge devices have extreme resource limitations, e.g., in terms of computing, memory, and energy. As a result, training Deep Neural Networks (DNNs) using the complex Backpropagation (BP) algorithm on such edge devices presents a major challenge. Forward-only algorithms have emerged as more computation- and memory-efficient alte

Direct Imaging of Nanoscale Ferroelectric Domains and Polarization Reversal in Ferroelectric Capacitors

Ferroelectric thin films present a powerful platform for next-generation computing and memory applications. However, domain morphology and dynamics in buried ferroelectric stacks have remained underexplored, despite their importance for real device performance. Here, nanoprobe X-ray diffraction (nano-XRD) is used to image ferroelectric domains inside BiFeO3-based capacitors, revealing local disord

Membership Inference Attack in Random Forests

Machine Learning (ML) offers many opportunities, but its reliance on personal data raises privacy concerns. One such example is the Membership Inference Attack (MIA), which aims to determine whether a specific data point was part of a model’s training dataset. In this paper, we investigate this attack on Random Forests (RFs) and propose a method to quantify their vulnerability to MIA. We also demo

Federated Learning for Obstacle Detection to Assist the Visually-Impaired Using Augmented Reality

Vision impairment increases risks such as social isolation, mobility challenges, and falls. Wearable Augmented Reality (AR) devices with Artificial Intelligence (AI) can enhance sensory perception by enabling real-time recognition of obstacles, assisting visually impaired individuals during street navigation, aiming to reduce the risk of falls. In this paper, we propose a Federated Learning (FL) f

A Unified Framework for Real-Time Failure Handling in Robotics Using Vision-Language Models, Reactive Planner and Behavior Trees

Robotic systems often face execution failures due to unexpected obstacles, sensor errors, or environmental changes. Traditional failure recovery methods rely on predefined strategies or human intervention, making them less adaptable. This paper presents a unified failure recovery framework that combines Vision-Language Models (VLMs), a reactive planner, and Behavior Trees (BTs) to enable real-time

Improving the Sales Process Efficiency Without Jeopardizing Technical Risks

Since recently, Vestas Northern Europe has been facing a buyers’ market with more demanding customers than before. In addition, a rapid growth and a restrictive risk policy have caused inefficiency within the organization. The purpose is to investigate how the efficiency in the sales phase can be increased in advantage for additional projects to be handled. The efficiency is to be increased withou