Prior scholarship on same-sex relationships and health has primarily relied on cross-sectional data, leaving a number of unanswered questions about health changes of same-sex couples over time. This ...study examined the self-rated health statuses and changes of individuals in same- and different-sex cohabitations and marriages over time (2014-2017).
Data were drawn from the 2014 panel of the Survey of Income and Program Participation (SIPP), a nationally representative and longitudinal study (N = 23,297) in the United States. Mixed- and fixed-effects regression models were performed to investigate the self-rated health changes of individuals in same-sex compared to different-sex relationships.
Results show that same-sex married individuals report a faster decline in self-rated health compared to different-sex married counterparts despite similar initial health statuses. Similarly, same-sex cohabitors also exhibit a more rapid health decline as compared to different-sex cohabitors.
The results point to health change disadvantages experienced by same-sex married and cohabiting individuals during the study period. The findings from this study advance scholarly knowledge on the health changes of individuals in marginalized intimate relationships and highlight the importance of studying sexual minorities' health using longitudinal data.
Adverse experiences in childhood may set the stage for future response to stress, emotion regulation, and interaction with partners in intimate relationships. This study examines the moderating role ...of childhood adversity on the association of daily marital stress with emotion work provision (intentional activities devoted to enhancing others' emotional well-being) and considers whether the association varies for men and women in same- and different-sex marriages. Specifically, I use ten days of dyadic diary data collected from 378 midlife same- and differentsex married couples (n = 756 individuals) and conduct multilevel regression models. The results show marital stress is positively associated with emotion work provision, and that the association is stronger for respondents who report more adverse childhood experiences. For respondents with low childhood adversity, the association of marital stress with emotion work is greater for same-sex couples compared to different-sex couples; for those with high childhood adversity, the association is equally strong. Findings from this study suggest that both men and women in same- and different-sex relationships do more emotion work in response to increased daily marital stress. Furthermore, early experiences of adversity are linked to stress responses in adulthood, with differing implications for men and women in different-sex and same-sex unions.
Classification of hyperspectral image (HSI) is an important research topic in the remote sensing community. Significant efforts (e.g., deep learning) have been concentrated on this task. However, it ...is still an open issue to classify the high-dimensional HSI with a limited number of training samples. In this paper, we propose a semi-supervised HSI classification method inspired by the generative adversarial networks (GANs). Unlike the supervised methods, the proposed HSI classification method is semi-supervised, which can make full use of the limited labeled samples as well as the sufficient unlabeled samples. Core ideas of the proposed method are twofold. First, the three-dimensional bilateral filter (3DBF) is adopted to extract the spectral-spatial features by naturally treating the HSI as a volumetric dataset. The spatial information is integrated into the extracted features by 3DBF, which is propitious to the subsequent classification step. Second, GANs are trained on the spectral-spatial features for semi-supervised learning. A GAN contains two neural networks (i.e., generator and discriminator) trained in opposition to one another. The semi-supervised learning is achieved by adding samples from the generator to the features and increasing the dimension of the classifier output. Experimental results obtained on three benchmark HSI datasets have confirmed the effectiveness of the proposed method , especially with a limited number of labeled samples.
This paper presents a kernelized version of the extended recursive least squares (EX-KRLS) algorithm which implements for the first time a general linear state model in reproducing kernel Hilbert ...spaces (RKHS), or equivalently a general nonlinear state model in the input space. The center piece of this development is a reformulation of the well known extended recursive least squares (EX-RLS) algorithm in RKHS which only requires inner product operations between input vectors, thus enabling the application of the kernel property (commonly known as the kernel trick). The first part of the paper presents a set of theorems that shows the generality of the approach. The EX-KRLS is preferable to 1) a standard kernel recursive least squares (KRLS) in applications that require tracking the state-vector of general linear state-space models in the kernel space, or 2) an EX-RLS when the application requires a nonlinear observation and state models. The second part of the paper compares the EX-KRLS in nonlinear Rayleigh multipath channel tracking and in Lorenz system modeling problem. We show that the proposed algorithm is able to outperform the standard KRLS and EX-RLS in both simulations.
Reconfigurable intelligent surface (RIS), equipped with a large number of small, low‐cost, and re‐configurable elements, is envisioned as a potential enabler for the upcoming 5G‐Advanced and 6G ...networks. Here, based on a flexibly tunable and readily programmable RIS, the capability of beamforming toward arbitrary desired directions and coverage enhancement are investigated and experimentally demonstrated. The theory of RIS‐based beamforming is introduced, the simulated beamforming radiation patterns are provided, and an over‐the‐air radiated testing platform is designed for characterizing RIS beamforming performance. The RIS beam steering radiation performance tests are conducted, and the radiation patterns for different directions are extracted and analyzed. In addition, the indoor field trials on the RIS performance evaluation of enhancing coverage are reported. The field trials for multiple RIS‐deployed scenarios, including RIS mirror placement, RIS non‐mirror placement, and non‐RIS assisted scenarios, are conducted, and the channel characteristics for those scenarios are extracted and modelled. Significant improvements in overcoming path loss and shadow fading in typical coverage holes can be observed. The proposed testing method and measurement results may provide some insights into the design and optimization of RIS‐aided wireless communications.
Here, based on a flexibly tunable and readily programmable reconfigurable intelligent surface (RIS), the capability of beamforming toward arbitrary desired directions and coverage enhancement are investigated and experimentally demonstrated. The theory of RIS‐based beamforming is introduced, the simulated beamforming radiation patterns are provided, and an over‐the‐air radiated testing platform is designed for characterizing RIS beamforming performance. The RIS beam steering radiation performance tests are conducted, and the radiation patterns for different directions are extracted and analyzed. In addition, the indoor field trials on the RIS performance evaluation of enhancing coverage are reported.
