The Press of the Royal Institution

The essay offers the first detailed account of the Press of the Royal Institution, established in 1801 in order to print the recently launched Journals of the Royal Institution as well as lecture syllabuses, other pedagogical works and a wide range of administrative and promotional documents. Analysing these diverse outputs, the essay also discusses the equipment and finances of the Printing Office, the people associated with it and the symbolism of the Press as an expression of the Institution’s ambitions and public image-building. The relationship with other London printers and booksellers is addressed, as are contemporary developments in printing technology and politically-motivated legislation to regulate the print trade. Later sections explain the reasons for the premature closure of the Printing Office in 1804 and chart its long-term legacy through the work of the printer (and later publisher and author) William Savage and his various collaborators, who included the bibliographer Thomas Frognall Dibdin and, briefly, Samuel Taylor Coleridge

Judgmental Translation in the World of Montaigne

Via Leonardo Bruni, we argue for the utility of the concept of “judgemental translation”, understood as a range of textual and intellectual practices that traverses the modern boundary between translation proper and the making of a new work. The ethics and politics of judgemental translation were central to the post-Reformation age and to Montaigne’s oeuvre. Par l’intermédiaire de Leonardo Bruni, nous défendons l’utilité du concept de « traduction critique », comprise comme un ensemble de pratiques textuelles et intellectuelles qui traversent la frontière moderne entre la traduction proprement dite et la création d’une nouvelle oeuvre. L’éthique et la politique de la traduction critique étaient au coeur de l'ère post-Réforme et de l’oeuvre de Montaigne

Introduction

Special issue on 'Romanticism at the Royal Institution

What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity

Pruning is an effective method to reduce the size of deep neural network models, maintain accuracy, and, in some cases, improve the network's overall performance. However, the mechanisms underpinning pruning remain unclear. Why can different methods prune by different percentages yet achieve similar performance? Why can we not prune at the start of training? Why are some models more amenable to being pruned than others? Given a model, what is the maximum amount it can be pruned before significantly affecting the performance? This paper explores and answers these questions from the global unstructured magnitude pruning perspective with one epoch of fine-tuning. We develop the idea that cosine similarity is an effective proxy measure for functional similarity between the parent and the pruned network. We prove that the L1 pruning method is optimal when pruning by cosine similarity. We show that the higher the kurtosis of a model's parameter distribution, the more it can be pruned while maintaining performance. Finally, we present a simple method to determine the optimal amount by which a network can be L1-pruned based on its parameter distribution. The code demonstrating the method is available at https://github.com/gmw99/what_makes_a_good_prun

Localization Algorithm Design for RIS-Aided Wireless Localization System

Reconfigurable intelligent surfaces (RISs) offer several advantages over traditional base stations (BSs) for localization systems, such as lower hardware costs and energy-efficient, high-precision estimation capabilities due to its passive panel nature. Additionally, the large RIS size allows for highly accurate radio localization parameter estimation. Consequently, developing localization algorithms for RIS-assisted wireless localization systems holds great significance. However, prevailing studies tend to assume an ideal and simplified communication environment when designing the localization algorithm for RIS-aided wireless localization systems. Addressing this oversight, this thesis investigates the algorithms design for RIS-aided wireless localization systems, specifically tackling practical conditions, such as non-Gaussian angle estimation errors (AEE), multiple users, faulty reflecting elements, and near-field. First, this thesis presents a comprehensive framework for jointly analyzing the AEE and designing a three-dimensional (3D) localization algorithm for a multiple RISs aided localization systems. The azimuth and elevation AoAs at the RISs are estimated by applying the two-dimensional discrete Fourier transform (2D-DFT) algorithm. The AEE is then analyzed in terms of probability density functions (PDF), revealing that the AEE is non-Gaussian. Then, the closed-form expressions of the variances are formulated using generalized hypergeometric series. Finally, the two-stage weighted least square (TSWLS) algorithm is employed to estimate the 3D position of the mobile user (MU) using the estimated AoAs and the obtained non-Gaussian variance. Second, this thesis designs a specific localization algorithms for accommodating the non-Gaussian nature of AoAs errors and the Gaussian character of TDoA error. Following the classical two-step 3D localization, the AoAs and TDoAs at the RISs are estimated using different methods, resulting in non-Gaussian and Gaussian errors, respectively. Then, a multiple weighted least squares (mWLS) algorithm is designed to accurately localize MU. Besides, this thesis presents a unique bias analysis for evaluating the performance of the proposed localization algorithm under both Gaussian and non-Gaussian errors. Third, this thesis investigates the localization algorithm designs for multiple MUs localization problem in the multiple-input multiple-output (MIMO) mmWave systems aided by the RIS. A novel type of fingerprint, space-time channel response vector (STCRV), is designed for fingerprint based localization algorithm design. Then, this thesis proposes a novel residual convolution network regression (RCNR) learning algorithm to output the estimated 3D position of the MU with higher accuracy. Fourth, this thesis explores the algorithm design addressing a practical scenario where RIS contains some unknown (number and places) faulty elements that cannot receive signals. Transfer learning is employed to design a two-phase transfer learning (TPTL) algorithm for accurate detection of faulty elements. Then, this thesis proposes a transfer-enhanced dual-stage (TEDS) algorithm to regain the information lost from the faulty elements and reconstruct the complete high-dimensional RIS information for localization. Fifth and last, this thesis investigates a near-field mobile tracking system assisted by extremely large-scale RIS (XL-RIS). An XL-RIS information reconstruction (XL-RIS-IR) algorithm is designed to reconstruct the high-dimensional RIS information from the low-dimensional BS received signal. Then, this thesis proposes a comprehensive framework for mobile tracking, consisting of a Feature Extraction Module and a Mobile Tracking Module. The Feature Extraction Module is designed for extracting a comprehensive from the reconstructed RIS information. A time-varying sequence formed by the extracted feature vector is fed into the Mobile Tracking Module, which employs an Auto-encoder (AE) with a stacked bidirectional long short-term memory (Bi-LSTM) encoder and a standard LSTM decoder to predict MUs' positions in the upcoming time slot

