Miracle-dz/UniFAR-FTUs huggingface dataset:
3D Human pose and shape estimation from multi-view imagery

In this study we present robust solution for estimating 3D pose and shape of human targets from multiple, synchronized video streams. The objective is to automatically estimate physical attributes of the targets that would allow us to analyze its behavior non-intrusively. Proposed system estimates the anthropometric skeleton, pose and shape of the human target from the 3D visual hull reconstructed from multiple silhouettes of the target. Discriminative (bottom-up) method is used to first initialize 3D pose of the targets using low-level features extracted from the 2D image. The pose is refined using generative (top-down) method that also estimates the optimal skeleton of the target using anthropometric prior models learned from the CAESAR dataset. Statistical shape models are also learned from the CAESAR dataset and are used to model both global and local shape variability of human body parts. We also propose a novel optimization scheme to fit 3D shape by searching in the parametric space of local parts model and constraining the overall shape using a global shape model. The system provides a useful framework for automatically identifying dispropotionate body parts, estimating size of backpacks and inferring attributes like gender, age and ethnicity of the human target.
A Mutant Impaired in the Production of Plastome-Encoded Proteins Uncovers a Mechanism for the Homeostasis of Isoprenoid Biosynthetic Enzymes in Arabidopsis Plastids[W]

The plastid-localized methylerythritol phosphate (MEP) pathway synthesizes the isoprenoid precursors for the production of essential photosynthesis-related compounds and hormones. We have identified an Arabidopsis thaliana mutant, rif1, in which posttranscriptional upregulation of MEP pathway enzyme levels is caused by the loss of function of At3g47450, a gene originally reported to encode a mitochondrial protein related to nitric oxide synthesis. However, we show that nitric oxide is not involved in the regulation of the MEP pathway and that the encoded protein is a plastid-targeted homolog of the Bacillus subtilis YqeH protein, a GTPase required for proper ribosome assembly. Consistently, in rif1 seedlings, decreased levels of plastome-encoded proteins were observed, with the exception of ClpP1, a catalytic subunit of the plastidial Clp protease complex. The unexpected accumulation of ClpP1 in plastids with reduced protein synthesis suggested a compensatory mechanism in response to decreased Clp activity levels. In agreement, a negative correlation was found between Clp protease activity and MEP pathway enzyme levels in different experiments, suggesting that Clp-mediated degradation of MEP pathway enzymes might be a mechanism used by individual plastids to finely adjust plastidial isoprenoid biosynthesis to their functional and physiological states.
Generative Data Models for Validation and Evaluation of Visualization Techniques

We argue that there is a need for substantially more research on the use of generative data models in the validation and evaluation of visualization techniques. For example, user studies will require the display of representative and uncon-founded visual stimuli, while algorithms will need functional coverage and assessable benchmarks. However, data is often collected in a semi-automatic fashion or entirely hand-picked, which obscures the view of generality, impairs availability, and potentially violates privacy. There are some sub-domains of visualization that use synthetic data in the sense of generative data models, whereas others work with real-world-based data sets and simulations. Depending on the visualization domain, many generative data models are "side projects" as part of an ad-hoc validation of a techniques paper and thus neither reusable nor general-purpose. We review existing work on popular data collections and generative data models in visualization to discuss the opportunities and consequences for technique validation, evaluation, and experiment design. We distill handling and future directions, and discuss how we can engineer generative data models and how visualization research could benefit from more and better use of generative data models.
Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options

This article provides several new insights into the economic sources of skewness. First, we document the differential pricing of individual equity options versus the market index, and relate it to variations in return skewness. Second, we show how risk aversion introduces skewness in the risk-neutral density. Third, we derive laws that decompose individual return skewness into a systematic component and an idiosyncratic component. Empirical analysis of OEX options and 30 stocks demonstrates that individual risk-neutral distributions differ from that of the market index by being far less negatively skewed. This paper explains the presence and evolution of risk-neutral skewness over time and in the cross-section of individual stocks.
Validation and Robustness Analysis of Dynamic Contrast Enhanced MRI

