A Consistent Nonlinear Frequency Domain Model for Finite Depth Ocean Wave Propagation

A new nonlinear second-order frequency-domain model based on the mild-slope equation is outlined. The model is an enhancement over previous work in that a closer correspondence between scaling of nonlinearity and horizontal variation of bathymetry is made relative to earlier models. This results in additional terms in the nonlinear summation terms of the model, as amplitude gradient terms are required in order to formulate a completely consistent model at second order. From the resulting elliptic model equation, a parabolic approximation is developed in order to efficiently model the equations for most applications. Comparisons between the present model, previously-formulated models, and experimental data show that the present model does evidence improvement in performance over previous, less-consistent models. It is also found that the “phase mismatch,” which arises from the dispersive nature of the resulting equations, can adversely impact performance; this is a potential problem with all models of this sort. Using a scheme developed for stochastic formulations of these phase-resolved models, a hybrid consistent nonlinear mild-slope equation in frequency-domain is developed. Using this scheme, a newly simplified version of the present model retains quasi-cubic terms having a form of cubic term but originating from triad wave interaction terms is developed. Because of the quasi-cubic nonlinear summation having zero-mismatch, the hybrid model replicates the triad wave-wave interactions more accurately compared to the previous deterministic models. A higher-order parabolic evolution equation is derived for high accuracy at large wave approach angles. As an alternative, a consistent nonlinear mild-slope equation based on the angular spectrum model is also developed. These two newly developed models are tested for accuracy in describing wave pattern by a refractive focal lens, elliptic shoal, and circular shoal with the several incidence angles. The newly developed models are further examined with field data in order to ensure the models’ capability in simulating two-dimensional irregular wave processes. Lastly, a source term for triad interactions is derived from the present model for implementation into operational phase-averaged wave models

Technology Adoption and Wage Distribution in the U.S. Manufacturing Sector : Quantile Regression Analysis

This paper examines the effect of technology adoption on the wage dispersion in the U.S. manufacturing sector using the quantile regression method. We obtain two main results. First during the period of 1970 to 1995, the marginal effect of capital intensity on wage has risen. Second, the marginal effect on high-wage quantiles has risen more than that on low-wage quantiles. These results suggest that (1) high-wage quantile have adopted technologies more actively than others and (2) highcaptial intensity industries have contributed to the widening of wage dispersion over the period

Self-Calibrating, Fully Differentiable NLOS Inverse Rendering

Existing time-resolved non-line-of-sight (NLOS) imaging methods reconstruct hidden scenes by inverting the optical paths of indirect illumination measured at visible relay surfaces. These methods are prone to reconstruction artifacts due to inversion ambiguities and capture noise, which are typically mitigated through the manual selection of filtering functions and parameters. We introduce a fully-differentiable end-to-end NLOS inverse rendering pipeline that self-calibrates the imaging parameters during the reconstruction of hidden scenes, using as input only the measured illumination while working both in the time and frequency domains. Our pipeline extracts a geometric representation of the hidden scene from NLOS volumetric intensities and estimates the time-resolved illumination at the relay wall produced by such geometric information using differentiable transient rendering. We then use gradient descent to optimize imaging parameters by minimizing the error between our simulated time-resolved illumination and the measured illumination. Our end-to-end differentiable pipeline couples diffraction-based volumetric NLOS reconstruction with path-space light transport and a simple ray marching technique to extract detailed, dense sets of surface points and normals of hidden scenes. We demonstrate the robustness of our method to consistently reconstruct geometry and albedo, even under significant noise levels

Deep Reinforcement Learning for Chatbots Using Clustered Actions and Human-Likeness Rewards

