BagStacking: An Integrated Ensemble Learning Approach for Freezing of Gait Detection in Parkinson's Disease

This paper introduces BagStacking, a novel ensemble learning method designed to enhance the detection of Freezing of Gait (FOG) in Parkinson's Disease (PD) by using a lower-back sensor to track acceleration. Building on the principles of bagging and stacking, BagStacking aims to achieve the variance reduction benefit of bagging's bootstrap sampling while also learning sophisticated blending through stacking. The method involves training a set of base models on bootstrap samples from the training data, followed by a meta-learner trained on the base model outputs and true labels to find an optimal aggregation scheme. The experimental evaluation demonstrates significant improvements over other state-of-the-art machine learning methods on the validation set. Specifically, BagStacking achieved a MAP score of 0.306, outperforming LightGBM (0.234) and classic Stacking (0.286). Additionally, the run-time of BagStacking was measured at 3828 seconds, illustrating an efficient approach compared to Regular Stacking's 8350 seconds. BagStacking presents a promising direction for handling the inherent variability in FOG detection data, offering a robust and scalable solution to improve patient care in PD

Every real-rooted exponential polynomial is the restriction of a Lee-Yang polynomial

A Lee-Yang polynomial $p(z_{1},\ldots,z_{n})$ is a polynomial that has no zeros in the polydisc $\mathbb{D}^{n}$ and its inverse $(\mathbb{C}\setminus\overline{\mathbb{D}})^{n}$. We show that any real-rooted exponential polynomial of the form $f(x) = \sum_{j=0}^s c_j e^{\lambda_j x}$ can be written as the restriction of a Lee-Yang polynomial to a positive line in the torus. Together with previous work by Olevskii and Ulanovskii, this implies that the Kurasov-Sarnak construction of $\mathbb{N}$-valued Fourier quasicrystals from stable polynomials comprises every possible $\mathbb{N}$-valued Fourier quasicrystal

Entangled coherent states by mixing squeezed vacuum and coherent light

Entangled coherent states are shown to emerge, with high fidelity, when mixing coherent and squeezed vacuum states of light on a beam-splitter. These maximally entangled states, where photons bunch at the exit of a beamsplitter, are measured experimentally by Fock-state projections. Entanglement is examined theoretically using a Bell-type nonlocality test and compared with ideal entangled coherent states. We experimentally show nearly perfect similarity with entangled coherent states for an optimal ratio of coherent and squeezed vacuum light. In our scheme, entangled coherent states are generated deterministically with small amplitudes, which could be beneficial, for example, in deterministic distribution of entanglement over long distances.Comment: 6 pages, 6 figures, comments are welcom

New Cascaded Architecture for Classical and Quantum Multiparameter Sensing

We present an innovative concept for quantum-enhanced multiparameter optical phase sensing that can be implemented in free space, optical fiber or on-chip. Our measurable phases are in series, or cascaded, enabling measurements as a function of position with only a single input and output. We have modeled up to 20 phases, and fitting shows near-linear scaling of the power requirements for additional phases. This novel approach represents a new paradigm in multiparameter quantum metrology, and can be applied to remote sensing, communications, and geophysics.Comment: 5 pages, 4 figures. Comments are welcom