Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Intensity Correction in the Contextof Image Registration

An image registration algorithm with intensity correction was developed. A particular goal was to apply intensity correction instead of using multimodal similarity measures. The algorithm utilises common Levenberg-Marquardt optimisation. The author has chosen two dimensional affine and one dimensional B-Spline model as spatial transformation, as well as intensity correction models specific to CT images. They are global non-linear mapping and smooth local affine correction. The algorithm was tested experimentally using a wide class of simulated images and a limited class of medical images. Affine registration works properly even for deformations which exceed typical deformation encountered in medical practice. B-Spline registration works properly for small deformations and requires further development to increase capture range. The idea of separating intensity correction mapping from similarity measure is shown to have advantages. Choosing intensity correction model can make the registration algorithm specific to the image class of interest.
Colonic Epithelial Cell Diversity in Health and IBD

Kaushal Parikh 1*, Agne Antanaviciute 1, 2*, David Fawkner-Corbett 1, 4*, Marta Jagielowicz 1 , Anna Aulicino 1, Christoffer Lagerholm 3, Simon Davis 7, James Kinchen 1, Hannah H. Chen1, Nasullah Khalid Alham 4, Neil Ashley 5, Errin Johnson 6, Philip Hublitz 5, Leyuan Bao 1, Joanna Lukomska 1, Rajinder Singh Andev 1, Elisabet Björklund 1, Benedikt M Kessler 7, Roman Fischer 7, Robert Goldin 8, Hashem Koohy 2, Alison Simmons 1§.
MODELLING THE DESTINATION CHOICE OF NEWCASTLE COMMUTERS USING LOCAL REGRESSION TECHNIQUES

Frequently, studies exploring the determinants of commuting flows have adopted global modelling techniques. These techniques estimate a single set of coefficients, implicitly assuming that the same relationship applies across the entire study area. This paper tests that notion, estimating a global spatial interaction model to explain commuting outflows from Newcastle, using census 2016 journey to work data. Results from this model are compared to the information generated using a count data version of a local regression model. Finally, a spatial clustering technique is applied to the estimated coefficients of the local models to identify spatial regimes in the relationship between commuting outflows from Newcastle and the model's estimated parameters.
THE NEGATIVE EFFECTS OF URBAN AGGLOMERATION ON HOUSING AFFORDABILITY IN AUSTRALIA

This study assesses the impacts of continued population growth in the largest Australian cities on housing affordability. Using data from the Australian census and other complementary sources over the period 2001-16, we estimate a system of seemingly unrelated and spatially lagged regressions to identify the relationship between a city’s population size on the one hand, and average wages and housing costs on the other, while controlling for the confounding influence of other geographic, demographic and economic determinants. We find that annual home sales values have risen roughly thirty times faster with population than annual full-time wages across Australia. An increase in the population of an urban area by 100,000 would increase annual fulltime wages by roughly $150 and annual home sales values by roughly $4,800. Our analysis also finds that real wages have not kept up with the high costs of living in large cities. For example, our model predicts that, ceteris paribus, price-to-income ratios (PIRs) in Greater Newcastle could rise from 7.0 to 8.4, if the city grows to the size of Sydney. And PIRs in Sydney themselves could rise from 13.6 to 14.8 by 2056, if the city grows to its expected size of 9.2 million. Relatedly, we find that there are no wage benefits to urban areas situated in close proximity to a large metropolitan centre, but these areas are more likely to have expensive local housing markets due to spatial spillover effects.
Experimental and theoretical study of the 65 Cu ( n , p ) 65 Ni reaction cross section from threshold to 25 MeV energies

reaction cross section from threshold to 25 MeV energies R. K. Singh*1, N. L. Singh*1, Rakesh Chauhan1, Mayur Mehta2, S. V. Suryanarayana3, Rajnikant Makwana1, S. Mukherjee1, B. K. Nayak3, H. Naik4, J. Varmuza5, K. Katovsky5 1Department of Physics, Faculty of Science, The M. S. University of Baroda, Vadodara -390002, INDIA 2Institute for Plasma Research, Gandhinagar-382428, INDIA 3Nuclear Physics Division, Bhabha Atomic Research Centre, Mumbai, INDIA 4Radiochemistry Division, Bhabha Atomic Research Centre, Mumbai, INDIA 5Department of Electrical Power Engineering, Brno University of Technology, Brno-61600, Czech Republic *E-mail: -ratankumar339@gmail.com/nl.singh-phy@msubaroda.ac. in
Bridging the Gap Between Training and Inference of Bayesian Controllable Language Models

