Miracle-dz/UniFAR-FTUs huggingface dataset:
Variational Inference with Holder Bounds

The recent introduction of thermodynamic integration techniques has provided a new framework for understanding and improving variational inference (VI). In this work, we present a careful analysis of the thermodynamic variational objective (TVO), bridging the gap between existing variational objectives and shedding new insights to advance the field. In particular, we elucidate how the TVO naturally connects the three key variational schemes, namely the importance-weighted VI, Renyi-VI, and MCMC-VI, which subsumes most VI objectives employed in practice. To explain the performance gap between theory and practice, we reveal how the pathological geometry of thermodynamic curves negatively affects TVO. By generalizing the integration path from the geometric mean to the weighted Holder mean, we extend the theory of TVO and identify new opportunities for improving VI. This motivates our new VI objectives, named the Holder bounds, which flatten the thermodynamic curves and promise to achieve a one-step approximation of the exact marginal log-likelihood. A comprehensive discussion on the choices of numerical estimators is provided. We present strong empirical evidence on both synthetic and real-world datasets to support our claims.
SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors

Today's scientific simulations require a significant reduction of data volume because of extremely large amounts of data they produce and the limited I/O bandwidth and storage space. Error-bounded lossy compression has been considered one of the most effective solutions to the above problem. In practice, however, the best-fit compression method often needs to be customized or optimized in particular because of diverse characteristics in different datasets and various user requirements on the compression quality and performance. In this paper, we address this issue with a novel modular, composable compression framework named SZ3. Our contributions are four-folds. (1) We develop SZ3 which features an innovative modular abstraction for the prediction-based compression framework, such that compression modules can be plugged in easily to create new compressors based on characteristics of data and user requirements. (2) We create a new compression pipeline by SZ3 for GAMESS data, which significantly improves the compression ratios over state-of-the-art compressors. (3) We develop an adaptive compression pipeline by SZ3 for APS data with minimal efforts, which leads to the best rate-distortion among all existing error-bounded lossy compressors for any bit-rate. (4) We compare the sustainability of SZ3 with leading error-bounded prediction-based compressors, and then demonstrate the necessity of diverse pipelines by integrating and evaluating several compression pipelines on diverse scientific datasets from multiple disciplines. Experiments show that SZ3 incurs very limited overhead in compressor integration and our customized compression pipelines lead to up to 20% improvement in compression ratios under the same data distortion, when compared with the best existing approach.
Fluidic Endogenous Magnetism and Magnetic Monopole Clues from Liquid Metal Droplet Machine

Magnetism and magnetic monopole are classical issues in basic physics. Conventional magnets are generally composed of rigid materials with shapes and structures unchangeable which may face challenges sometimes to answer the above questions. Here, from an alternative other than rigid magnet, we disclosed an unconventional way to generate endogenous magnetism and then construct magnetic monopole through tuning liquid metal machine. Through theoretical interpretation and conceptual experiments, we illustrated that when gallium base liquid metal in solution rotates under actuation of an external electric field, it forms an endogenous magnetic field inside which well explains the phenomenon that two such discrete metal droplets could easily fuse together, indicating their reciprocal attraction via N and S poles. Further, we conceived that the self-driving liquid metal motor was also an endogenous magnet owning the electromagnetic homology. When liquid metal in solution swallowed aluminum inside, it formed a spin motor and dynamically variable charge distribution which produced an endogenous magnetic field. This finding explains the phenomena that there often happened reflection collision and attraction fusion between running liquid metal motors which were just caused by the dynamic adjustment of their N and S polarities. Finally, we conceived that such endogenous magnet could lead to magnetic monopole and four technical routes were suggested as: 1. Matching the interior flow field of liquid metal machines; 2. Superposition between external electric effect and magnetic field; 3. Composite construction between magnetic particles and liquid metal motor; 4. Chemical ways such as via galvanic cell reaction. Overall, the fluidic endogenous magnet and the promising magnetic monopole it enabled may lead to unconventional magnetoelectric devices and applications in the near future.
Gamma-Ray Orbital Modulation of the Transitioning Millisecond Pulsar Binary XSS J12270–4859

