Control of a supernumerary robotic hand by foot: an experimental study in virtual reality.

In the operational theater, the surgical team could highly benefit from a robotic supplementary hand under the surgeon's full control. The surgeon may so become more autonomous; this may reduce communication errors with the assistants and take over difficult tasks such as holding tools without tremor. In this paper, we therefore examine the possibility to control a third robotic hand with one foot's movements. Three experiments in virtual reality were designed to assess the feasibility of this control strategy, the learning curve of the subjects in different tasks and the coordination of foot movements with the two natural hands. Results show that the limbs are moved simultaneously, in parallel rather than serially. Participants' performance improved within a few minutes of practice without any specific difficulty to complete the tasks. Subjective assessment by the subjects indicated that controlling a third hand by foot has been easy and required only negligible physical and mental efforts. The sense of ownership was reported to improve through the experiments. The mental burden was not directly related to the level of motion required by a task, but depended on the type of activity and practice. The most difficult task was moving two hands and foot in opposite directions. These results suggest that a combination of practice and appropriate tasks can enhance the learning process for controlling a robotic hand by foot

In a demanding task, three-handed manipulation is preferred to two-handed manipulation.

Equipped with a third hand under their direct control, surgeons may be able to perform certain surgical interventions alone; this would reduce the need for a human assistant and related coordination difficulties. However, does human performance improve with three hands compared to two hands? To evaluate this possibility, we carried out a behavioural study on the performance of naive adults catching objects with three virtual hands controlled by their two hands and right foot. The subjects could successfully control the virtual hands in a few trials. With this control strategy, the workspace of the hands was inversely correlated with the task velocity. The comparison of performance between the three and two hands control revealed no significant difference of success in catching falling objects and in average effort during the tasks. Subjects preferred the three handed control strategy, found it easier, with less physical and mental burden. Although the coordination of the foot with the natural hands increased trial after trial, about two minutes of practice was not sufficient to develop a sense of ownership towards the third arm

Cable-driven robotic interface for lower limb neuromechanics identification.

This paper presents a versatile cable-driven robotic interface to investigate the single-joint joint neuromechanics of the hip, knee and ankle in the sagittal plane. This endpoint-based interface offers highly dynamic interaction and accurate position control (as is typically required for neuromechanics identification), and provides measurements of position, interaction force and EMG of leg muscles. It can be used with the subject upright, corresponding to a natural posture during walking or standing, and does not impose kinematic constraints on a joint, in contrast to existing interfaces. Mechanical evaluations demonstrated that the interface yields a rigidity above 500 N/m with low viscosity. Tests with a rigid dummy leg and linear springs show that it can identify the mechanical impedance of a limb accurately. A smooth perturbation is developed and tested with a human subject, which can be used to estimate the hip neuromechanics

Mortgage default risks and high-frequency predictability of the U.S. housing market : a reconsideration

Recent evidence, based on a linear framework, tends to suggest that while mortgage default risks can predict weekly and monthly housing returns of the United States, the same does not hold at the daily frequency. We, however, indicate that the relationship between daily housing returns with mortgage default risks is in fact nonlinear, and hence a linear predictive model is misspecified. Given this, we use a k-th order nonparametric causality-in-quantiles test, which in turn allows us to test for predictability over the entire conditional distribution of not only housing returns, but also volatility, by controlling for misspecification due to nonlinearity. Based on this model, we show that mortgage default risks do indeed predict housing returns and volatility, barring at the extreme upper end of the respective conditional distributions.http://www.tandfonline.com/loi/repm202022-07-26hj2021Economic

Price effects after one-day abnormal returns in developed and emerging markets: ESG versus traditional indices