In Dynamic Contrast Enhanced MRI there are several steps from the initial signal to obtaining the pharmacokinetic parameters for tumor characterization. The aim of this work was to validate the steps in the flow of data focusing on T1-mapping, Contrast Agent (CA)-quantification and the pharmacokinetical (PK) model, using a digital phantom of a head. In the Digital Phantom tissues are assigned necessary values to obtain both a regular and contrast enhanced (using Parker AIF) representation and simulating an SPGR signal. The data analysis was performed in a software called MICE, as well as the Digital Phantom developed at the department of Radiation Sciences at Umea University. The method of variable flip angles for the T1-mapping was analyzed with respect to SNR and number of flip angles, finding that the median value in each tissue is correct and stable. A "two point" inversion recovery sequence was tested with optimal combination of inversion times for white matter and CSF and obtaining correct T1-values when the inversion times were close to the tissue T1, otherwise with large deviations seen. Three different methods for CA-quantification were analyzed and a large underestimation was found assuming a linearity between signal and CA-concentration mainly for vessels at about 60%, but also for other tissue such as white matter at about 15%, improving when the assumption was removed. Still there was a noticeable underestimation of 30% and 10% and the quantification was improved further, achieving a near perfect agreement with the reference concentration, taking the T2*-effect into account. Applying Kety-model, discarding the vp-term, Ktrans was found to be stable with respect to noise in the tumor rim but ve noticeably underestimated with about 50%. The effect of different bolus arrival time, shifting the AIF required in the PK-model with respect to the CA-concentration, was tested with values up to 5 s, obtaining up to about 5% difference in Ktrans as well as the effect of a vascular transport function obtained by the means of an effective mean transit time up to 5 s and up to about 5% difference in Ktrans.
X4 Human Immunodeficiency Virus Type 1 gp120 Promotes Human Hepatic Stellate Cell Activation and Collagen I Expression through Interactions with CXCR4

Background & Aims Patients coinfected with HIV-1 and HCV develop more rapid liver fibrosis than patients monoinfected with HCV. HIV RNA levels correlate with fibrosis progression implicating HIV directly in the fibrotic process. While activated hepatic stellate cells (HSCs) express the 2 major HIV chemokine coreceptors, CXCR4 and CCR5, little is known about the pro-fibrogenic effects of the HIV-1 envelope protein, gp120, on HSCs. We therefore examined the in vitro impact of X4 gp120 on HSC activation, collagen I expression, and underlying signaling pathways and examined the in vivo expression of gp120 in HIV/HCV coinfected livers. Methods Primary human HSCs and LX-2 cells, a human HSC line, were challenged with X4 gp120 and expression of fibrogenic markers assessed by qRT-PCR and Western blot +/− either CXCR4-targeted shRNA or anti-CXCR4 neutralizing antibody. Downstream intracellular signaling pathways were evaluated with Western blot and pre-treatment with specific pathway inhibitors. Gp120 immunostaining was performed on HIV/HCV coinfected liver biopsies. Results X4 gp 120 significantly increased expression of alpha-smooth muscle actin (a-SMA) and collagen I in HSCs which was blocked by pre-incubation with either CXCR4-targeted shRNA or anti-CXCR4 neutralizing antibody. Furthermore, X4 gp120 promoted Extracellular signal-regulated kinase (ERK) 1/2 phosphorylation and pretreatment with an ERK inhibitor attenuated HSC activation and collagen I expression. Sinusoidal staining for gp120 was evident in HIV/HCV coinfected livers. Conclusions X4 HIV-1 gp120 is pro-fibrogenic through its interactions with CXCR4 on activated HSCs. The availability of small molecule inhibitors to CXCR4 make this a potential anti-fibrotic target in HIV/HCV coinfected patients.
Wage Gaps , Capital and Skills ∗

A novel testing procedure is devised to assess the impact of traded investment goods, technical change and capital accumulation on labor demand. The procedure identifies capital-affected skill groups and results in an according production function. The method is applied to a newly constructed matched firm-worker data set for the Brazilian manufacturing sector during 1992-98, a period immediately following trade liberalization. The data distinguish nine schooling levels. Capital is found to affect mostly workers with secondary schooling. New equipment is a substitute to those skills and tends to reduce the wage differential of workers with secondary schooling vis à vis less and more educated workers. Immaterial skill-biased technical change may be an additional force on the widening wage gap of college graduates vis à vis secondary-schooled workers. Despite a continuing replacement of domestic capital goods with imported equipment, the elasticity of skill-capital substitution remains constant. JEL F16, J31, O33 ∗We thank Ricardo Friede at Datamec and Paulo Furtado at IPEA-DF for their generous help with RAIS, and IBGE’s Departamento de Indústria for ongoing support with PIA. Rodrigo Dias provided excellent research assistance. Prita Subramanian and seminar participants at the LACEA 2002 conference made thoughtful suggestions. We thank the World Bank and the Ministério do Trabalho e Emprego Braśılia for financial support. An earlier version of the paper had the title “The wage gap in Brazil: Is it capital accumulation, skill bias or neither one? ” and was part of the authors’ work for the World Bank’s 2002 Annual Report of the Chief Economist, Latin America and Caribbean Region. ‡c.corseuil@ucl.ac. uk ‡‡muendler@ucsd.edu (www.econ.ucsd.edu/muendler), corresponding author
Extremal solutions and instantaneous complete blow-up for elliptic and parabolic problems