We report on gamma-ray orbital modulation of the transitioning MSP binary XSS J12270–4859 detected in the Fermi Large Area Telescope (LAT) data. We use long-term optical data taken with the XMM-Newton OM and the Swift UltraViolet Optical Telescope to inspect radio timing solutions that are limited to relatively short time intervals and find that extrapolation of the solutions aligns well with the phasing of the optical data over 15 yr. The Fermi-LAT data folded on the timing solutions exhibit significant modulation (p = 5 × 10−6) with a gamma-ray minimum at the inferior conjunction of the pulsar. Intriguingly, the source seems to show similar modulation in both the low-mass X-ray binary and the MSP states, implying that mechanisms for gamma-ray emission in the two states are similar. We discuss these findings and their implications using an intrabinary shock scenario.
The stable rank of $\mathbb{Z}[x]$ is $3$

Grunewald, Mennicke and Vaserstein proved that the Bass stable rank of $\mathbb{Z}[x]$, the ring of the univariate polynomials over $\mathbb{Z}$, is $3$. This note addresses minor errors found in their proof. Using their method, we show in addition that the unimodular row $(3, x + 1, x^2 + 16)$ is not stable.
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs

The Deep Operator Networks~(DeepONet) is a fundamentally different class of neural networks that we train to approximate nonlinear operators, including the solution operator of parametric partial differential equations (PDE). DeepONets have shown remarkable approximation and generalization capabilities even when trained with relatively small datasets. However, the performance of DeepONets deteriorates when the training data is polluted with noise, a scenario that occurs very often in practice. To enable DeepONets training with noisy data, we propose using the Bayesian framework of replica-exchange Langevin diffusion. Such a framework uses two particles, one for exploring and another for exploiting the loss function landscape of DeepONets. We show that the proposed framework's exploration and exploitation capabilities enable (1) improved training convergence for DeepONets in noisy scenarios and (2) attaching an uncertainty estimate for the predicted solutions of parametric PDEs. In addition, we show that replica-exchange Langeving Diffusion (remarkably) also improves the DeepONet's mean prediction accuracy in noisy scenarios compared with vanilla DeepONets trained with state-of-the-art gradient-based optimization algorithms (e.g. Adam). To reduce the potentially high computational cost of replica, in this work, we propose an accelerated training framework for replica-exchange Langevin diffusion that exploits the neural network architecture of DeepONets to reduce its computational cost up to 25% without compromising the proposed framework's performance. Finally, we illustrate the effectiveness of the proposed Bayesian framework using a series of experiments on four parametric PDE problems.
Computer aided design of a firmware flashing protocol for vehicular on-board networks

Vehicular On-Board Networks consist of up to 70 electronic control units (ECUs) interconnected by buses and gateways and organized within domains with different trust levels. This paper describes how the design of a protocol for deploying a new firmware onto various vehicular ECUs might be automated. In particular, such a protocol should prevent attacks to the firmware update process and make sure that no malicious firmware is actually installed in place of a regular firmware update, despite the fact that it may be sent through insecure domains. Designing security protocols for ECU communication in such architectures can become quite complex and error-prone, especially given the computational and deployment constraints that apply in the domain. This paper discusses how the protocol designer might receive some help in exploring fundamental design decisions based on the systematic review of alternative security architectures and potential threats.
OGHReS: Large-scale filaments in the outer Galaxy

Filaments are a ubiquitous morphological feature of the molecular interstellar medium and are identified as sites of star formation. In recent years, more than 100 large-scale filaments (with a length > 10 pc) have been observed in the inner Milky Way. As they appear linked to Galactic dynamics, studying those structures represents an opportunity to link kiloparsec-scale phenomena to the physics of star formation, which operates on much smaller scales. In this letter, we use newly acquired Outer Galaxy High Resolution Survey (OGHReS) 12CO(2-1) data to demonstrate that a significant number of large-scale filaments are present in the outer Galaxy as well. The 37 filaments identified appear tightly associated with inter-arm regions. In addition, their masses and linear masses are, on average, one order of magnitude lower than similar-sized molecular filaments located in the inner Galaxy, showing that Milky Way dynamics is able to create very elongated features in spite of the lower gas supply in the Galactic outskirts.
Count-Less: A Counting Sketch for the Data Plane of High Speed Switches

