bluuebunny/crossref_metadata_2025_split huggingface dataset:
The CFT$$_6$$ origin of all tree-level 4-point correlators in AdS$$_3 \times S^3$$
Authors: Giusto Stefano , Russo Rodolfo , Tyukov Alexander , Wen Congkao 
Published: August 2020

AbstractWe provide strong evidence that all tree-level 4-point holographic correlators in $$\hbox {AdS}_3 \times S^3$$AdS3×S3 are constrained by a hidden 6D conformal symmetry. This property has been discovered in the $$\hbox {AdS}_5 \times S^5$$AdS5×S5 context and noticed in the tensor multiplet subsector of the AdS$$_3 \times S^3$$3×S3 theory. Here we extend it to general AdS$$_3 \times S^3$$3×S3 correlators which contain also the chiral primary operators of spin zero and one that sit in the gravity multiplet. The key observation is that the 6D conformal primary field associated with these operators is not a scalar but a self-dual 3-form primary. As an example, we focus on the correlators involving two fields in the tensor multiplets and two in the gravity multiplet and show that all such correlators are encoded in a conformal 6D correlator between two scalars and two self-dual 3-forms, which is determined by three functions of the cross ratios. We fix these three functions by comparing with the results of the simplest correlators derived from an explicit supergravity calculation.
Probing sterile neutrinos in B (D) meson decays at Belle II (BESIII)
Authors: Kim C. S. , Kwon Youngjoon , Lee Donghun , Oh Sechul , Sahoo Dibyakrupa 
Published: August 2020

AbstractWe present, how a systematic study of $$B \rightarrow D\ell N$$B→DℓN ($$D \rightarrow K \ell N$$D→KℓN) decays with $$\ell =\mu ,\tau $$ℓ=μ,τ, at Belle II (BESIII) can provide unambiguous signature of a heavy neutrino N and/or constrain its mixing with active neutrinos $$\nu _\ell $$νℓ, which is parameterized by $$| U_{\ell N} |^2$$|UℓN|2. Our constraint on $$\vert U_{\mu N} \vert ^2$$|UμN|2 that can be achieved from the full Belle II data is comparable with what can be obtained from the much larger data set of the upgraded LHCb. Additionally, our method offers better constraint on $$\vert U_{\mu N} \vert ^2$$|UμN|2 for mass of sterile neutrino $$m_N < 2$$mN<2 GeV. We can also probe the Dirac and Majorana nature of N by observing the sequential decay of N, including suppression from observation of a displaced vertex as well as helicity flip, for Majorana N.
Balancing Assisted Reproductive Technology Dataset for Improving the Efficiency of Incremental Classifiers and Feature Selection Techniques
Authors: Suruliandi A. , Ranjini K. , Raja S. P. 
Published: August 2020

Assisted Reproductive Technology (ART) is a set of medical procedures primarily used to address infertility. Success Rate of ART is very low because it is affected by large number of variables. Machine Learning Techniques are now applied to predict ART outcome and to find strategies to improve success rate. For this, determining the best performing classifier for ART is very important. Previously, some classifiers are applied to ART with static data. But, in reality, the datasets are dynamic in nature and require dynamic setup which can be achieved with the help of Incremental Classifiers. Due to low success rate, the ART dataset contains less number of records for positive results that make the dataset imbalanced. This research work first finds the best evaluation metric for classification on imbalanced dataset and then balances the dataset using three different balancing techniques such as undersampling, oversampling and Synthetic Minority Oversampling Technique (SMOTE) and applies five different Incremental Classifiers, namely Stochastic Gradient Descent (SGD), Stochastic Primal Estimated sub-GrAdient SOlver for Support vector machine (SPegasos), Naïve Bayes Updatable, Instance Based (IBk), Averaged One Dependence Estimators (A1DE) Updatable and finds the best balancing technique and suitable classifier for ART outcome prediction. The result shows that for an imbalanced dataset Receiver Operating Characteristics (ROC) Area may be taken as a metric instead of the accuracy. It is found that SMOTE is best method for balancing the ART dataset and IB1 classifier performs well for the balanced data with the high prediction rate of 92.3 for ROC. Finally, various Feature Selection methods are applied to the top three best performing classifiers and suitable feature selection method for each classifier is identified.
Efficient Latency Control in Fog Deployments via Hardware-Accelerated Popularity Estimation
Authors: Enguehard Marcel , Desmouceaux Yoann , Carofiglio Giovanna 
Published: August 2020