Large-scale pre-trained language models have achieved great success on natural language generation tasks. However, it is difficult to control the pre-trained language models to generate sentences with the desired attribute such as topic and sentiment, etc. Recently, Bayesian Controllable Language Models (BCLMs) have been shown to be efficient in controllable language generation. Rather than fine-tuning the parameters of pre-trained language models, BCLMs use external discriminators to guide the generation of pre-trained language models. However, the mismatch between training and inference of BCLMs limits the performance of the models. To address the problem, in this work we propose a"Gemini Discriminator"for controllable language generation which alleviates the mismatch problem with a small computational cost. We tested our method on two controllable language generation tasks: sentiment control and topic control. On both tasks, our method reached achieved new state-of-the-art results in automatic and human evaluations.
Dynamic Network Anomaly Modeling of Cell-Phone Call Detail Records for Infectious Disease Surveillance

Global monitoring of novel diseases and outbreaks is crucial for pandemic prevention. To this end, movement data from cell-phones is already used to augment epidemiological models. Recent work has posed individual cell-phone metadata as a universal data source for syndromic surveillance for two key reasons: (1) these records are already collected for billing purposes in virtually every country and (2) they could allow deviations from people's routine behaviors during symptomatic illness to be detected, both in terms of mobility and social interactions. In this paper, we develop the necessary models to conduct population-level infectious disease surveillance by using cell-phone metadata individually linked with health outcomes. Specifically, we propose GraphDNA---a model that builds Graph neural networks (GNNs) into Dynamic Network Anomaly detection. Using cell-phone call records (CDR) linked with diagnostic information from Iceland during the H1N1v influenza outbreak, we show that GraphDNA outperforms state-of-the-art baselines on individual Date-of-Diagnosis (DoD) prediction, while tracking the epidemic signal in the overall population. Our results suggest that proper modeling of the universal CDR data could inform public health officials and bolster epidemic preparedness measures.
ON COMMUNITIES SIZE AND REMOTENESS: THE ATTRACTIVENESS OF SMALL AND REMOTE COMMUNITIES IN ICELAND COMPARED TO THE LARGER AND MORE CENTRAL ONES

There are quite a few examples in Iceland of people living in isolated and sparsely populated communities, both along the coastline and in inland valleys. Those who live elsewhere, particularly in larger and more successful communities, have sometimes maintained, or at least insinuated, that those people must be trapped in their traditional environment. But can we be sure of this? According to Roback (1982) people’s migrations and choices of residence are influenced by amenity value and quality of life. It is a well-known fact that we do not all have the same tastes, needs and wishes. Therefore, the municipalities or individual communities within each country should differ, as Tiebout (1956) argued. Such theories might, for example, indicate that a strong desire or need for close proximity to a varied, wild and untouched natural environment pulls people towards remote and sparsely populated communities and prevents them from moving away. In this article, we investigate the different wishes and priorities of people inhabiting different regions in Iceland, focusing on residential conditions with special emphasis on the difference between inhabitants of remote and sparsely populated regions and those who live on the fringe of the capital area. The analysis is based on data from a survey of more than 6,000 respondents conducted in 2016 and 2017.
Hacienda Pública Española/Review of Public Economics

Public spending is one effective instrument of fiscal policy in both developed and developing countries. Governments use it to overcome the cyclicality of the economy and to run the economy. However, it can crowd in or crowd out private investment. Is there a difference in the public expenditure – private investment relationship between developed and developing countries? This study looks for an answer by empirically investigating the effect of public expenditure on private investment for a group of 36 developed countries and a group of 98 developing countries from 2002 to 2019. The results by the two-step difference GMM Arellano-Bond estimator seem to be counter-intuitive. Public expenditure crowds out private investment in developed countries but crowds in it in developing countries. The study uses the FE-IV estimator and the PGM estimator to check the robustness of these estimates. The study suggests some arguments to explain the validity of the counter-intuitive results and policy implications for governments in both developed and developing countries.
CAFR-02-2022-0003_proof 2..24

Purpose –The aim of this paper is to examine the effect of information disclosure by unlisted bond issuers on the stock price informativeness of listed firms in the same industry. Design/methodology/approach – This paper takes advantage of information disclosure during the bond issuance and examines the spillover effect of unlisted bond issuers’ information disclosure on listed firms in the stock market. The sample is composed of A-share firms listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2018. All the data are obtained from the China StockMarket and Accounting Research andWIND databases. The impact of bond market information disclosure on price informativeness of listed firms in the same industry is identified through multivariate regression analyses. Findings – Empirical results show that price informativeness of listed firms has a significantly positive associationwith the information disclosure of same-industry unlisted bond issuers. Further analyses show that the above finding is more significant when information disclosure of bond issuers is a more important channel for acquiring industry information (i.e. when industry is more concentrated, when economic uncertainty is high, and when industry information is less transparent) and understanding the industry competitive landscape (i.e. when bond issuers are relatively large, when bond issuers and listed firms have more direct product competition, when bond issuance firms are large-scale state-owned business groups), and when there are more cross-market information intermediaries (i.e. more cross-market institutional investors and more sellside analysts). This paper indicates that information disclosure of bond issuers has a positive spillover effect on the stock market. Originality/value – The novelty of the research is that the authors examine industry information spillover from unlisted firms to listed firms leveraging on unlisted firms’ information disclosure in bond markets.
The Theory of LEGO A Proof Checker for the Extended Calculus of Constructions