Demands are increasing to measure per-flow statistics in the data plane of high-speed switches. Measuring flows with exact counting is infeasible due to processing and memory constraints, but a sketch is a promising candidate for collecting approximately per-flow statistics in data plane in real-time. Among them, Count-Min sketch is a versatile tool to measure spectral density of high volume data using a small amount of memory and low processing overhead. Due to its simplicity and versatility, Count-Min sketch and its variants have been adopted in many works as a stand alone or even as a supporting measurement tool. However, Count-Min's estimation accuracy is limited owing to its data structure not fully accommodating Zipfian distribution and the indiscriminate update algorithm without considering a counter value. This in turn degrades the accuracy of heavy hitter, heavy changer, cardinality, and entropy. To enhance measurement accuracy of Count-Min, there have been many and various attempts. One of the most notable approaches is to cascade multiple sketches in a sequential manner so that either mouse or elephant flows should be filtered to separate elephants from mouse flows such as Elastic sketch (an elephant filter leveraging TCAM + Count-Min) and FCM sketch (Count-Min-based layered mouse filters). In this paper, we first show that these cascaded filtering approaches adopting a Pyramid-shaped data structure (allocating more counters for mouse flows) still suffer from under-utilization of memory, which gives us a room for better estimation. To this end, we are facing two challenges: one is (a) how to make Count-Min's data structure accommodate more effectively Zipfian distribution, and the other is (b) how to make update and query work without delaying packet processing in the switch's data plane. Count-Less adopts a different combination .
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers

We develop machinery to design efficiently computable and consistent estimators, achieving estimation error approaching zero as the number of observations grows, when facing an oblivious adversary that may corrupt responses in all but an $\alpha$ fraction of the samples. As concrete examples, we investigate two problems: sparse regression and principal component analysis (PCA). For sparse regression, we achieve consistency for optimal sample size $n\gtrsim (k\log d)/\alpha^2$ and optimal error rate $O(\sqrt{(k\log d)/(n\cdot \alpha^2)})$ where $n$ is the number of observations, $d$ is the number of dimensions and $k$ is the sparsity of the parameter vector, allowing the fraction of inliers to be inverse-polynomial in the number of samples. Prior to this work, no estimator was known to be consistent when the fraction of inliers $\alpha$ is $o(1/\log \log n)$, even for (non-spherical) Gaussian design matrices. Results holding under weak design assumptions and in the presence of such general noise have only been shown in dense setting (i.e., general linear regression) very recently by d'Orsi et al. [dNS21]. In the context of PCA, we attain optimal error guarantees under broad spikiness assumptions on the parameter matrix (usually used in matrix completion). Previous works could obtain non-trivial guarantees only under the assumptions that the measurement noise corresponding to the inliers is polynomially small in $n$ (e.g., Gaussian with variance $1/n^2$). To devise our estimators, we equip the Huber loss with non-smooth regularizers such as the $\ell_1$ norm or the nuclear norm, and extend d'Orsi et al.'s approach [dNS21] in a novel way to analyze the loss function. Our machinery appears to be easily applicable to a wide range of estimation problems.
Molecular mapping of the rabbit atrioventricular node.

The atrioventricular node (AVN) of the heart is responsible for the important conduction delay between atrial systole and ventricular systole. The anatomical architecture and functional properties of the AVN are complex. Ionic currents have been characterised in the AVN at both the whole tissue level and single cell level. However, little is known about the molecular basis of these ionic currents. There were two aims of this research: 1) to generate an accurate three-dimensional reconstruction of the rabbit AVN conduction axis and 2) to use real time PCR and in situ hybridisation to measure levels of mRNA for specific ion channels and membrane proteins in the rabbit AVN and surrounding atrial and ventricular tissue. Neurofilament-M (NF-M) immunolabelling revealed a tract of cells extending from the posterior nodal extension through the compact node to the common bundle. The PNE appeared to correspond to the slow pathway. Loosely packed atrial muscle comprised the anterior region of the AVN conduction axis closest to the enclosed part of the AVN and most likely represents the fast pathway. Lower nodal cells extended from the common bundle to the lower extremities of the compact node and PNE. Significant differences in the mRNA levels between the PNE and atrial muscle for the pacemaker channel HCN4, INa channels Navl. 1 and Na, 1.5, the Ica,L channel Cav 1.3, the I to channel s-subunit KChIP2 and Cx43 were found HCNI, Nav 1.1, Cav 1.3 and NF-M mRNA were significantly higher in the PNE, compact node and common bundle compared to the atrium and ventricle. Kir 2.1 mRNA was significantly higher in the ventricular muscle compared to the PNE and atrial muscle. Atrial natriuretic peptide (ANP) mRNA, was significantly higher in the atrial muscle compared to other tissues. For mRNAs for the Ito channels, Kv 4.2 and Kv 4.3, the delayed rectifier K+ channels, Kv 1.5, ERG, K, LQTI and minK, the inward rectifier K+ channels, Kir 2.2, Kir6.2 and s-subunit SUR2A, and the Ca2+ handling proteins, RYR2, RYR3, NCXI and SERCA2a, there were no significant differences between tissues. In situ hybridisation staining revealed further complexity of the AVN conduction axis tissue. A region of loosely packed atrial tissue immediately adjacent to the nodal tissue was KChIP2 negative and Nav1.5 negative, and the lower nodal cells were both Cav 1.2 and Cav 1.3 positive. This study has described a complex architecture of the AVN and added further complexity by providing a detailed account of ion channel expression throughout this tissue.
Planar dual‐mode wideband antenna using short‐circuited‐strips loaded slotline radiator: Operation principle, design, and validation