Introduced as an extension of the Cloud at the network edge for computing and storage purposes, the Fog is increasingly considered a key enabler for Internet-of-Things applications whose latency requirements are not compatible with a Cloud-only approach. Unlike Cloud platforms, which can elastically accommodate large numbers of requests, Fog deployments are usually dimensioned for an average traffic load and, thus, unable to handle sudden bursts of requests without violating latency guarantees. In this article, we address the problem of efficiently controlling Fog admission to guarantee application response time. We propose request-aware admission control (AC) strategies maximizing the number of Fog-handled requests by means of dynamic popularity estimation. In particular, the
LRU-AC
, an AC strategy based on online learning of the request popularity distribution via a Least Recently Used (LRU) filter, is introduced. We contribute an analytical model for assessing LRU-AC performance and quantifying the incurred reduction of Cloud offload cost, w.r.t. both an ideal oracle-based and a request-oblivious AC strategy. Further, we propose a feasible implementation design of LRU-AC on FPGA hardware using Aging Bloom Filters (ABF) to mimic the function of the LRU-AC, while providing a compact memory representation. The use of ABFs for LRU-AC is theoretically validated and verified through simulation. The current implementation shows a throughput of 16.7 Mpps and a processing latency of less than 3μ
s
while multiplying the Fog acceptance-rate by 10 in the evaluated scenario.
Image-based acquisition and modeling of polarimetric reflectance
Authors: Baek Seung-Hwan , Zeltner Tizian , Ku Hyun Jin , Hwang Inseung , Tong Xin , Jakob Wenzel , Kim Min H. 
Published: August 2020

Realistic modeling of the bidirectional reflectance distribution function (BRDF) of scene objects is a vital prerequisite for any type of physically based rendering. In the last decades, the availability of databases containing real-world material measurements has fueled considerable innovation in the development of such models. However, previous work in this area was mainly focused on increasing the visual realism of images, and hence ignored the effect of scattering on the polarization state of light, which is normally imperceptible to the human eye. Existing databases thus only capture scattered flux, or polarimetric BRDF datasets are too directionally sparse (e.g., in-plane) to be usable for simulation.
While subtle to human observers, polarization is easily perceived by any optical sensor (e.g., using polarizing filters), providing a wealth of additional information about shape and material properties of the object under observation. Given the increasing application of rendering in the solution of inverse problems via analysis-by-synthesis and differentiation, the ability to realistically model polarized radiative transport is thus highly desirable.
Polarization depends on the wavelength of the spectrum, and thus we provide the first polarimetric BRDF (pBRDF) dataset that captures the polarimetric properties of real-world materials over the full angular domain, and at multiple wavelengths. Acquisition of such reflectance data is challenging due to the extremely large space of angular, spectral, and polarimetric configurations that must be observed, and we propose a scheme combining image-based acquisition with spectroscopic ellipsometry to perform measurements in a realistic amount of time. This process yields raw Mueller matrices, which we subsequently transform into Rusinkiewicz-parameterized pBRDFs that can be used for rendering.
Our dataset provides 25 isotropic pBRDFs spanning a wide range of appearances: diffuse/specular, metallic/dielectric, rough/smooth, and different color albedos, captured in five wavelength ranges covering the visible spectrum. We demonstrate usage of our data-driven pBRDF model in a physically based renderer that accounts for polarized interreflection, and we investigate the relationship of polarization and material appearance, providing insights into the behavior of characteristic real-world pBRDFs.
Simple and scalable frictional contacts for thin nodal objects
Authors: Daviet Gilles 
Published: August 2020

