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

Expression and localization of thylakoid-associated mRNAs during heterocyst development in cyanobacterium Anabaena sp. strain PCC 7120

Cyanobacteria are the only prokaryotes that perform oxygen-producing photosynthesis. Photosynthetic light reactions occur at the thylakoid membranes. In the filamentous cyanobacterium Anabaena sp. PCC 7120, thylakoids are remodelled during heterocyst development and the honeycomb domain is generated at the sub-polar region of the heterocysts with specific terminal oxidases (Cox proteins). Little is known about the remodelling of thylakoids during heterocyst development and the targeting of proteins to the specific membrane domain. In this study, RNA-Fluorescence in situ Hybridisation was used to investigate the sites of translation of thylakoid membrane proteins by probing mRNAs encoding membrane components in Anabaena sp. PCC 7120 during heterocyst development. The mRNA signals are concentrated in patches at the inner surface of the thylakoid membranes, facing the central cytoplasm. These patches mark the putative sites of translation and membrane insertion of these proteins. The localisation of cox mRNA and oxidase activity following nitrogen depletion was probed. cox mRNAs are evenly distributed over the inner surface of the thylakoid membranes, while oxidase activity is concentrated at the honeycomb thylakoids, suggesting that the oxidase proteins migrate extensively after translation to reach the location of their activity. The effect of specific RNA-binding proteins in mRNA expression and localisation was then studied. Rbp2 and Rbp3 were suggested to be involved in the targeting of photosynthetic mRNAs to the thylakoids in Synechocystis sp. PCC 6803. The deletion of rbpG, the closest homolog of Rbp3 in Anabaena sp. PCC 7120, shows a disrupted thylakoid membrane organisation with reduced Photosystem II activity and lower efficiency of the PSII repair cycle. The ΔrbpG mutant also shows significantly reduced cellular levels of photosynthetic mRNAs, particularly for psbA mRNA that encodes PSII D1 subunit. This suggests that the chaperoning of photosynthetic mRNAs by RbpG is important for the correct co-ordination of thylakoid protein translation and assembly

Biogeomorphological response to river restoration of a suburban river with large wood: creating a restoration vision and cost-effectively monitoring the response trajectory using the citizen science MoRPh survey

Biogeomorphological responses to river restoration are rarely reported. Despite a transition in the emphasis and priorities of river management over the last 40 years from controlling river channel forms and processes to restoring and supporting natural processes, forms and functions, remarkably little information is available on project outcomes. Here, using the example of Beverley Brook within Wimbledon Common, Greater London, UK, we illustrate how standardised detailed monitoring information can be assembled at a very low cost using the citizen science MoRPh survey and we demonstrate the importance of having a pre-project vision of likely outcomes that can be tracked by the monitoring programme. We show how a pre-project and five post-project surveys undertaken over 4 years according to a before-after-control-impact (BACI) design provides scientifically robust data. Analysis of the survey data quantifies the nature, abundance and spatial distribution of restoration interventions, the immediate responses to those interventions, and the ensuing trajectory of biogeomorphological adjustments. Changes in the persistence, size, position, abundance and evolution of habitats reveal the degree to which the restoration achieved the pre-project biogeomorphological vision and why the recovery trajectory progressed at the observed rate and to the observed end point over 4 years. Our approach has enormous potential for monitoring the outcomes of river interventions. Whilst our project was limited in its spatial scale and focus on physical habitats, we suggest how these limitations could be overcome whilst still containing costs

A multiscale modeling framework for Scenario Modeling: Characterizing the heterogeneity of the COVID-19 epidemic in the US.

The Scenario Modeling Hub (SMH) initiative provides projections of potential epidemic scenarios in the United States (US) by using a multi-model approach. Our contribution to the SMH is generated by a multiscale model that combines the global epidemic metapopulation modeling approach (GLEAM) with a local epidemic and mobility model of the US (LEAM-US), first introduced here. The LEAM-US model consists of 3142 subpopulations each representing a single county across the 50 US states and the District of Columbia, enabling us to project state and national trajectories of COVID-19 cases, hospitalizations, and deaths under different epidemic scenarios. The model is age-structured, and multi-strain. It integrates data on vaccine administration, human mobility, and non-pharmaceutical interventions. The model contributed to all 17 rounds of the SMH, and allows for the mechanistic characterization of the spatio-temporal heterogeneities observed during the COVID-19 pandemic. Here we describe the mathematical and computational structure of our model, and present the results concerning the emergence of the SARS-CoV-2 Alpha variant (lineage designation B.1.1.7) as a case study. Our findings show considerable spatial and temporal heterogeneity in the introduction and diffusion of the Alpha variant, both at the level of individual states and combined statistical areas, as it competes against the ancestral lineage. We discuss the key factors driving the time required for the Alpha variant to rise to dominance within a population, and quantify the impact that the emergence of the Alpha variant had on the effective reproduction number at the state level. Overall, we show that our multiscale modeling approach is able to capture the complexity and heterogeneity of the COVID-19 pandemic response in the US

The Motor Dysfunction Seen in Isolated REM Sleep Behavior Disorder.

BACKGROUND: Isolated Rapid Eye Movement (REM) sleep Behavior Disorder (iRBD) requires quantitative tools to detect incipient Parkinson's disease (PD). METHODS: A motor battery was designed and compared with the Movement Disorder Society-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) in people with iRBD and controls. This included two keyboard-based tests (BRadykinesia Akinesia INcoordination tap test and Distal Finger Tapping) and two dual tasking tests (walking and finger tapping). RESULTS: We included 33 iRBD patients and 29 controls. The iRBD group performed both keyboard-based tapping tests more slowly (P < 0.001, P = 0.020) and less rhythmically (P < 0.001, P = 0.006) than controls. Unlike controls, the iRBD group increased their walking duration (P < 0.001) and had a smaller amplitude (P = 0.001) and slower (P = 0.007) finger tapping with dual task. The combination of the most salient motor markers showed 90.3% sensitivity for 89.3% specificity (area under the ROC curve [AUC], 0.94), which was higher than the MDS-UPDRS-III (minus action tremor) (69.7% sensitivity, 72.4% specificity; AUC, 0.81) for detecting motor dysfunction. CONCLUSION: Speed, rhythm, and dual task motor deterioration might be accurate indicators of incipient PD in iRBD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society