A novel dual‐mode planar wideband slotline antenna is proposed. A pair of short‐circuited strips is symmetrically introduced along the slotline resonator near the nulls of electric field distribution of the second odd‐order resonant mode. In this way, two resonant modes are excited in a single slotline radiator and are both used for radiation in a wide frequency range. With the help of these paired strips, the dominant half‐wavelength mode can be gradually moved to the three halves‐wavelength mode, resulting to achieve a wideband radiation with two resonances. Prototype antennas are then fabricated to experimentally validate the principle and design approach of the proposed planar slotline antenna. It is shown that the proposed slotline antenna's impedance bandwidth could be effectively increased to 37.6% while keeping its inherent narrow slot configuration with length‐to‐width ratio (LWR) up to 42.00. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:573–581, 2015.
Effects of Wireless Sensor Network Uncertainties on Output-Only Modal Analysis Employing Merged Data of Multiple Tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.
Modelling multimodal passenger choices with stated preference

Redland Shire Council has recently started the implementation of an Integrated Local Transport Plan (ILTP) that aims to reduce the car dependency by enhancing the usage of alternative modes of transport. A multi mode choice model is required that can forecast the travel behaviour across the region in order to achieve the targets set in ILTP. This paper presents the findings of a state-of-the-art literature review done on mode choice modelling and outlines the development and calibration of a model to investigate the travel behaviour of Redlands’ residents. The present study attempts to develop a nested logit model and calibrate it using data obtained from a stated preference (SP) survey to be conducted in the Shire. The model development will consider all the vital attributes of the travelling modes used in the study area including various public transit access modes. The possibility of combining SP and revealed preference (RP) data to calibrate the model using joint-estimation method will be further assessed. It is expected that the outcomes of the research will assist policy makers in the areas of public transport planning and the development of network for public transport access modes including walkways and cycleways.
The measurement of carbon performance of construction activities: A case study of a hotel construction project in South Wales

Purpose – The purpose of this research project is to reduce the carbon emissions of construction processes by Measuring, Mapping, Modelling and Managing (4Ms) the carbon performance of construction activities. This particular paper presents the research work and major findings in the first two stages: measuring the carbon footprint of construction activities in building projects; and mapping the carbon emissions from construction activities.Design/methodology/approach – A hotel project in South Wales was selected as a case study where the carbon emissions from six categories of construction activities (i.e. management, operations, visitors, deliveries, plant and utilities) were monitored by using carefully designed data collection methods throughout the construction process. Both qualitative and quantitative analysis methods were adopted to distil and map the emissions with construction activities.Findings – This study provides a benchmark for the carbon emissions from construction processes. The results .
Risk Management in Projects

Project managers and professionals in construction real estate, civil engineering and transport planning need to base their decisions on realistic information. For this they require a sound understanding of risk and of peoples' attitudes towards it. The focus of the second edition of John Raftery's successful text Risk Analysis in Project Management has been expanded to encompass the entire risk management process and to provide a fuller presentation of how risk is perceived by the general public. This new material is covered in two new chapters on risk identification and risk response and by a complete reorganization of the chapters on risk analysis. The style is still very straightforward and easy to read, but there is an increased attention to the theory underlying the principles, and an expanded bibliography is given to guide an exploration of the subject in greater detail. Risk management is demystified by presenting the subject in simple and practical terms, free of technical jargon. Case studies are used extensively to illustrate the concepts discussed