Frictional contacts are the primary way by which physical bodies interact, yet they pose many numerical challenges. Previous works have devised robust methods for handling collisions in elastic bodies, cloth, or fiber assemblies such as hair, but the performance of many of those algorithms degrades when applied to objects with different topologies or constitutive models, or simply cannot scale to high-enough numbers of contacting points.
In this work we propose a unified approach, able to handle a large class of dynamical objects, that can solve for millions of contacts with unbiased Coulomb friction while keeping computation time and memory usage reasonable. Our method allows seamless coupling between the various simulated components that comprise virtual characters and their environment. Furthermore, our proposed approach is simple to implement and can be easily integrated in popular time integrators such as Projected Newton or ADMM.
Abstract A28: Deregulation of KMT2D promotes squamous differentiation in a mouse model of muscle-invasive bladder cancer
Authors: Rong Lijie , Abate-Shen Cory 
Published: August 2020

Abstract
Cell differentiation and plasticity is precisely controlled by specific gene expression programs coordinate with chromatin remodeling, which are often deregulated during tumorigenesis. While divergent histopathologic differentiation in bladder cancer is prevalent and may affect clinical outcome, the underlying mechanisms are not well understood. Here, we aim to elucidate mechanisms for alteration of the histopathologic and molecular features of muscle-invasive bladder cancer (MIBC) by interrogating the functional role of chromatin-remodeling genes using relevant genetically engineered mouse models (GEMMs). High frequency of mutations in chromatin-remodeling genes encoding COMPASS-like chromatin-remodeling complex members has been identified in human MIBC. These genes include “writers” that create histone post-translational modification, such as the lysine methyltransferase KMT2D (MLL2/4), and “erasers” that remove these modifications, such as the lysine demethylase KDM6A (UTX). We have generated GEMMs that enable bladder-specific conditional inactivation of individual chromatin-remodeling genes in combination with loss of function of Trp53 and Pten, which leads to MIBC. Interestingly, bladder tumors from GEMMs having inactivation of Kmt2d along with Trp53 and Pten (e.g., Kmt2d;Trp53;Pten mice) develop a variant histologic phenotype that is not observed in tumors from either the Trp53;Pten or Kdm6a;Trp53;Pten mice. Specifically, these Kmt2d-inactivated tumors share histopathologic features in common with human urothelial carcinoma that display squamous differentiation. Furthermore, expression profiling of these Kmt2d;Trp53;Pten bladder tumors identified a unique set of differentially expressed genes that are enriched for genes representing squamous differentiation in other nonbladder cancers. Our findings suggest that deregulated Kmt2d expression promotes squamous differentiation in MIBC, at least in context of Trp53;pten coinactivation.
Citation Format: Lijie Rong, Cory Abate-Shen. Deregulation of KMT2D promotes squamous differentiation in a mouse model of muscle-invasive bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr A28.
Abstract B02: TP63 isoform expression landscape associations with bladder cancer patient outcomes
Authors: Bankhead Armand , McMaster Thomas , Palmbos Phillip L. 
Published: August 2020

Abstract
Bladder cancer will cause an estimated 17,000 deaths this year in the United States. Transformation-related protein 63 (TP63) is a p53 family transcription factor that has been shown to be important for development and is commonly expressed in bladder cancer. However, the relationship of TP63 to bladder cancer patient outcome remains unclear. Some studies have associated TP63 expression with a positive patient outcome, while others have shown TP63 expression is associated with reduced survival. One potential explanation for this discrepancy is that TP63 is expressed as one of at least 15 unique isoforms, of which there are two main types (TAp63 and DNp63) exhibiting unique functional domains. In this work we define the landscape of TP63 isoform expression and quantify its association with bladder cancer patient outcome using RNA sequencing data from the TCGA bladder cancer cohort and other human bladder cancer samples. To examine the TP63 isoform landscape in bladder cancer, we utilized annotations from Refgene and Ensembl databases and used Cufflinks to identify two potentially novel TP63 isoforms not represented in current TP63 gene annotations. To quantitate isoform expression, we used multiple RNA-Seq expression quantification algorithms (Cufflinks, Kallisto, and Salmon) to infer isoform expression estimates of 15 TP63 isoforms for 408 bladder cancer patients from TCGA. We experimentally validated our findings using a collection of 14 bladder cancer cell lines and show that results translated to an additional collection of 19 primary bladder cancer tumor samples. We find that DNp63 is significantly higher in patients with luminal papillary and basal squamous subtypes, while TAp63 was selectively expressed in patients with basal squamous bladder cancer. Analysis of TP63 isoform expression with clinical data demonstrated that DNp63 trends with improved patient survival (HR=0.94, CI=0.88,1.006, P=0.082), whereas TAp63 is associated with worse patient survival (HR = 1.8, CI=1.38,2.4, P=0.00022) in human bladder cancer. Taken together, this work represents a comprehensive assessment of TP63 isoform expression in the TCGA bladder cancer cohort using contemporary, extended gene isoform annotations and quantifications—underscoring the need for profiling additional bladder cancer cohorts with RNA-Seq for further insight to isoform-specific expression. It also implicates TP63 isoform expression as a potential biomarker of clinical patient outcomes.
Citation Format: Armand Bankhead III, Thomas McMaster, Phillip L. Palmbos. TP63 isoform expression landscape associations with bladder cancer patient outcomes [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr B02.
Abstract IA11: Chemotherapy remodels the bladder cancer immune microenvironment
Authors: Kim William Y. 
Published: August 2020

