Network Connections and Salivary Testosterone Among Older U.S. Women: Social Modulation or Hormonal Causation?

Objectives This study examined potentially bidirectional connections of older U.S. women’s salivary testosterone with their social network connections. Methods Data were from the 2005–2006 and 2010–2011 waves of the National Social Life, Health and Aging Project (NSHAP), a national probability sample of older U.S. adults. Autoregressive cross-lagged panel models tested linkages of women’s testosterone with their social networks. Results Consistent with recent biological theory suggesting social modulation of hormones, a higher kin proportion in one’s egocentric (person-centered) network, arguably a stable compositional feature, negatively predicted women’s testosterone levels. In contrast, findings for tie strength were consistent with hormonal regulation of women’s sociality—with both perceived support from friends and family, and closeness to network members, negatively influenced by testosterone. Discussion Rather than being a static and exogenous biological factor, older women’s testosterone levels seem partly an outcome of their social context. Implications for sexual health and hormone therapy are discussed. However, this androgen also influences dimensions of their intimate networks critical to successful aging. Findings suggest the need for social scientists to engage with the neuroendocrine literature, which offers suggestions on linkages of hormones with specific network patterns.

Feature-Based Digital Modulation Recognition Using Compressive Sampling

Compressive sensing theory can be applied to reconstruct the signal with far fewer measurements than what is usually considered necessary, while in many scenarios, such as spectrum detection and modulation recognition, we only expect to acquire useful characteristics rather than the original signals, where selecting the feature with sparsity becomes the main challenge. With the aim of digital modulation recognition, the paper mainly constructs two features which can be recovered directly from compressive samples. The two features are the spectrum of received data and its nonlinear transformation and the compositional feature of multiple high-order moments of the received data; both of them have desired sparsity required for reconstruction from subsamples. Recognition of multiple frequency shift keying, multiple phase shift keying, and multiple quadrature amplitude modulation are considered in our paper and implemented in a unified procedure. Simulation shows that the two identification features can work effectively in the digital modulation recognition, even at a relatively low signal-to-noise ratio.

Grounded Compositional Semantics for Finding and Describing Images with Sentences

Previous work on Recursive Neural Networks (RNNs) shows that these models can produce compositional feature vectors for accurately representing and classifying sentences or images. However, the sentence vectors of previous models cannot accurately represent visually grounded meaning. We introduce the DT-RNN model which uses dependency trees to embed sentences into a vector space in order to retrieve images that are described by those sentences. Unlike previous RNN-based models which use constituency trees, DT-RNNs naturally focus on the action and agents in a sentence. They are better able to abstract from the details of word order and syntactic expression. DT-RNNs outperform other recursive and recurrent neural networks, kernelized CCA and a bag-of-words baseline on the tasks of finding an image that fits a sentence description and vice versa. They also give more similar representations to sentences that describe the same image.

A Corpus-Based Study of Evaluative That-Clause in Abstracts of Chinese Learners' Doctoral Dissertations

Evaluative language is one of the key features in academic discourse, which might cause difficulties for L2 writers. Based on a corpus of 150 English abstracts of Chinese doctoral dissertations in five disciplines, this paper studies the frequency, form and distribution of the evaluative that-clause, and compares the results with those in previous studies. The results show that Chinese learners use this structure significantly less frequently than experienced writers, which might be caused by learners' misunderstanding of the compositional feature of abstracts and lack of consciousness of the evaluative feature of abstracts. It is also demonstrated that verb-predicates occur most frequently in Chinese learners' abstracts among the three frequent word classes which introduce the proposition, that the stance feature expressed is mainly to confirm the findings and credit the study, and that the evaluated entity is mostly concerned with the writer's own research. We also design the feasible teaching procedures for pedagogical purposes.

regA, a Volvox gene that plays a central role in germ-soma differentiation, encodes a novel regulatory protein

Volvox has two cell types: mortal somatic cells and immortal germ cells. Here we describe the transposon-tagging, cloning and characterization of regA, which plays a central role as a master regulatory gene in Volvox germ-soma differentiation by suppressing reproductive activities in somatic cells. The 12.5 kb regA transcription unit generates a 6,725 nucleotide mRNA that appears at the beginning of somatic cell differentiation, and that encodes a 111 kDa RegA protein that localizes to the nucleus, and has an unusual abundance of alanine, glutamine and proline. This is a compositional feature shared by functional domains of many ‘active’ repressors. These findings are consistent with the hypothesis that RegA acts in somatic cells to repress transcription of genes required for growth and reproduction, including 13 genes whose products are required for chloroplast biogenesis.