BIRP: Bitcoin Information Retrieval Prediction Model Based on Multimodal Pattern Matching

Financial time series have historically been assumed to be a martingale process under the Random Walk hypothesis. Instead of making investment decisions using the raw prices alone, various multimodal pattern matching algorithms have been developed to help detect subtly hidden repeatable patterns within the financial market. Many of the chart-based pattern matching tools only retrieve similar past chart (PC) patterns given the current chart (CC) pattern, and leaves the entire interpretive and predictive analysis, thus ultimately the final investment decision, to the investors. In this paper, we propose an approach of ranking similar PC movements given the CC information and show that exploiting this as additional features improves the directional prediction capacity of our model. We apply our ranking and directional prediction modeling methodologies on Bitcoin due to its highly volatile prices that make it challenging to predict its future movements.Comment: 5 pages, 2 figures, KDD 2023 Machine Learning in Finance worksho

First-principles identification of the charge-shifting mechanism and ferroelectricity in hybrid halide perovskites

Hybrid halide perovskite solar cells have recently attracted substantial attention, mainly because of their high power conversion efficiency. Among diverse variants, (CH3NH3)PbI3 and HC(NH2)(2)PbI3 are particularly promising candidates because their bandgap well matches the energy range of visible light. Here, we demonstrate that the large nonlinear photocurrent in beta-(CH3NH3)PbI3 and alpha -HC(NH2)(2)PbI3 is mostly determined by the intrinsic electronic band properties near the Fermi level, rooted in the inorganic backbone, whereas the ferroelectric polarization of the hybrid halide perovskite is largely dominated by the ionic contribution of the molecular cation. The spatial charge shift upon excitation is attributed to the charge transfer from iodine to lead atoms in the backbone, which is independent of the presence of the cationic molecules. Our findings can serve as a guiding principle for the design of future materials for halide-perovskite solar cells with further enhanced photovoltaic performance

Optoelectronic manifestation of the orbital angular momentum driven by chiral hopping in helical Se chains

Chiral materials have garnered significant attention in the field of condensed matter physics. Nevertheless, the magnetic moment induced by the chiral spatial motion of electrons in helical materials, such as elemental Te and Se, remains inadequately understood. In this work, we investigate the development of quantum angular momentum enforced by chirality using static and time-dependent density functional theory calculations for an elemental Se chain. Our findings reveal the emergence of an unconventional orbital texture driven by the chiral geometry, giving rise to a non-vanishing current-induced orbital moment. By incorporating spin-orbit coupling, we demonstrate that a current-induced spin accumulation arises in the chiral chain, which fundamentally differs from the conventional Edelstein effect. Furthermore, we demonstrate the optoelectronic detection of the orbital angular momentum in the chiral Se chain, providing a conceptually novel alternative to the interband Berry curvature, which is ill-defined in low dimensions.Comment: 24 pages, 4 figure

The variation of relative magnetic helicity around major flares

We have investigated the variation of magnetic helicity over a span of several days around the times of 11 X-class flares which occurred in seven active regions (NOAA 9672, 10030, 10314, 10486, 10564, 10696, and 10720) using the magnetograms taken by the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory (SOHO). As a major result we found that each of these major flares was preceded by a significant helicity accumulation over a long period (0.5 to a few days). Another finding is that the helicity accumulates at a nearly constant rate and then becomes nearly constant before the flares. This led us to distinguish the helicity variation into two phases: a phase of monotonically increasing helicity and the following phase of relatively constant helicity. As expected, the amount of helicity accumulated shows a modest correlation with time-integrated soft X-ray flux during flares. However, the average helicity change rate in the first phase shows even stronger correlation with the time-integrated soft X-ray flux. We discuss the physical implications of this result and the possibility that this characteristic helicity variation pattern can be used as an early warning sign for solar eruptions

Prediction of ferroelectricity-driven Berry curvature enabling charge- and spin-controllable photocurrent in tin telluride monolayers

