MAP3K19 regulatory variation in populations with African ancestry may increase COVID-19 severity

To identify ancestry-linked genetic risk variants associated with COVID-19 hospitalization, we performed an integrative analysis of two genome-wide association studies and resolved four single nucleotide polymorphisms more frequent in COVID-19-hospitalized patients with non-European ancestry. Among them, the COVID-19 risk SNP rs16831827 shows the largest difference in minor allele frequency (MAF) between populations with African and European ancestry and also shows higher MAF in hospitalized COVID-19 patients among cohorts of mixed ancestry (odds ratio [OR] = 1.20, 95% CI: 1.10-1.30) and entirely African ancestry (OR = 1.30, 95% CI: 1.02-1.67). rs16831827 is an expression quantitative trait locus of MAP3K19. MAP3K19 expression is induced during ciliogenesis and most abundant in ciliated tissues including lungs. Single-cell RNA sequencing analyses revealed that MAP3K19 is highly expressed in multiple ciliated cell types. As rs16831827∗T is associated with reduced MAP3K19 expression, it may increase the risk of severe COVID-19 by reducing MAP3K19 expression

Effects of single session transcranial direct current stimulation on aerobic performance and one arm pull-down explosive force of professional rock climbers

Objective: To explore the effects of single-session transcranial direct current stimulation (tDCS) on aerobic performance and explosive force in the one-arm pull-down of long-term trained rock climbers.Method: Twenty athletes (twelve male and eight female) from the Rock Climbing Team of Hunan province (Hunan, China) were selected for a randomized double-blind crossover study. After baseline tests, All subjects visited laboratories twice to randomly receive either sham or a-tDCS at a current intensity of 2 mA for 20 min. The two visits were more than 72 h apart. Immediately after each stimulation, subjects completed a 9-min 3-level-load aerobic test and a one-arm pull-down test.Results: Differences in the heart rate immediately after 9-min incremental aerobic exercises revealed no statistical significance between each group (p > 0.05). However, the decrease in heart rate per unit time after exercise after real stimulation was significantly better than before stimulation (p < 0.05), and no statistical significance was observed between after sham stimulation and before stimulation (p > 0.05). One-arm pull-down explosive force on both sides after real stimulation was improved by a-tDCS compared with before stimulation, but with no significant difference (p > 0.05). Real stimulation was significantly improved, compared with sham stimulation on the right side (p < 0.05).Conclusion: Single-session tDCS could potentially benefit sports performance in professional athletes

Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array

Nonlinear optical processing of ambient natural light is highly desired in computational imaging and sensing applications. A strong optical nonlinear response that can work under weak broadband incoherent light is essential for this purpose. Here we introduce an optoelectronic nonlinear filter array that can address this emerging need. By merging 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron array that allows self-amplitude modulation of spatially incoherent light, achieving a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than what is achievable in most optical nonlinear materials. For a proof-of-concept demonstration, we fabricated a 10,000-pixel array of optoelectronic neurons, each serving as a nonlinear filter, and experimentally demonstrated an intelligent imaging system that uses the nonlinear response to instantly reduce input glares while retaining the weaker-intensity objects within the field of view of a cellphone camera. This intelligent glare-reduction capability is important for various imaging applications, including autonomous driving, machine vision, and security cameras. Beyond imaging and sensing, this optoelectronic neuron array, with its rapid nonlinear modulation for processing incoherent broadband light, might also find applications in optical computing, where nonlinear activation functions that can work under ambient light conditions are highly sought.Comment: 20 Pages, 5 Figure

Estimation in Semi-Varying Coefficient Heteroscedastic Instrumental Variable Models with Missing Responses

This paper studies the estimation problem for semi-varying coefficient heteroscedastic instrumental variable models with missing responses. First, we propose the adjusted estimators for unknown parameters and smooth functional coefficients utilizing the ordinary profile least square method and instrumental variable adjustment technique with complete data. Second, we present an adjusted estimator of the stochastic error variance by employing the Nadaraya–Watson kernel estimation technique. Third, we apply the inverse probability-weighted method and instrumental variable adjustment technique to construct the adaptive-weighted adjusted estimators for unknown parameters and smooth functional coefficients. The asymptotic properties of our proposed estimators are established under some regularity conditions. Finally, numerous simulation studies and a real data analysis are conducted to examine the finite sample performance of the proposed estimators

A massive MIMO system based multi-length pilot scheme

In massive MIMO system,pilot contamination is considered as a challenging problem,which deteriorates channel estimation at base station (BS) and therefore reduces the total throughput.In the conventional single-length pilot schemes,such contamination is severe due to the full reuse of pilot sequences in adjacent cells.Therefore,in this paper,we propose a novel multi-length pilot scheme (MLPS) so that each user equaipment (UE) in the target cell can approach respective optimal pilot length and the total throughput can be increased.First,we illustrate the fact that the optimal pilot lengths of UEs in the same cell are distributed among several values.Then,to eliminate the interferences caused by nonorthogonality of different-length pilots and simultaneous transmission of pilots and data,a feasible pilot design criterion is presented and two time-division strategies are developed.Finally,we evaluate our schemes by extensive simulations,MLPS obtains a gain of up to 18% for uplink throughput and up to 20% for downlink throughput

PV power prediction based on AO-VMD-RF-Informer

Due to the strong volatility of PV power, PV grid-connected may have an impact on the safe and stable operation of the power system, so accurate prediction of PV power is of great significance to the operation and maintenance of the power system. In order to improve the prediction accuracy of photovoltaic power, an ultra-short-term photovoltaic power prediction method was studied by combining the Aquila Optimizer (AO) algorithm, the Variational Mode Decomposition (VMD), the Random Forest (RF) and the Informer prediction model. Firstly, the VMD parameters are optimized by AO to reduce the adverse effects of human-set parameters on the prediction accuracy; the optimized VMD is used to decompose the original PV power series into multiple sub-sequences to reduce the volatility and complexity of the original power series; then, the RF feature selection method is used to screen out the meteorological features of strong relevance for each sub-sequence to further reduce the feature dimensions and the model runtime and ensure the effectiveness of the input features. Finally, the Informer model is used to deeply mine the potential time series features of each subsequence for prediction, and the predicted values of each subsequence are superimposed and reconstructed to obtain the final prediction results. The simulation results show that the method in this paper has high prediction accuracy, and compared with the original Informer, the MAE is reduced by 49.14% and the RMSE is reduced by 47.64%