Apple leaf diseases seriously damage the yield and quality of apples. Current apple leaf disease diagnosis methods primarily rely on human visual inspection, which often results in low efficiency and ...insufficient accuracy. Many computer vision algorithms have been proposed to diagnose apple leaf diseases, but most of them are designed to run on high-performance GPUs. This potentially limits their application in the field, in which mobile devices are expected to be used to perform computer vision-based disease diagnosis on the spot. In this paper, we propose a lightweight one-stage network, called the Mobile Ghost Attention YOLO network (MGA-YOLO), which enables real-time diagnosis of apple leaf diseases on mobile devices. We also built a dataset, called the Apple Leaf Disease Object Detection dataset (ALDOD), that contains 8,838 images of healthy and infected apple leaves with complex backgrounds, collected from existing public datasets. In our proposed model, we replaced the ordinary convolution with the Ghost module to significantly reduce the number of parameters and floating point operations (FLOPs) due to cheap operations of the Ghost module. We then constructed the Mobile Inverted Residual Bottleneck Convolution and integrated the Convolutional Block Attention Module (CBAM) into the YOLO network to improve its performance on feature extraction. Finally, an extra prediction head was added to detect extra large objects. We tested our method on the ALDOD testing set. Results showed that our method outperformed other state-of-the-art methods with the highest
mAP
of 89.3%, the smallest model size of only 10.34 MB and the highest frames per second (FPS) of 84.1 on the GPU server. The proposed model was also tested on a mobile phone, which achieved 12.5 FPS. In addition, by applying image augmentation techniques on the dataset,
mAP
of our method was further improved to 94.0%. These results suggest that our model can accurately and efficiently detect apple leaf diseases and can be used for real-time detection of apple leaf diseases on mobile devices.
This article explores Archaic Wind music (gufeng 古風) and its implications for Sinophone articulations. Gufeng can be categorised as a particular type of music with lyrical, musical, and symbolic ...references to ancient China that is produced, consumed, and circulated within an online fan community. While the lyrics of gufeng music express a post-loyalist yearning to return to the fictional roots of “Cultural China,” its video adaptations deconstruct the authenticity of such cultural roots in their homoerotic subtext. Exploring the audio-visual texts of the gufeng music, I suggest that it shows a rhizomatic return to ancient China that disorients the routes to the past.
Background The angiotensin-receptor neprilysin inhibitor (ARNI) sacubitril/valsartan was shown to be superior to the angiotensin-converting enzyme inhibitor enalapril in terms of reducing ...cardiovascular mortality in the PARADIGM-HF (Prospective Comparison of ARNI with angiotensin-converting enzyme inhibitor to Determine Impact on Global Mortality and Morbidity in Heart Failure) study. However, the impact of ARNI on cardiac reverse remodeling (CRR) has not been established. Methods and Results We conducted a meta-analysis to compare the effects of ARNI versus angiotensin-converting enzyme inhibitors or angiotensin receptor blockers on CRR indices. We searched databases for studies published between 2010 and 2019 that reported CRR indices following ARNI administration. Effect size was expressed as mean difference (MD) with 95% CIs. Twenty studies enrolling 10 175 patients were included. ARNI improved functional capacity in patients with heart failure (HF) and a reduced ejection fraction (EF), including increasing New York Heart Association functional class (MD -0.79, 95% CI -0.86, -0.71) and 6-minute walking distance (MD 27.62 m, 95% CI 15.76, 39.48). ARNI outperformed angiotensin-converting enzyme inhibitors/angiotensin receptor blockers in terms of CRR indices, with striking changes in left ventricular EF, diameter, and volume. However, there were no significant improvements in indices except left ventricular mass index (MD -3.25 g/m
, 95% CI -3.78, -2.72) and left atrial volume (MD -7.20 mL, 95% CI -14.11, -0.29) in HF patients with preserved EF treated with ARNI. Improvements in CRR indices were observed at 3 months and became more significant with longer follow-up to 12 months. The regression equation for the relationship between left ventricular EF and end-diastolic dimension was y=0.041+0.071x+0.045x
+0.006x
. Conclusions ARNI distinctly improved left ventricular size and hypertrophy compared with angiotensin-converting enzyme inhibitors/angiotensin receptor blockers in HF with reduced EF patients, even after short-term follow-up. Patients appeared to benefit more in terms of CRR treated with ARNI as early as possible and for at least 3 months. Further large sample trials are required to determine the effects of ARNI on CRR in HF with preserved EF patients.
Spike prediction models effectively predict downstream spike trains from upstream neural activity for neural prostheses. Such prostheses could potentially restore damaged neural communication ...pathways using predicted patterns to guide electrical stimulations on downstream. Since the ground truth of downstream neural activity is unavailable for subjects with the damage, reinforcement learning (RL) with behavior-level rewards becomes necessary for model training. However, existing models do not involve any constraint on the generated firing patterns and neglect the correlations among neural activities. Thus, the model outputs can greatly deviate from the natural range of neural activities, causing concerns for clinical usage. This study proposes the neural manifold constraint to solve this problem, shaping RL-generated spike trains in the feature space. The constraint terms describe the first and second order statistics of the neural manifold estimated from neural recordings during subjects' freely moving period. Then, the models can be optimized within the neural manifold by behavioral reinforcement. We test the method to predict primary motor cortex (M1) spikes from medial prefrontal (mPFC) spikes when rats perform the two-lever discrimination task. Results show that the neural activity generated by constrained models resembles the real M1 recordings. Compared with models without constraints, our approach achieves similar behavioral success rates, but reduces the mean squared error of neural firing by 61%. The constraints also increase the model's robustness across data segments and induce realistic neural correlations. Our method provides a promising tool to restore transregional communication with high behavioral performance and more realistic microscopic patterns.
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