Abstract
In the United States urothelial carcinoma (UC) of the bladder is the 4th and 9th most frequent malignancy in men and women, respectively, with around 74,000 new cases and 16,000 deaths in 2017. High-grade (HG), muscle-invasive bladder tumors account for the majority of those deaths as patients with metastatic disease have a 5-year survival rate of only 15%. The current standard-of-care first-line therapy for metastatic disease is cisplatin-based combination chemotherapy or immune checkpoint inhibition in patients who are platinum ineligible. Novel immune checkpoint (IC) inhibitors, including anti-PD1 and anti-PD-L1, represent a paradigm shift in cancer therapy and have demonstrated substantial clinical benefits in patients with advanced UC. Despite the enthusiasm engendered by PD-1/PD-L1 axis blockade in metastatic UC, only 15-25% of patients treated in published trials had objective responses. Preliminary studies from our laboratory show that chemotherapy remodels the immune microenvironment of muscle-invasive bladder cancers. We have begun to investigate the mechanisms by which chemotherapy drives a heightened immune response using our recently described genetically engineered murine (GEM) models of bladder cancer.
Citation Format: William Y. Kim. Chemotherapy remodels the bladder cancer immune microenvironment [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr IA11.
An In Vivo Kras Allelic Series Reveals Distinct Phenotypes of Common Oncogenic Variants
Authors: Zafra Maria Paz , Parsons Marie J. , Kim Jangkyung , Alonso-Curbelo Direna , Goswami Sukanya , Schatoff Emma M. , Han Teng , Katti Alyna , Fernandez Maria Teresa Calvo , Wilkinson John E. , Piskounova Elena , Dow Lukas E. 
Published: August 2020

Abstract

KRAS is the most frequently mutated oncogene in cancer, yet there is little understanding of how specific KRAS amino acid changes affect tumor initiation, progression, or therapy response. Using high-fidelity CRISPR-based engineering, we created an allelic series of new LSL-Kras mutant mice, reflecting codon 12 and 13 mutations that are highly prevalent in lung (KRASG12C), pancreas (KRASG12R), and colon (KRASG13D) cancers. Induction of each allele in either the murine colon or pancreas revealed striking quantitative and qualitative differences between KRAS mutants in driving the early stages of transformation. Furthermore, using pancreatic organoid models, we show that KRASG13D mutants are sensitive to EGFR inhibition, whereas KRASG12C-mutant organoids are selectively responsive to covalent G12C inhibitors only when EGFR is suppressed. Together, these new mouse strains provide an ideal platform for investigating KRAS biology in vivo and for developing preclinical precision oncology models of KRAS-mutant pancreas, colon, and lung cancers.

