Restricted Hidden Markov Model based Innovation in Physical Learning Education with Computer Internet Technology

The integration of computer internet technology into college physical education teaching has greatly enriched the teaching methods and forms and has promoted the innovation of the physical education teaching mode. The integration of computer internet technology into college physical education teaching mode has brought about significant innovation and improvement, enabling teachers to provide richer, more interactive, personalized, and flexible teaching. The integration of computer internet technology in physical education teaching has opened up new opportunities for enhancing the learning experience and improving student outcomes. This research focuses on the development of a technological innovation that leverages deep learning techniques, specifically the Restricted Hidden Markov Model (RHMMDL), to optimize physical education instruction. By harnessing the power of deep learning algorithms, the RHMMDL model aims to analyze and interpret movement patterns, providing personalized feedback and guidance to students. This paper presents the conceptual framework and methodology of the RHMMDL model, highlighting its potential benefits and implications for physical education teaching. The study also discusses the challenges and limitations associated with the implementation of this innovative technology

Revisiting the interacting model of new agegraphic dark energy

In this paper, a new version of the interacting model of new agegraphic dark energy (INADE) is proposed and analyzed in detail. The interaction between dark energy and dark matter is reconsidered. The interaction term $Q=bH_0\rho_{\rm de}^\alpha\rho_{\rm dm}^{1-\alpha}$ is adopted, which abandons the Hubble expansion rate $H$ and involves both $\rho_{\rm de}$ and $\rho_{\rm dm}$. Moreover, the new initial condition for the agegraphic dark energy is used, which solves the problem of accommodating baryon matter and radiation in the model. The solution of the model can be given using an iterative algorithm. A concrete example for the calculation of the model is given. Furthermore, the model is constrained by using the combined Planck data (Planck+BAO+SNIa+$H_0$) and the combined WMAP-9 data (WMAP+BAO+SNIa+$H_0$). Three typical cases are considered: (A) $Q=bH_0\rho_{\rm de}$, (B) $Q=bH_0\sqrt{\rho_{\rm de}\rho_{\rm dm}}$, and (C) $Q=bH_0\rho_{\rm dm}$, which correspond to $\alpha=1$, 1/2, and 0, respectively. The departures of the models from the $\Lambda$CDM model are measured by the $\Delta$BIC and $\Delta$AIC values. It is shown that the INADE model is better than the NADE model in the fit, and the INADE(A) model is the best in fitting data among the three cases.Comment: 6 pages, 2 figure

A digitally implemented practical photovoltaic simulator with a double current mode controller

This thesis presents a microcontroller- and DC-DC converter-based photovoltaic (PV) simulator which emulates the output characteristic of a PV module. The current-voltage (IV) characteristic of a PV module is implemented as a look-up-table that generates an output reference current based on a measured output voltage. The control mechanism is based on a double current mode controller that consists of a predictive current mode controller and a proportional-integral (PI) controller arranged in an inner loop and outer loop configuration. The PI controller is designed based on classical phase margin and gain margin criteria to ensure system stability. The performance of the portable PV simulator prototype of 85 W is examined in terms of its steady state IV curve matching capability and the convergence time corresponding to step changes in load and insolation levels. The result shows a well behaved and responsive PV simulator that can be treated as a real PV module in most situations --Abstract, page iii

Divorce, Abortion and Children's Sex Ratio: The Impact of Divorce Reform in China

This paper explores how the relative circumstances of men and women following marital dissolution affect sex-selection behavior within marriages. China's 2001 divorce reform liberalized divorce in favor of women and secured women's property rights after separation. We use this improvement in women's bargaining power in marriage for a regression discontinuity analysis of the demand for sex-selective abortions. We show that the increase in women's bargaining power reduces the propensity to have a son after a firstborn daughter by 8.9 percentage points. We also find that the effect is larger for women with higher health risks

Counterfactual Slope and Its Applications to Social Stratification

This paper addresses two prominent theses in social stratification research, the great equalizer thesis and Mare's (1980) school transition thesis. Both theses are premised on a descriptive regularity: the association between socioeconomic background and an outcome variable changes when conditioning on an intermediate treatment. The interpretation of this descriptive regularity is complicated by social actors' differential selection into treatment based on their potential outcomes under treatment. In particular, if the descriptive regularity is driven by selection, then the theses do not have a substantive interpretation. We propose a set of novel counterfactual slope estimands, which capture the two theses under the hypothetical scenario where differential selection into treatment is eliminated. Thus, we use the counterfactual slopes to construct selection-free tests for the two theses. Compared with the existing literature, we are the first to provide explicit, nonparametric, and causal estimands, which enable us to conduct principled selection-free tests. We develop efficient and robust estimators by deriving the efficient influence functions of the estimands. We apply our framework to a nationally representative dataset in the United States and re-evaluate the two theses. Findings from our selection-free tests show that the descriptive regularity of the two theses is misleading for substantive interpretations