whenever g > 0 is increasing and convex on R and superlinear at +∞ in the sense (7) stated below. Under these assumptions, the extremal parameter of (2) satisfies 0 < λ∗ < ∞. Here and throughout the paper, Ω is a smooth bounded domain of R . For each 0 ≤ λ < λ∗, the minimal solution of (2) is classical. Their limit as λ ↑ λ∗ is the extremal solution u∗ and it may be singular (i.e. unbounded) for some nonlinearities and domains. When g(u) = e, it is known that u∗ ∈ L∞(Ω) if N ≤ 9 (for every Ω), while u∗(x) = log(1/|x|) if N ≥ 10 and Ω = B1. Brezis and Vázquez [BV] raised the question of determining the
Assessment of the risk posed by bovine spongiform encephalopathy in cattle in Great Britain and the impact of potential changes to current control measures

We extended an existing back–calculation model to analyse data on reported clinical cases of bovine spongiform encephalopathy (BSE), data from random testing of healthy animals slaughtered in abattoirs and testing data from animals reported as sick or dying on the farm. Extensive analysis of demographic data was also undertaken. We estimated past and current BSE infection prevalences in the cattle population and the degree of case under–ascertainment resulting from excess mortality in cattle near to disease onset. Ongoing levels of human exposure to BSE infectivity were also estimated, together with the effect on these of a range of possible exposure–reduction strategies that might replace the current rule banning tissue from cattle over 30 months (OTM) of age from the human food supply. While any policy change that allows a wider age range of animals into the human food supply will increase levels of human exposure to infectivity, the risk posed by such increases is small by comparison with historical exposure levels. Making the pessimistic assumption that there will be 5000 deaths during the variant Creutzfeldt–Jakob disease (vCJD) epidemic in total, our analysis indicates that replacement of the OTM rule with testing would result in 0.04 additional vCJD deaths over the next 60 years. However, there is substantial (more than 40–fold) uncertainty surrounding this estimate, the sources of which are discussed.
Parallel interleaver design and VLSI architecture for low-latency MAP turbo decoders

Standard VLSI implementations of turbo decoding require substantial memory and incur a long latency, which cannot be tolerated in some applications. A parallel VLSI architecture for low-latency turbo decoding, comprising multiple single-input single-output (SISO) elements, operating jointly on one turbo-coded block, is presented and compared to sequential architectures. A parallel interleaver is essential to process multiple concurrent SISO outputs. A novel parallel interleaver and an algorithm for its design are presented, achieving the same error correction performance as the standard architecture. Latency is reduced up to 20 times and throughput for large blocks is increased up to six-fold relative to sequential decoders, using the same silicon area, and achieving a very high coding gain. The parallel architecture scales favorably: latency and throughput are improved with increased block size and chip area.
Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management

Traffic congestion and automobile accidents are two of the leading causes of decreased standard of living and lost productivity in urban settings. Recent advances in artificial intelligence and, specifically, intelligent vehicle technology suggest that vehicles driven entirely by autonomous agents will be possible in the near future. In previous work, we presented a novel reservation-based approach for governing interactions of multiple autonomous vehicles, specifically at intersections. This approach alleviated many traditional problems associated with intersections, in terms of both safety and efficiency. However, such a system relies on all vehicles being equipped with the requisite technology — a restriction that would make implementing such a system in the real world extremely difficult. In this paper, we augment the system such that it is able to accomodate traditional human-operated vehicles using existing infrastructure. Furthermore, we show that as the number of autonomous vehicles on the road increases, traffic delays decrease monotonically toward the levels exhibited in the system involving only autonomous vehicles. Additionally, we demonstrate how the system can be extended to allow high-priority vehicles such as ambulances, police cars, or fire trucks through more quickly without placing undue burden on other vehicles. Both augmentations are fully implemented and tested in our custom simulator, and we present detailed experimental results attesting to their effectiveness.
Imaging the Biodistribution and Performance of Transplanted Stem Cells with PET

Several clinical trials have assessed the efficacy of transplanted stem cells for treatment of muscle-related diseases (1), yet clinical translation of these cell-based therapies has been limited by the host immune response, ineffective homing strategies for getting the donor cells to targeted musculature, and the intricate generation of large numbers of transplantable cells. Because highly invasive tissue biopsies are often required to diagnose muscle-related diseases and monitor their treatment, there is a dire need for alternative noninvasive approaches. Recently, PET imaging of biomarkers has shown great potential for tracking disease progression and monitoring therapeutic interventions. More specifically, PET imaging can track injected cells of interest that have been directly labeled with an imaging tag or indirectly labeled with a reporter, allowing for in vivo tracking of their fate. This ability virtually eliminates the need for highly invasive procedures, in addition to providing fast and reliable data.
Characterization of Active Sites/Entities and Redox/Catalytic Correlations in Copper-Ceria-Based Catalysts for Preferential Oxidation of CO in H2-Rich Streams