Significance:
KRAS is the most frequently mutated oncogene. Here, we describe new preclinical models that mimic tissue-selective KRAS mutations and show that each mutation has distinct cellular consequences in vivo and carries differential sensitivity to targeted therapeutic agents.
See related commentary by Kostyrko and Sweet-Cordero, p. 1626.
This article is highlighted in the In This Issue feature, p. 1611
Effects of Collateral Status on Infarct Distribution Following Endovascular Therapy in Large Vessel Occlusion Stroke
Authors: Al-Dasuqi Khalid , Payabvash Seyedmehdi , Torres-Flores Gerardo A. , Strander Sumita M. , Nguyen Cindy Khanh , Peshwe Krithika U. , Kodali Sreeja , Silverman Andrew , Malhotra Ajay , Johnson Michele H. , Matouk Charles C. , Schindler Joseph L. , Sansing Lauren H. , Falcone Guido J. , Sheth Kevin N. , Petersen Nils H. 
Published: August 2020

Background and Purpose:
We aim to examine effects of collateral status and post-thrombectomy reperfusion on final infarct distribution and early functional outcome in patients with anterior circulation large vessel occlusion ischemic stroke.

Methods:
Patients with large vessel occlusion who underwent endovascular intervention were included in this study. All patients had baseline computed tomography angiography and follow-up magnetic resonance imaging. Collateral status was graded according to the criteria proposed by Miteff et al and reperfusion was assessed using the modified Thrombolysis in Cerebral Infarction (mTICI) system. We applied a multivariate voxel-wise general linear model to correlate the distribution of final infarction with collateral status and degree of reperfusion. Early favorable outcome was defined as a discharge modified Rankin Scale score ≤2.

Results:

Of the 283 patients included, 129 (46%) had good, 97 (34%) had moderate, and 57 (20%) had poor collateral status. Successful reperfusion (mTICI 2b/3) was achieved in 206 (73%) patients. Poor collateral status was associated with infarction of middle cerebral artery border zones, whereas worse reperfusion (mTICI scores 0–2a) was associated with infarction of middle cerebral artery territory deep white matter tracts and the posterior limb of the internal capsule. In multivariate regression models, both mTICI (
P
<0.001) and collateral status (
P
<0.001) were among independent predictors of final infarct volumes. However, mTICI (
P
<0.001), but not collateral status (
P
=0.058), predicted favorable outcome at discharge.

Conclusions:
In this cohort of patients with large vessel occlusion stroke, both the collateral status and endovascular reperfusion were strongly associated with middle cerebral artery territory final infarct volumes. Our findings suggesting that baseline collateral status predominantly affected middle cerebral artery border zones infarction, whereas higher mTICI preserved deep white matter and internal capsule from infarction; may explain why reperfusion success—but not collateral status—was among the independent predictors of favorable outcome at discharge. Infarction of the lentiform nuclei was observed regardless of collateral status or reperfusion success.
Streamlined Poststroke Treatment Order Sets During the SARS-CoV-2 Pandemic
Authors: Gioia Laura C. , Poppe Alexandre Y. , Laroche Roxanne , Dacier-Falque Tristan , Sévigny Isabelle , Daneault Nicole , Deschaintre Yan , Jacquin Grégory , Stapf Christian , Odier Celine 
Published: August 2020

Background and Purpose:
Standard poststroke treatment monitoring protocols are made problematic during the coronavirus disease 2019 (COVID-19) pandemic by the frequency of patient assessments, requiring repeated donning and doffing procedures in a short interval of time.

Methods:
A streamlined poststroke treatment protocol was developed to limit frequency of patient encounters while maximizing the yield of each encounter by grouping together different components of poststroke care into single bedside visits.

Results:
Streamlined order sets were developed late March 2020. During the first 6 weeks following implementation, 70 patients were admitted to a geographically defined designated warm COVID-19 unit with modified poststroke care order sets. Of these, 33 (47.1%) patients received acute reperfusion therapy. All but 3 patients evolved favorably with either stable or improving National Institutes of Health Stroke Scale at 24 hours. In the 3 patients who experienced early neurological deterioration, none were found to be attributable to insufficient patient monitoring.

Conclusions:
Adapting preexisting poststroke care protocols may be necessary while the risk of COVID-19 infection remains high. We propose a streamlined approach to facilitate poststroke monitoring in patients with stroke with unknown COVID status.