Speaking up and being heard: the changing metadiscourse about ‘voice’ in British parliamentary debates since 1800

As a metaphor for political power, participation, and legitimacy, the concept of ‘voice’ is central to considerations of representative politics during the modern era. Little is known about how political actors themselves understood and referred to their own voices, those of others, and their respective significance for representative politics. This article focuses on the British Parliament, which was since the eighteenth century regarded as a paradigmatic incarnation of political voice and as the pinnacle of modern representative government. Based on a corpus of Hansard debates from 1800 to 2005, we analyse MPs’ explicit references to ‘voice’ in parliamentary debates. We aim to explore the salience of ‘voice’ for MPs and of different aspects of voice as a vehicle for expressing political will. We also shed light on how metadiscursive references to ‘voice’ change over the course of the nineteenth and twentieth centuries

Soliton microcomb based spectral domain optical coherence tomography

Spectral domain optical coherence tomography (SD-OCT) is a widely used and minimally invaive technique for bio-medical imaging [1]. SD-OCT typically relies on the use of superluminescent diodes (SLD), which provide a low-noise and broadband optical spectrum. Recent advances in photonic chipscale frequency combs [2, 3] based on soliton formation in photonic integrated microresonators provide an chipscale alternative illumination scheme for SD-OCT. Yet to date, the use of such soliton microcombs in OCT has not yet been analyzed. Here we explore the use of soliton microcombs in spectral domain OCT and show that, by using photonic chipscale Si3N4 resonators in conjunction with 1300 nm pump lasers, spectral bandwidths exceeding those of commercial SLDs are possible. We demonstrate that the soliton states in microresonators exhibit a noise floor that is ca. 3 dB lower than for the SLD at identical power, but can exhibit significantly lower noise performance for powers at the milliWatt level. We perform SD-OCT imaging on an ex vivo fixed mouse brain tissue using the soliton microcomb, alongside an SLD for comparison, and demonstrate the principle viability of soliton based SD-OCT. Importantly, we demonstrate that classical amplitude noise of all soliton comb teeth are correlated, i.e. common mode, in contrast to SLD or incoherent microcomb states [4], which should, in theory, improve the image quality. Moreover, we demonstrate the potential for circular ranging, i.e. optical sub-sampling [5, 6], due to the high coherence and temporal periodicity of the soliton state. Taken together, our work indicates the promising properties of soliton microcombs for SD-OCT

GMC collisions as triggers of star formation – VIII. The core mass function

Compression in giant molecular cloud (GMC) collisions is a promising mechanism to trigger the formation of massive star clusters and OB associations. We simulate colliding and non-colliding magnetized GMCs and examine the properties of pre-stellar cores, selected from projected mass surface density maps, including after synthetic ALMA observations. We then examine core properties, including mass, size, density, velocity, velocity dispersion, temperature, and magnetic field strength. After 4 Myr, ∼1000 cores have formed in the GMC collision, and the high-mass end of the core mass function (CMF) can be fit by a power-law dN/dlogM ∝ M-α with α ≃ 0.7, i.e. relatively top heavy compared to a Salpeter mass function. Depending on how cores are identified, a break in the power law can appear around a few 710 M☉. The non-colliding GMCs form fewer cores with a CMF with α ≃ 0.8–1.2, i.e. closer to the Salpeter index. We compare the properties of these CMFs to those of several observed samples of cores. Considering other properties, cores formed from colliding clouds are typically warmer, have more disturbed internal kinematics, and are more likely to be gravitational unbound, than cores formed from non-colliding GMCs. The dynamical state of the protocluster of cores formed in the GMC–GMC collision is intrinsically subvirial but can appear to be supervirial if the total mass measurement is affected by observations that miss mass on large scales or at low densities

Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis

Efficient and interpretable spatial analysis is crucial in many fields such as geology, sports, and climate science. Large-scale spatial data often contains complex higher-order correlations across features and locations. While tensor latent factor models can describe higher-order correlations, they are inherently computationally expensive to train. Furthermore, for spatial analysis, these models should not only be predictive but also be spatially coherent. However, latent factor models are sensitive to initialization and can yield inexplicable results. We develop a novel Multi-resolution Tensor Learning (MRTL) algorithm for efficiently learning interpretable spatial patterns. MRTL initializes the latent factors from an approximate full-rank tensor model for improved interpretability and progressively learns from a coarse resolution to the fine resolution for an enormous computation speedup. We also prove the theoretical convergence and computational complexity of MRTL. When applied to two real-world datasets, MRTL demonstrates 4 ~ 5 times speedup compared to a fixed resolution while yielding accurate and interpretable models

Determinants of Spike infectivity, processing, and neutralization in SARS-CoV-2 Omicron subvariants BA.1 and BA.2