Training chatbots using the reinforcement learning paradigm is challenging due to high-dimensional states, infinite action spaces and the difficulty in specifying the reward function. We address such problems using clustered actions instead of infinite actions, and a simple but promising reward function based on human-likeness scores derived from human-human dialogue data. We train Deep Reinforcement Learning (DRL) agents using chitchat data in raw text—without any manual annotations. Experimental results using different splits of training data report the following. First, that our agents learn reasonable policies in the environments they get familiarised with, but their performance drops substantially when they are exposed to a test set of unseen dialogues. Second, that the choice of sentence embedding size between 100 and 300 dimensions is not significantly different on test data. Third, that our proposed human-likeness rewards are reasonable for training chatbots as long as they use lengthy dialogue histories of ≥10 sentences

Coordination tuning of cobalt phosphates towards efficient water oxidation catalyst

The development of efficient and stable water oxidation catalysts is necessary for the realization of practically viable water-splitting systems. Although extensive studies have focused on the metal-oxide catalysts, the effect of metal coordination on the catalytic ability remains still elusive. Here we select four cobalt-based phosphate catalysts with various cobalt-and phosphate-group coordination as a platform to better understand the catalytic activity of cobalt-based materials. Although they exhibit various catalytic activities and stabilities during water oxidation, Na2CoP2O7 with distorted cobalt tetrahedral geometry shows high activity comparable to that of amorphous cobalt phosphate under neutral conditions, along with high structural stability. First-principles calculations suggest that the surface reorganization by the pyrophosphate ligand induces a highly distorted tetrahedral geometry, where water molecules can favourably bind, resulting in a low overpotential (similar to 0.42 eV). Our findings emphasize the importance of local cobalt coordination in the catalysis and suggest the possible effect of polyanions on the water oxidation chemistry.

Effects of heat stress on conception in Holstein and Jersey cattle and oocyte maturation in vitro

Korea, located in East Asia in the northern hemisphere, is experiencing severe climate changes. Specifically, the heat stress caused by global warming is negatively affecting the dairy sector, including milk production and reproductive performance, as the major dairy cattle Holstein-Friesian is particularly susceptible to heat stress. Here, we collected artificial insemination and pregnancy data of the Holstein and the Jersey cows from a dairy farm from 2014 to 2021 and analyzed the association between the conception rate and the temperature-humidity index, calculated using the data from the closest official weather station. As the temperature-humidity index threshold increased, the conception rate gradually decreased. However, this decrease was steeper in the Holstein breed than in the Jersey one at a temperature-humidity index threshold of 75. To evaluate the effects of heat stress on the oocyte quality, we examined the nuclear and cytoplasmic maturation of Holstein (n = 158, obtained from six animals) and Jersey oocytes (n = 123, obtained from six animals), obtained by ovum pick-up. There were no differences in the nuclear maturation between the different conditions (heat stress: 40.5°C, non- heat stress: 37.5°C) or breeds, although the Holstein oocytes seemed to have a lower metaphase II development (p = 0.0521) after in vitro maturation under heat stress conditions. However, we found that the Holstein metaphase II oocytes exposed to heat stress presented more reactive oxygen species and a peripheral distribution of the mitochondria, compared to those of the Jersey cattle. Here, we show that weather information from local meteorological stations can be used to calculate the temperature-humidity index threshold at which heat stress influences the conception rate, and that the Jersey cows are more tolerant to heat stress in terms of their conception rate at a temperature-humidity index over 75. The lower fertility of the Holstein cows is likely attributed to impaired cytoplasmic maturation induced by heat stress. Thus, the Jersey cows can be a good breed for the sustainability of dairy farms for addressing climate changes in South Korea, as they are more resistant to hyperthermia

The anti-aging gene KLOTHO is a novel target for epigenetic silencing in human cervical carcinoma