LEGO is a computer program for interactive typechecking in the Extended Calculus of Constructions and two of its subsystems. LEGO also supports the extension of these three systems with inductive types. These type systems can be viewed as logics, and as meta languages for expressing logics, and LEGO is intended to be used for interactively constructing proofs in mathematical theories presented in these logics. I have developed LEGO over six years, starting from an implementation of the Calculus of Constructions by Gérard Huet. LEGO has been used for problems at the limits of our abilities to do formal mathematics. In this thesis I explain some aspects of the meta-theory of LEGO’s type systems leading to a machine-checked proof that typechecking is decidable for all three type theories supported by LEGO, and to a verified algorithm for deciding their typing judgements, assuming only that they are normalizing. In order to do this, the theory of Pure Type Systems (PTS) is extended and formalized in LEGO. This extended example of a formally developed body of mathematics is described, both for its main theorems, and as a case study in formal mathematics. In many examples, I compare formal definitions and theorems with their informal counterparts, and with various alternative approaches, to study the meaning and use of mathematical language, and suggest clarifications in the informal usage. Having outlined a formal development far too large to be surveyed in detail by a human reader, I close with some thoughts on how the human mathematician’s state of understanding and belief might be affected by posessing such a thing.
Active Teacher for Semi-Supervised Object Detection

In this paper, we study teacher-student learning from the perspective of data initialization and propose a novel algorithm called Active Teacher11Source code are available at: https://github.com/HunterJLin/ActiveTeacher for semi-supervised object detection (SSOD). Active Teacher extends the teacher-student framework to an iterative version, where the label set is partially initialized and gradually augmented by evaluating three key factors of unlabeled examples, including difficulty, information and diversity. With this design, Active Teacher can maximize the effect of limited label information while improving the quality of pseudo-labels. To validate our approach, we conduct extensive experiments on the MS-COCO benchmark and compare Active Teacher with a set of recently proposed SSOD methods. The experimental results not only validate the superior performance gain of Active Teacher over the compared methods, but also show that it enables the baseline network, i.e., Faster-RCNN, to achieve 100% supervised performance with much less label expenditure, i.e. 40% labeled examples on MS-COCO. More importantly, we believe that the experimental analyses in this paper can provide useful empirical knowledge for data annotation in practical applications.
Performance assessment of CsI(Tl) screens on various substrates for X-ray imaging

Thallium-doped cesium iodide (CsI(Tl)) screens are widely used in X-ray imaging devices because of the columnar structure of CsI(Tl) layer, but few reports focus on the optical role of the substrate in the screen system. In this paper, four substrates including fused silica (SiO2), silver-film coated SiO2, graphite (C) and fiber optic plate (FOP) are used to fabricate CsI(Tl) screens by thermal evaporation. Their imaging performance is evaluated by relative light output (RLO), modulation transfer function (MTF), normalized noise power spectrum (NNPS) and noise equivalent quanta (NEQ). The results reveal that although CsI(Tl) film on graphite plate yields images with the lowest light output, it presents relatively higher spatial resolution and better signal-to-noise characteristics. However, films on SiO2 plate obtain low MTF but high NNPS curves, whether or not coated with silver film. Furthermore, scintillation screens on FOP have bright images with low NNPS and high NEQ, but have the lowest MTF. By controlling the substrate optical features, CsI(Tl) films can be tailed to suit a given application.
Integrating Chapel programs and MPI-Based Libraries for High-performance Graph Analysis Summer project:

1 We identify techniques to interface Chapel programs with parallel, 2 distributed, MPI-based libraries written in C++ without storing mul3 tiple copies of shared data. This integration enables Chapel users 4 to take advantage of the vast array of capabilities developed in 5 parallel numerical libraries without the memory cost of duplicated 6 data. We demonstrate two approaches to interface Chapel code 7 with the MPI-based graph and numerical solver libraries Graki 8 and Trilinos. The rst uses a single Chapel executable to call a C 9 function that interacts with the MPI libraries; it requires Chapel 10 users to understand the Graki library interfaces and link their 11 codes with the MPI-based libraries. The second uses the Unix mmap 12 function to allow separate Chapel and Graki executables to read 13 and write to the same block of memory on a node; it maintains 14 greater independence between the Chapel and MPI-based codes, 15 simplifying the Chapel user’s experience. We also encapsulated the 16 second approach in Docker/Singularity containers to maximize ease 17 of use by Chapel users. Comparisons of the two approaches using 18 shared and distributed memory installations of Chapel show that 19 both approaches are feasible for sharing data between Chapel and 20 MPI-based libraries, yielding similar scalability and performance 21 with no penalty from using mmap. 22
AND LIVER DISEASE