In symmetry-broken crystalline solids, pole structures of Berry curvature (BC) can emerge, and they have been utilized as a versatile tool for controlling transport properties. For example, the monopole component of the BC is induced by the time-reversal symmetry breaking, and the BC dipole arises from a lack of inversion symmetry, leading to the anomalous Hall and nonlinear Hall effects, respectively. Based on first-principles calculations, we show that the ferroelectricity in a tin telluride monolayer produces a unique BC distribution, which offers charge- and spin-controllable photocurrents. Even with the sizable band gap, the ferroelectrically driven BC dipole is comparable to those of small-gap topological materials. By manipulating the photon handedness and the ferroelectric polarization, charge and spin circular photogalvanic currents are generated in a controllable manner. The ferroelectricity in group-IV monochalcogenide monolayers can be a useful tool to control the BC dipole and the nonlinear optoelectronic responses

Experimental verification on the robustness and stability of an interaction control: Single-degree-of-freedom robot case

The nonlinear bang-bang impact control (NBBIC) had been proposed for robots performing tasks having frequent contact with different environments because it takes advantage of the frictions in robot joints that are not helpful for constrained space control usually, does not need to change gains throughout tasks, and requires little information on robot dynamics. Despite these advantages, due to the lack of stability proof, it was not widely adopted. Recently, the stability of the NBBIC for one degree-of-freedom (DOF) robot has been proved almost two decades after its first proposal. The stability condition provided a theoretical stable region of the inertia estimate and was not dependent on environment dynamics, indicating the robustness of NBBIC to environment dynamics (e.g. stiffness). Thus, there is a strong need to verify the stability condition and the robustness of NBBIC to environment dynamics. Experiments of single DOF robots colliding with various environments showed that the stability condition predicted the stable range of the inertia estimate well, though there was a reduction in upper-bound because of sensor noise. The impact force response did not vary significantly for environments with different stiffness (silicon, aluminium, and steel wall), thereby confirming the robustness of the NBBIC to environment dynamics

Generation of homogeneous midbrain organoids with in vivo-like cellular composition facilitates neurotoxin-based Parkinson\u27s disease modeling

Recent studies have demonstrated the generation of midbrain-like organoids (MOs) from human pluripotent stem cells. However, the low efficiency of MO generation and the relatively immature and heterogeneous structures of the MOs hinder the translation of these organoids from the bench to the clinic. Here we describe the robust generation of MOs with homogeneous distribution of midbrain dopaminergic (mDA) neurons. Our MOs contain not only mDA neurons but also other neuronal subtypes as well as functional glial cells including astrocytes and oligodendrocytes. Furthermore, our MOs exhibit mDA neuron-specific cell death upon treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, indicating that MOs could be a proper human model system for studying the in vivo pathology of Parkinson\u27s disease (PD). Our optimized conditions for producing homogeneous and mature MOs might provide an advanced patient-specific platform for in vitro disease modeling as well as for drug screening for PD

Enhancing the volumetric capacity of sodium ferrocyanide beyond its solubility limit in a Na-aqueous-catholyte redox flow battery

School of Energy and Chemical Engineering (Energy Engineering (Battery Science and Technology))clos

Automatic Psychological Text Analysis using Support Vector Machine Classification

In recent years, there has been an increasing number of patients with mental disorders. A conversational agent is being developed to ensure an easier diagnosis based on the chat between a patient and the agent. The objective of this research is to assess how well Support Vector Machine (SVM) classifies text into its corresponding schema, which are the mental states of the patient. In total, three different classifications have been attempted, Binary, Ordinal, and Per-Questionnaire. The experimental result indicated that SVM is possible to classify 2 out of 7 schema modes, but in general, the performance of SVM was not outperforming with a low f1-score. At the end of the research, SVM was compared to Recurrent Neural Network (RNN) and k-Nearest-Neighbour (kNN) and it turned out that RNN gives the best performance. One of the limitations affecting the result is the quality of the data set. With more correlated labels and a greater size of the data set, improved results can be expected.CSE3000 Research ProjectComputer Science and Engineerin

High-Resolution Photoacoustic Microscopy Based on a Transparent Ultrasonic Transducer

We present high-resolution and high-SNR in vivo vascular imaging of the mouse eye, brain, and ear with photoacoustic microscopy (PAM) integrated with a transparent ultrasound transducer. We observed microvessels in a chemically damaged mouse eye. Particularly, the performance of PAM as a comprehensive eye disease diagnosis tool was demonstrated by observing not only corneal neovascularization, but also iris blood vessels and hemorrhages in a cloudy state of the corneal. Second, we delineated in vivo mouse brain vascular imaging at high resolution with a depth encoding. Third, we monitored the ears of tumor-bearing mice to observe for angiogenesis over time. © 2022 SPIE.1