Robust federated learning with noisy communication

Federated learning is a communication-efficient training process that alternate between local training at the edge devices and averaging of the updated local model at the center server. Nevertheless, it is impractical to achieve perfect acquisition of the local models in wireless communication due to the noise, which also brings serious effect on federated learning. To tackle this challenge in this paper, we propose a robust design for federated learning to decline the effect of noise. Considering the noise in two aforementioned steps, we first formulate the training problem as a parallel optimization for each node under the expectation-based model and worst-case model. Due to the non-convexity of the problem, regularizer approximation method is proposed to make it tractable. Regarding the worst-case model, we utilize the sampling-based successive convex approximation algorithm to develop a feasible training scheme to tackle the unavailable maxima or minima noise condition and the non-convex issue of the objective function. Furthermore, the convergence rates of both new designs are analyzed from a theoretical point of view. Finally, the improvement of prediction accuracy and the reduction of loss function value are demonstrated via simulation for the proposed designs

Effect of lighting schedule, intensity, and colour on reproductive performance of rabbit does

[EN] In order to establish a lighting regime suitable for rabbit farms in East China, the effects of lighting schedule, intensity and colour on the reproductive performance of rabbit does were evaluated by three experiments, respectively. In experiment 1, does were exposed to different lighting schedules: 16L:8D-continuous, 16L:8D-18d (6 d before artificial insemination (AI) to 12 d post-AI), 16L:8D-6d (6 d before AI to the day of AI) and 12L:12D-continuous. In experiment 2, does were exposed to different light intensities: 40 lx, 60 lx, 80 lx and 120 lx. In experiment 3, does were exposed to different light colours: white, yellow, blue and red. For all experiments, conception rate, kindling rate and pre-weaning mortality were calculated; litter size at birth, litter weight at birth, litter size at weaning, litter weight at weaning and individual kit weight at weaning were recorded. Results showed that none of the reproductive parameters of does were affected by the application of 16L:8D-18d lighting schedule compared with the continuous 16L:8D group(P>0.05). Moreover, rabbits does exposed to 80 lx light performed as well as those under 120 lx light in conception rate, kindling rate, litter size (total and alive) at birth and litter weight at birth (P>0.05). Furthermore, the exposures of 60 lx and 80 lx light were beneficial for litter weight at weaning. In addition, red light had a positive effect, as it led to a larger litter size and litter weight at weaning and lower pre-weaning mortality than white light (P<0.05). In summary, a 16L:8D photoperiod with 80 lx red light from 6 d before AI to 12 d post-AI is recommended for use in breeding of rabbit does according to our results.We would like to thank the support of Earmarked Fund for Modern Agro-Industry Technology Research System (CARS-44).Wu, Y.; Zhao, A.; Qin, Y. (2021). 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A coupled chlorinase-fluorinase system with high efficiency of trans-halogenation and a shared substrate tolerance

Enzymatic trans-halogenation enables radiolabeling under mild and aqueous conditions, but rapid reactions are desired. We discovered two new S-adenosyl-L-methionine (SAM)-dependent chlorinases from soil bacteria and developed a coupled chlorinase-fluorinase system for highly improved trans-halogenation reactions. The chlorinase was for the first time demonstrated to tolerate the modification at the C-2 position of the adenine ring and act cooperatively with the fluorinase to accelerate the trans-halogenation of 5’-chlorodeoxy-2-ethynyladenosine (5’-ClDEA) to 5’-fluorodeoxy-2-ethynyladenosine (5’-FDEA). The acetylene group will enable the linkage with an azide tethered peptide via a “click” reaction. The coupled chlorinase-fluorinase system offers the prospect of developing rapid radiolabeling protocols under mild and aqueous conditions. Please click Additional Files below to see the full abstract

Iterative Geometry-Aware Cross Guidance Network for Stereo Image Inpainting

Currently, single image inpainting has achieved promising results based on deep convolutional neural networks. However, inpainting on stereo images with missing regions has not been explored thoroughly, which is also a significant but different problem. One crucial requirement for stereo image inpainting is stereo consistency. To achieve it, we propose an Iterative Geometry-Aware Cross Guidance Network (IGGNet). The IGGNet contains two key ingredients, i.e., a Geometry-Aware Attention (GAA) module and an Iterative Cross Guidance (ICG) strategy. The GAA module relies on the epipolar geometry cues and learns the geometry-aware guidance from one view to another, which is beneficial to make the corresponding regions in two views consistent. However, learning guidance from co-existing missing regions is challenging. To address this issue, the ICG strategy is proposed, which can alternately narrow down the missing regions of the two views in an iterative manner. Experimental results demonstrate that our proposed network outperforms the latest stereo image inpainting model and state-of-the-art single image inpainting models.Comment: Accepted by IJCAI 202