high serum levels achievable with therapeutic doses. There is evidence that some strains of S. aureus may develop resistance to the drug. There is not yet sufficient data to assess the extent or importance of this phenomenon. Dosage and Administration-Tentative adult dosage is 250 to 500 mg three to four times daily. Food in the stomach interferes with absorption. A single 500 mg dose taken in the fasting state produced an average peak serum level of 18 mcg/ml in 12 adults. Approximately 70-80% of the drug is excreted unchanged into the urine within four hours of oral administration on an empty stomach. Toxicity and Side Effects-There is little data on toxicity, but it appears that increased frequency of bowel movements or diarrhea may occur. There is no information concerning possible nephrotoxicity in clinical usage. Allergy to other cephalosporin derivatives, and perhaps to penicillin as well, may make allergic response to cephalexin likely.
Earnings dynamics of immigrants and natives in Sweden 1985–2016

This paper analyzes earnings inequality and earnings dynamics in Sweden over 1985–2016. The deep recession in the early 1990s marks a historic turning point with a massive increase in earnings inequality and earnings volatility, and the impact of the recession and the recovery from it lasted for decades. In the aftermath of the recession, we find steady growth in real earnings across the entire distribution for men and women and decreasing inequality over more than 20 years. Despite the positive trend, large gender differences in earnings dynamics persist. While earnings growth for men is more closely tied to the business cycle, women face much higher volatility overall. Earnings volatility is also substantially higher among foreign‐born workers, reflecting weaker labor market attachment and high risk of large negative shocks for low‐income immigrants. We document an important role of social benefits usage for the overall trends and for differences across subpopulations. Higher benefits enrollment, especially for women and immigrants, is associated with higher earnings volatility. As the generosity and usage of benefit programs declined over time, we find stronger earnings growth among low‐income workers, consistent with higher self‐sufficiency.
Cappella: Establishing Multi-User Augmented Reality Sessions Using Inertial Estimates and Peer-to-Peer Ranging

Current collaborative augmented reality (AR) systems establish a common localization coordinate frame among users by exchanging and comparing maps comprised of feature points. However, relative positioning through map sharing struggles in dynamic or feature-sparse environments. It also requires that users exchange identical regions of the map, which may not be possible if they are separated by walls or facing different directions. In this paper, we present Cappella11Like its musical inspiration, Cappella utilizes collaboration among agents to forgo the need for instrumentation, an infrastructure-free 6-degrees-of-freedom (6DOF) positioning system for multi-user AR applications that uses motion estimates and range measurements between users to establish an accurate relative coordinate system. Cappella uses visual-inertial odometry (VIO) in conjunction with ultra-wideband (UWB) ranging radios to estimate the relative position of each device in an ad hoc manner. The system leverages a collaborative particle filtering formulation that operates on sporadic messages exchanged between nearby users. Unlike visual landmark sharing approaches, this allows for collaborative AR sessions even if users do not share the same field of view, or if the environment is too dynamic for feature matching to be reliable. We show that not only is it possible to perform collaborative positioning without infrastructure or global coordinates, but that our approach provides nearly the same level of accuracy as fixed infrastructure approaches for AR teaming applications. Cappella consists of an open source UWB firmware and reference mobile phone application that can display the location of team members in real time using mobile AR. We evaluate Cappella across mul-tiple buildings under a wide variety of conditions, including a contiguous 30,000 square foot region spanning multiple floors, and find that it achieves median geometric error in 3D of less than 1 meter.
Contextual Instance Decoupling for Robust Multi-Person Pose Estimation

Crowded scenes make it challenging to differentiate persons and locate their pose keypoints. This paper proposes the Contextual Instance Decoupling (CID), which presents a new pipeline for multi-person pose estimation. Instead of relying on person bounding boxes to spatially differentiate persons, CID decouples persons in an image into multiple instance-aware feature maps. Each of those feature maps is hence adopted to infer keypoints for a specific person. Compared with bounding box detection, CID is differentiable and robust to detection errors. Decoupling persons into different feature maps allows to isolate distractions from other persons, and explore context cues at scales larger than the bounding box size. Experiments show that CID outperforms previous multi-person pose estimation pipelines on crowded scenes pose estimation benchmarks in both accuracy and efficiency. For instance, it achieves 71.3% AP on CrowdPose, outperforming the recent single-stage DEKR by 5.6%, the bottom-up CenterAttention by 3.7%, and the top-down JC-SPPE by 5.3%. This advantage sustains on the commonly used COCO benchmark††Code is available at https://github.com/kennethwdk/CID.