У цій статті розглядається вплив ціни після одноденного аномального прибутку на складі індекси ринків як розвинених, так і тих, що розвиваються, диференціюючи між собою екологічні, соціальні та управлінські (ESG) і звичайні індекси. Використання щодня дані сімейних індексів MSCI за період 2007-2020 рр. За допомогою різних методів щоб уникнути методологічної упередженості, перевіряються наступні гіпотези: після одноден ненормальний прибуток специфічний ціновий ефект (моментум/контраріан) з’являється (H1) для випадок позитивної (H1.1) і негативної (H1.2) прибутковості; ціновий ефект після одного дня аномальна віддача є більшою для випадку традиційних індексів порівняно з ESG індекси (Н2); Цінові ефекти після одноденної аномальної прибутковості є сильнішими протягом кризовий період (Н3); динамічний тригерний підхід більш доречний для визначення ненормального повертає ніж статичний (H4); Цінові ефекти після одноденної аномальної прибутковості сильніші для ринки, що розвиваються, порівняно з розвиненими (H5). Результати неоднозначні для випадку H1 і не надають доказів на користь H2-H5. Вони не виставляються значні відмінності між ESG та звичайними індексами. Типи виявлених ефекти однакові; в деяких випадках сила ефектів різна, але нізначно, і ніяких закономірностей у цих відмінностях не виявлено. Загалом, є сильний протилежний ефект на фондовому ринку США після одноденної аномальної прибутковості. А торгова стратегія, побудована на основі цього ефекту, може генерувати прибуток від торгівлі. Основні результати дають додаткові докази проти гіпотези ефективного ринку і надати висновки, які можуть допомогти практикам перемогти ринок.This paper examines the price effects after one-day abnormal returns in stock markets indices of both developed and emerging while differentiating between Environmental, social, and governance (ESG) and conventional indices. Using daily data of MSCI family indices over the period 2007-2020. Using various methods to avoid methodological bias, the following hypotheses are tested: after one-day abnormal returns specific price effects (momentum/contrarian) do appear (H1) for the case of positive (H1.1) and negative (H1.2) returns; price effects after one-day abnormal returns are stronger for the case of traditional indices compared to ESG indices (H2); price effects after one-day abnormal returns are stronger during the crisis period (H3); dynamic trigger approach is more appropriate to define abnormal returns than static (H4); price effects after one-day abnormal returns are stronger for emerging markets compared to developed ones (H5). The results are mixed for the case of H1 and provide no evidence in favor of H2-H5. They do not exhibit significant differences between ESG and conventional indices. Types of detected effects are the same; in some cases, the power of the effects is different, but not significantly, and no patterns in these differences are detected. Overall, there is a strong contrarian effect in the US stock market after one-day abnormal returns. A trading strategy constructed based on this effect can generate profits from trading. The main results give additional evidence against the Efficient Market Hypothesis and provide implications that can help practitioners in beating the market

Ears of the Armadillo: Global Health Research and Neglected Diseases in Texas

Neglected tropical diseases (NTDs) have\ud been recently identified as significant public\ud health problems in Texas and elsewhere in\ud the American South. A one-day forum on the\ud landscape of research and development and\ud the hidden burden of NTDs in Texas\ud explored the next steps to coordinate advocacy,\ud public health, and research into a\ud cogent health policy framework for the\ud American NTDs. It also highlighted how\ud U.S.-funded global health research can serve\ud to combat these health disparities in the\ud United States, in addition to benefiting\ud communities abroad

Technical trading and cryptocurrencies

This paper carries out a comprehensive examination of technical trading rules in cryptocurrency markets, using data from two Bitcoin markets and three other popular cryptocurrencies. We employ almost 15,000 technical trading rules from the main five classes of technical trading rules and find significant predictability and profitability for each class of technical trading rule in each cryptocurrency. We find that the breakeven transaction costs are substantially higher than those typically found in cryptocurrency markets. To safeguard against data-snooping, we implement a number of multiple hypothesis procedures which confirms our findings that technical trading rules do offer significant predictive power and profitability to investors. We also show that the technical trading rules offer substantially higher risk-adjusted returns than the simple buy-and-hold strategy, showing protection against lengthy and severe drawdowns associated with cryptocurrency markets. However there is no predictability for Bitcoin in the out-of-sample period, although predictability remains in other cryptocurrency markets

Forecasting Cryptocurrency Value by Sentiment Analysis: An HPC-Oriented Survey of the State-of-the-Art in the Cloud Era

This chapter surveys the state-of-the-art in forecasting cryptocurrency value by Sentiment Analysis. Key compounding perspectives of current challenges are addressed, including blockchains, data collection, annotation, and filtering, and sentiment analysis metrics using data streams and cloud platforms. We have explored the domain based on this problem-solving metric perspective, i.e., as technical analysis, forecasting, and estimation using a standardized ledger-based technology. The envisioned tools based on forecasting are then suggested, i.e., ranking Initial Coin Offering (ICO) values for incoming cryptocurrencies, trading strategies employing the new Sentiment Analysis metrics, and risk aversion in cryptocurrencies trading through a multi-objective portfolio selection. Our perspective is rationalized on the perspective on elastic demand of computational resources for cloud infrastructures

The Robotic Multiobject Focal Plane System of the Dark Energy Spectroscopic Instrument (DESI)

A system of 5020 robotic fiber positioners was installed in 2019 on the Mayall Telescope, at Kitt Peak National Observatory. The robots automatically retarget their optical fibers every 10-20 minutes, each to a precision of several microns, with a reconfiguration time of fewer than 2 minutes. Over the next 5 yr, they will enable the newly constructed Dark Energy Spectroscopic Instrument (DESI) to measure the spectra of 35 million galaxies and quasars. DESI will produce the largest 3D map of the universe to date and measure the expansion history of the cosmos. In addition to the 5020 robotic positioners and optical fibers, DESI’s Focal Plane System includes six guide cameras, four wave front cameras, 123 fiducial point sources, and a metrology camera mounted at the primary mirror. The system also includes associated structural, thermal, and electrical systems. In all, it contains over 675,000 individual parts. We discuss the design, construction, quality control, and integration of all these components. We include a summary of the key requirements, the review and acceptance process, on-sky validations of requirements, and lessons learned for future multiobject, fiber-fed spectrographs