SARS-CoV-2 Omicron rapidly outcompeted other variants and currently dominates the COVID-19 pandemic. Its enhanced transmission and immune evasion are thought to be driven by numerous mutations in the Omicron Spike protein. Here, we systematically introduced BA.1 and/or BA.2 Omicron Spike mutations into the ancestral Spike protein and examined the impacts on Spike function, processing, and susceptibility to neutralization. Individual mutations of S371F/L, S375F, and T376A in the ACE2-receptor-binding domain as well as Q954H and N969K in the hinge region 1 impaired infectivity, while changes to G339D, D614G, N764K, and L981F moderately enhanced it. Most mutations in the N-terminal region and receptor-binding domain reduced the sensitivity of the Spike protein to neutralization by sera from individuals vaccinated with the BNT162b2 vaccine and by therapeutic antibodies. Our results represent a systematic functional analysis of Omicron Spike adaptations that have allowed this SARS-CoV-2 variant to dominate the current pandemic

Markov analysis of stochastic resonance in a periodically driven integrate-fire neuron

We model the dynamics of the leaky integrate-fire neuron under periodic stimulation as a Markov process with respect to the stimulus phase. This avoids the unrealistic assumption of a stimulus reset after each spike made in earlier work and thus solves the long-standing reset problem. The neuron exhibits stochastic resonance, both with respect to input noise intensity and stimulus frequency. The latter resonance arises by matching the stimulus frequency to the refractory time of the neuron. The Markov approach can be generalized to other periodically driven stochastic processes containing a reset mechanism.Comment: 23 pages, 10 figure

Anti-CD3 antibody treatment reduces scar formation in a rat model of myocardial infarction

Introduction: Antibody treatment with anti-thymocyte globulin (ATG) has been shown to be cardioprotective. We aimed to evaluate which single anti-T-cell epitope antibody alters chemokine expression at a level similar to ATG and identified CD3, which is a T-cell co-receptor mediating T-cell activation. Based on these results, the effects of anti-CD3 antibody treatment on angiogenesis and cardioprotection were tested in vitro and in vivo. Methods: Concentrations of IL-8 and MCP-1 in supernatants of human peripheral blood mononuclear cell (PBMC) cultures following distinct antibody treatments were evaluated by Enzyme-linked Immunosorbent Assay (ELISA). In vivo, anti-CD3 antibodies or vehicle were injected intravenously in rats subjected to acute myocardial infarction (AMI). Chemotaxis and angiogenesis were evaluated using tube and migration assays. Intracellular pathways were assessed using Western blot. Extracellular vesicles (EVs) were quantitatively evaluated using fluorescence-activated cell scanning, exoELISA, and nanoparticle tracking analysis. Also, microRNA profiles were determined by next-generation sequencing. Results: Only PBMC stimulation with anti-CD3 antibody led to IL-8 and MCP-1 changes in secretion, similar to ATG. In a rat model of AMI, systemic treatment with an anti-CD3 antibody markedly reduced infarct scar size (27.8% (Inter-quartile range; IQR 16.2–34.9) vs. 12.6% (IQR 8.3–27.2); p < 0.01). The secretomes of anti-CD3 treated PBMC neither induced cardioprotective pathways in cardiomyocytes nor pro-angiogenic mechanisms in human umbilical vein endothelial cell (HUVECs) in vitro. While EVs quantities remained unchanged, PBMC incubation with an anti-CD3 antibody led to alterations in EVs miRNA expression. Conclusion: Treatment with an anti-CD3 antibody led to decreased scar size in a rat model of AMI. Whereas cardioprotective and pro-angiogenetic pathways were unaltered by anti-CD3 treatment, qualitative changes in the EVs miRNA expression could be observed, which might be causal for the observed cardioprotective phenotype. We provide evidence that EVs are a potential cardioprotective treatment target. Our findings will also provide the basis for a more detailed analysis of putatively relevant miRNA candidates

A Comparative Study on the WCRF International/University of Bristol Methodology for Systematic Reviews of Mechanisms Underpinning Exposure-Cancer Associations

The World Cancer Research Fund (WCRF) International and the University of Bristol have developed a novel framework for providing an overview of mechanistic pathways and conducting a systematic literature review of the biologically plausible mechanisms underlying exposure-cancer associations. Two teams independently applied the two-stage framework on mechanisms underpinning the association between body fatness and breast cancer to test the framework feasibility and reproducibility as part of a WCRF-commissioned validation study. In stage I, a "hypothesis-free" approach was used to provide an overview of potential intermediate mechanisms between body fatness and breast cancer. Dissimilar rankings of potential mechanisms were observed between the two teams due to different applications of the framework. In stage II, a systematic review was conducted on the insulin-like growth factor 1 receptor (IGF1R) chosen as an intermediate mechanism. Although the studies included differed, both teams found inconclusive evidence for the body fatness-IGF1R association and modest evidence linking IGF1R to breast cancer, and therefore concluded that there is currently weak evidence for IGF1R as mechanism linking body fatness to breast cancer. The framework is a good starting point for conducting systematic reviews by integrating evidence from mechanistic studies on exposure-cancer associations. On the basis of our experience, we provide recommendations for future users. (C) 2017 AACR