<p>Abstract</p> <p>Background</p> <p><it>Klotho </it>was originally characterized as an anti-aging gene that predisposed Klotho-deficient mice to a premature aging-like syndrome. Recently, KLOTHO was reported to function as a secreted Wnt antagonist and as a tumor suppressor. Epigenetic gene silencing of secreted Wnt antagonists is considered a common event in a wide range of human malignancies. Abnormal activation of the canonical Wnt pathway due to epigenetic deregulation of Wnt antagonists is thought to play a crucial role in cervical tumorigenesis. In this study, we examined epigenetic silencing of <it>KLOTHO </it>in human cervical carcinoma.</p> <p>Results</p> <p>Loss of <it>KLOTHO </it>mRNA was observed in several cervical cancer cell lines and in invasive carcinoma samples, but not during the early, preinvasive phase of primary cervical tumorigenesis. <it>KLOTHO </it>mRNA was restored after treatment with either the DNA demethylating agent 2'-deoxy-5-azacytidine or histone deacetylase inhibitor trichostatin A. Methylation-specific PCR and bisulfite genomic sequencing analysis of the promoter region of <it>KLOTHO </it>revealed CpG hypermethylation in non-<it>KLOTHO</it>-expressing cervical cancer cell lines and in 41% (9/22) of invasive carcinoma cases. Histone deacetylation was also found to be the major epigenetic silencing mechanism for <it>KLOTHO </it>in the SiHa cell line. Ectopic expression of the secreted form of KLOTHO restored anti-Wnt signaling and anti-clonogenic activity in the CaSki cell line including decreased active β-catenin levels, suppression of T-cell factor/β-catenin target genes, such as <it>c-MYC </it>and <it>CCND1</it>, and inhibition of colony growth.</p> <p>Conclusions</p> <p>Epigenetic silencing of <it>KLOTHO </it>may occur during the late phase of cervical tumorigenesis, and consequent functional loss of KLOTHO as the secreted Wnt antagonist may contribute to aberrant activation of the canonical Wnt pathway in cervical carcinoma.</p

Unexpected discovery of low-cost maricite NaFePO_4 as a high-performance electrode for Na-ion batteries

Battery chemistry based on earth-abundant elements has great potential for the development of cost-effective, large-scale energy storage systems. Herein, we report, for the first time, that maricite NaFePO_4 can function as an excellent cathode material for Na ion batteries, an unexpected result since it has been regarded as an electrochemically inactive electrode for rechargeable batteries. Our investigation of the Na re-(de)intercalation mechanism reveals that all Na ions can be deintercalated from the nano-sized maricite NaFePO_4 with simultaneous transformation into amorphous FePO_4. Our quantum mechanics calculations show that the underlying reason for the remarkable electrochemical activity of NaFePO_4 is the significantly enhanced Na mobility in the transformed phase, which is ~ one fourth of the hopping activation barrier. Maricite NaFePO_4, fully sodiated amorphous FePO_4, delivered a capacity of 142 mA h g^(−1) (92% of the theoretical value) at the first cycle, and showed outstanding cyclability with a negligible capacity fade after 200 cycles (95% retention of the initial cycle)

Ensemble-Based Deep Reinforcement Learning for Chatbots

Trainable chatbots that exhibit fluent and human-like conversations remain a big challenge in artificial intelligence. Deep Reinforcement Learning (DRL) is promising for addressing this challenge, but its successful application remains an open question. This article describes a novel ensemble-based approach applied to value-based DRL chatbots, which use finite action sets as a form of meaning representation. In our approach, while dialogue actions are derived from sentence clustering, the training datasets in our ensemble are derived from dialogue clustering. The latter aim to induce specialised agents that learn to interact in a particular style. In order to facilitate neural chatbot training using our proposed approach, we assume dialogue data in raw text only – without any manually-labelled data. Experimental results using chitchat data reveal that (1) near human-like dialogue policies can be induced, (2) generalisation to unseen data is a difficult problem, and (3) training an ensemble of chatbot agents is essential for improved performance over using a single agent. In addition to evaluations using held-out data, our results are further supported by a human evaluation that rated dialogues in terms of fluency, engagingness and consistency – which revealed that our proposed dialogue rewards strongly correlate with human judgements