Dexterity analysis and robot hand design

Understanding about a dexterous robot hand's motion ranges is important to the precision grasping and precision manipulation. A planar robot hand is studied for object orientation, including ranges of motion, measures with respect to the palm, position reaching of a point in the grasped object, and rotation of the object about the reference point. The rotational dexterity index and dexterity chart are introduced and an analysis procedure is developed for calculating these quantities. A design procedure for determining the hand kinematic parameters based on a desired partial or complete dexterity chart is also developed. These procedures have been tested in detail for a planar robot hand with two 2- or 3-link fingers. The derived results are shown to be useful to performance evaluation, kinematic parameter design, and grasping motion planning for a planar robot hand

Volatility Mispricing in US Equity Option Markets

Recent research shows that volatility measurement errors are a prime source of mispricing in options markets. This allows investors to engage in trading strategies that earn abnormal rates of return. We conduct empirical research on US non-dividend paying American call options and perform a cross-sectional study of these stock option returns. We find that a zero-cost trading strategy that is long (short) in 2-month-to-expiry calls with relatively large positive (negative) difference between historical realized volatility and option implied volatility produces significant positive returns, but the same strategy applied to 1-month-to-expiry calls and delta-hedged calls does not

Prospects of Natural Zeolites in Indonesia for Industrial Separations and Environmental Management

Zeolite as well as molecular sieves are a class of aluminosilicate materials, which have found wide use in industries for separation, purification and pollution control. In the new era of nanomaterials in the 21st century, these nanoporous materials have become more widely used in separation, catalysis and environmental management, even in microelectronic and energy storage sectors. The following briefly shows the great potential of natural zeolites for some important environmental applications: CO2 removal from landfill gas and coal seam gas using Pressure Swing Adsorption (PSA) with Clinoptilolites: Natural zeolite is not only a cheaper solution to the economical storage system of methane for NGVs but it also present a safer storage medium as alternative adsorbent such activated carbon is flammable and very costly. There is also an increasing interest in indoor air quality control issues among the building industries and health organizations. It has been demonstrated that clinoptilolite is particularly effective adsorbent for odours and some volatiles in indoor environment. Another area of importantnce of natural zeolites is the solar energy application. Zeolites can adsorb water vapour and create effective cooling with solar heat as the energy to regenerate the zeolite. Systems using zeolites can be designed in such a way that combined cooling and heating can be achieved at about 40-60% efficiency. Adsorption of Nitrogen and Oxygen in zeolites for PSA application Cp zeolite deposit has about 75% of the capacity of a commercial Mordenite zeolite for air separation at 30°C. The dynamics studies showed that Cp zeolite is suitable for N2 and O2 separation due to their large difference in adsorption kinetics

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

When primed with only a handful of training samples, very large, pretrained language models such as GPT-3 have shown competitive results when compared to fully-supervised, fine-tuned, large, pretrained language models. We demonstrate that the order in which the samples are provided can make the difference between near state-of-the-art and random guess performance: essentially some permutations are “fantastic” and some not. We analyse this phenomenon in detail, establishing that: it is present across model sizes (even for the largest current models), it is not related to a specific subset of samples, and that a given good permutation for one model is not transferable to another. While one could use a development set to determine which permutations are performant, this would deviate from the true few-shot setting as it requires additional annotated data. Instead, we use the generative nature of language models to construct an artificial development set and based on entropy statistics of the candidate permutations on this set, we identify performant prompts. Our method yields a 13% relative improvement for GPT-family models across eleven different established text classification tasks

Comparing weak lensing peak counts in baryonic correction models to hydrodynamical simulations

Next-generation weak lensing (WL) surveys, such as by the Vera Rubin Observatory's LSST, the $\textit{Roman}$ Space Telescope, and the $\textit{Euclid}$ space mission, will supply vast amounts of data probing small, highly nonlinear scales. Extracting information from these scales requires higher-order statistics and the controlling of related systematics such as baryonic effects. To account for baryonic effects in cosmological analyses at reduced computational cost, semi-analytic baryonic correction models (BCMs) have been proposed. Here, we study the accuracy of BCMs for WL peak counts, a well studied, simple, and effective higher-order statistic. We compare WL peak counts generated from the full hydrodynamical simulation IllustrisTNG and a baryon-corrected version of the corresponding dark matter-only simulation IllustrisTNG-Dark. We apply galaxy shape noise expected at the depths reached by DES, KiDS, HSC, LSST, $\textit{Roman}$, and $\textit{Euclid}$. We find that peak counts in BCMs are (i) accurate at the percent level for peaks with $\mathrm{S/N}<4$, (ii) statistically indistinguishable from IllustrisTNG in most current and ongoing surveys, but (iii) insufficient for deep future surveys covering the largest solid angles, such as LSST and $\textit{Euclid}$. We find that BCMs match individual peaks accurately, but underpredict the amplitude of the highest peaks. We conclude that existing BCMs are a viable substitute for full hydrodynamical simulations in cosmological parameter estimation from beyond-Gaussian statistics for ongoing and future surveys with modest solid angles. For the largest surveys, BCMs need to be refined to provide a more accurate match, especially to the highest peaks.Comment: 12 pages, 10 figure