This article reviews work done at authors’ laboratories about catalysts based on combinations between copper and ceria for preferential oxidation of CO in H2-rich streams (CO-PROX). The main focus of this review is the characterization of active sites for the process on the basis of spectroscopic analysis of the systems under reaction conditions (operando techniques). On such a basis, it is exposed the state of the art in this field in connection with results obtained in other laboratories.
The Dawes Review 1: Kinematic Studies of Star-Forming Galaxies Across Cosmic Time

Abstract The last seven years have seen an explosion in the number of Integral Field galaxy surveys, obtaining resolved 2D spectroscopy, especially at high-redshift. These have taken advantage of the mature capabilities of 8–10 m class telescopes and the development of associated technology such as AO. Surveys have leveraged both high spectroscopic resolution enabling internal velocity measurements and high spatial resolution from AO techniques and sites with excellent natural seeing. For the first time, we have been able to glimpse the kinematic state of matter in young, assembling star-forming galaxies and learn detailed astrophysical information about the physical processes and compare their kinematic scaling relations with those in the local Universe. Observers have measured disc galaxy rotation, merger signatures, and turbulence-enhanced velocity dispersions of gas-rich discs. Theorists have interpreted kinematic signatures of galaxies in a variety of ways (rotation, merging, outflows, and feedback) and attempted to discuss evolution vs. theoretical models and relate it to the evolution in galaxy morphology. A key point that has emerged from this activity is that substantial fractions of high-redshift galaxies have regular kinematic morphologies despite irregular photometric morphologies and this is likely due to the presence of a large number of highly gas-rich discs. There has not yet been a review of this burgeoning topic. In this first Dawes review, I will discuss the extensive kinematic surveys that have been done and the physical models that have arisen for young galaxies at high-redshift.
Discriminative Syntactic Reranking for Statistical Machine Translation

This paper describes a method that successfully exploits simple syntactic features for n-best translation candidate reranking using perceptrons. Our approach uses discriminative language modelling to rerank the n-best translations generated by a statistical machine translation system. The performance is evaluated for Arabic-to-English translation using NIST’s MT-Eval benchmarks. Whilst parse trees do not consistently help, we show how features extracted from a simple Part-of-Speech annotation layer outperform two competitive baselines, leading to significant BLEU improvements on three different test sets.
Tumor Suppressor Function of CYLD in Nonmelanoma Skin Cancer

Ubiquitin and ubiquitin-related proteins posttranslationally modify substrates, and thereby alter the functions of their targets. The ubiquitination process is involved in various physiological responses, and dysregulation of components of the ubiquitin system has been linked to many diseases including skin cancer. The ubiquitin pathways activated among skin cancers are highly diverse and may reflect the various characteristics of the cancer type. Basal cell carcinoma and squamous cell carcinoma, the most common types of human skin cancer, are instances where the involvement of the deubiquitination enzyme CYLD has been recently highlighted. In basal cell carcinoma, the tumor suppressor protein CYLD is repressed at the transcriptional levels through hedgehog signaling pathway. Downregulation of CYLD in basal cell carcinoma was also shown to interfere with TrkC expression and signaling, thereby promoting cancer progression. By contrast, the level of CYLD is unchanged in squamous cell carcinoma, instead, catalytic inactivation of CYLD in the skin has been linked to the development of squamous cell carcinoma. This paper will focus on the current knowledge that links CYLD to nonmelanoma skin cancers and will explore recent insights regarding CYLD regulation of NF-κB and hedgehog signaling during the development and progression of these types of human tumors.
Toward benchmarking a general-domain Thai LVCSR System

We believe that a benchmark evaluation is one of the key factors that help accelerate research and development of a Thai speech recognition system as various algorithms and training techniques can be systematically compared. In this paper, we are interested in benchmarking a general-domain Thai Large Vocabulary Continuous Speech Recognition (LVCSR) system using the LOTUS speech corpus. We conducted a set of experiments as an initial attempt to benchmark the performance of a general domain Thai LVCSR system. In our experiments, we explored some variations of three acoustic model training parameters: the number of tied-state triphones, the number of Gaussian mixtures and a list of triphones. For language model training, we evaluated the usefulness of additional data from a large text corpus. We found that an acoustic model trained with higher number of tied-state triphones and higher number of Gaussian mixtures achieved better recognition accuracy. For language model training, we found that using additional data from a large text corpus help improve the recognition performance of the LVCSR system. The best recognition performance in terms of word error rate on the LOTUS evaluation test set (ET) is 24.4%. This result was obtained when a list of triphones manually selected by a linguist was used for training an acoustic model with 3,000 tied-state triphones and 32 Gaussian mixtures while the language model is a linear interpolation of two language models, one trained from the LOTUS training set (TR) and another one trained from the large text corpus BEST.