Comparative Investigation of the Microstructure of MgCl2 Aqueous Solutions Using Different X-ray Scattering Sources, Raman Spectroscopy, and Atomistic Simulations.

Aqueous solutions of magnesium chloride (MgCl2(aq)) are often used to test advances in the theory of electrolyte solutions because they are considered an ideal strong 2:1 electrolyte. However, there is evidence that some ion association occurs in these solutions, even at low concentrations. Even a small ion-pairing constant can have a significant impact on the chemical speciation of ions, so it is important to determine whether ion pairing actually occurs. In this study, MgCl2(aq) with concentrations ranging from 1 to 35% was studied using three methods: X-ray scattering (XRS) with the Shanghai Synchrotron Radiation Facility (SSRF) and silver-anode laboratory sources, Raman spectroscopy, and molecular dynamics (MD) simulations with the COMPASS-II and Madrid force fields. XRS results were analyzed in the framework of PDF theory to obtain the reduced structure function F(Q) and the reduced pair distribution function G(r). The F(Q) values from synchrotron radiation and laboratory sources both showed that the tetrahedral hydrogen bonds in bulk water were destroyed with the increased MgCl2 concentration. The results of G(r) indicated that the main peaks centered at 2.05 and 2.80 Å can be ascribed to the interactions of Mg-O and O-O, respectively. The peak at 3.10 Å is attributed to the combined effect of O-O and Cl-O. By comparing the structural information on MgCl2 solution obtained from the two light sources, it was found that both SSRF and silver-anode laboratory sources can reflect the above-mentioned structural information on MgCl2 solution. The radial distribution function (RDF) obtained from MD simulations of MgCl2 solutions assigned the peaks at 2.0, 2.8, and 3.2 Å to the Mg-O, O-O, and Cl-O interatomic pairs, respectively. The decrease in the O-O coordination number confirms that the hydrogen-bonding network of water is disrupted by increasing MgCl2 observed by X-ray scattering. The proportion of Mg-Cl contact ion pairs gradually increases with MgCl2 concentration as does the coordination number. Raman spectroscopy results show that the bond type changes from double donor double acceptor (DDAA) to single donor-single acceptor (DA) with increasing concentration, providing explicit details of the hydrogen-bond evolution in the aqueous solution

Endothelial Neuropilin-1: a multifaced signal transducer with an emerging role in inflammation and atherosclerosis beyond angiogenesis.

Neuropilin-1 (NRP1) is a transmembrane glycoprotein expressed by several cell types including, neurons, endothelial cells (ECs), smooth muscle cells, cardiomyocytes and immune cells comprising macrophages, dendritic cells and T cell subsets. Since NRP1 discovery in 1987 as an adhesion molecule in the frog nervous system, more than 2300 publications on PubMed investigated the function of NRP1 in physiological and pathological contexts. NRP1 has been characterised as a coreceptor for class 3 semaphorins and several members of the vascular endothelial growth factor (VEGF) family. Because the VEGF family is the main regulator of blood and lymphatic vessel growth in addition to promoting neurogenesis, neuronal patterning, neuroprotection and glial growth, the role of NRP1 in these biological processes has been extensively investigated. It is now established that NRP1 promotes the physiological growth of new vessels from pre-existing ones in the process of angiogenesis. Furthermore, several studies have shown that NRP1 mediates signalling pathways regulating pathological vascular growth in ocular neovascular diseases and tumour development. Less defined are the roles of NRP1 in maintaining the function of the quiescent established vasculature in an adult organism. This review will focus on the opposite roles of NRP1 in regulating transforming growth factor β signalling pathways in different cell types, and on the emerging role of endothelial NRP1 as an atheroprotective, anti-inflammatory factor involved in the response of ECs to shear stress