bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structure of Chern-Simons scattering amplitudes from topological equivalence theorem and double-copy
Authors: Hang Yan-Feng , He Hong-Jian , Shen Cong 
Published: January 2022

Abstract
We study the mechanism of topological mass-generation for 3d Chern-Simons (CS) gauge theories, where the CS term can retain the gauge symmetry and make gauge boson topologically massive. Without CS term the 3d massless gauge boson has a single physical transverse polarization state, while adding the CS term converts it into a massive physical polarization state and conserves the total physical degrees of freedom. We formulate the mechanism of topological mass-generation at S-matrix level. For this, we propose and prove a Topological Equivalence Theorem (TET) which connects the N-point scattering amplitude of the gauge boson’s physical polarization states ($$ {A}_{\mathrm{P}}^a $$

A
P
a

) to that of the transverse polarization states ($$ {A}_{\mathrm{T}}^a $$

A
T
a

) under high energy expansion. We present a general 3d power counting method on the leading energy dependence of the scattering amplitudes in both topologically massive Yang-Mills (TMYM) and topologically massive gravity (TMG) theories. With these, we uncover a general energy cancellation mechanism for N -gauge boson scattering amplitudes which predicts the cancellation E4→ E4−N at tree level. Then, we compute the 4-gauge boson amplitudes of $$ {A}_{\mathrm{P}}^a $$

A
P
a

-states and $$ {A}_{\mathrm{T}}^a $$

A
T
a

-states, with which we explicitly demonstrate the TET and establish such energy cancellations for N = 4. We further extend the double-copy approach to reconstruct the massive 4-graviton amplitude of TMG from the massive 4-gauge boson amplitude of TMYM. With these, we uncover striking large energy cancellations in the 4-graviton amplitude: E12→ E1, and establish its correspondence to the leading energy cancellation E4→ E0in the 4-gauge boson amplitude of TMYM.
Saturation of thermal complexity of purification
Authors: Haque S. Shajidul , Jana Chandan , Underwood Bret 
Published: January 2022

Abstract
We purify the thermal density matrix of a free harmonic oscillator as a two-mode squeezed state, characterized by a squeezing parameter and squeezing angle. While the squeezing parameter is fixed by the temperature and frequency of the oscillator, the squeezing angle is otherwise undetermined, so that the complexity of purification is obtained by minimizing the complexity of the squeezed state over the squeezing angle. The resulting complexity of purification of the thermal state is minimized at non-zero values of the squeezing angle and saturates to an order one number at low frequencies, indicating that there is no additional operator cost required to build thermal mixed states when the oscillator probes length scales that are large compared to the thermal length scale. We also review applications in which thermal density matrices arise for quantum fields on curved spacetimes, including Hawking radiation and a simple model of decoherence of cosmological density perturbations in the early Universe. The complexity of purification for these mixed states also saturates as a function of the effective temperature, which may have interesting consequences for the quantum information stored in these systems.
Large N optimization for multi-matrix systems
Authors: de Mello Koch Robert , Jevicki Antal , Liu Xianlong , Mathaba Kagiso , Rodrigues João P. 
Published: January 2022

Abstract
In this work we revisit the problem of solving multi-matrix systems through numerical large N methods. The framework is a collective, loop space representation which provides a constrained optimization problem, addressed through master-field minimization. This scheme applies both to multi-matrix integrals (c = 0 systems) and multi-matrix quantum mechanics (c = 1 systems). The complete fluctuation spectrum is also computable in the above scheme, and is of immediate physical relevance in the later case. The complexity (and the growth of degrees of freedom) at large N have stymied earlier attempts and in the present work we present significant improvements in this regard. The (constrained) minimization and spectrum calculations are easily achieved with close to 104 variables, giving solution to Migdal-Makeenko, and collective field equations. Considering the large number of dynamical (loop) variables and the extreme nonlinearity of the problem, high precision is obtained when confronted with solvable cases. Through numerical results presented, we prove that our scheme solves, by numerical loop space methods, the general two matrix model problem.
Sialic acid blockade in dendritic cells enhances CD8+ T cell responses by facilitating high-avidity interactions
Authors: Balneger N. , Cornelissen L. A. M. , Wassink M. , Moons S. J. , Boltje T. J. , Bar-Ephraim Y. E. , Das K. K. , Søndergaard J. N. , Büll C. , Adema G. J. 
Published: January 2022

AbstractSialic acids are negatively charged carbohydrates that cap the glycans of glycoproteins and glycolipids. Sialic acids are involved in various biological processes including cell–cell adhesion and immune recognition. In dendritic cells (DCs), the major antigen-presenting cells of the immune system, sialic acids emerge as important regulators of maturation and interaction with other lymphocytes including T cells. Many aspects of how sialic acids regulate DC functions are not well understood and tools and model systems to address these are limited. Here, we have established cultures of murine bone marrow-derived DCs (BMDCs) that lack sialic acid expression using a sialic acid-blocking mimetic Ac53FaxNeu5Ac. Ac53FaxNeu5Ac treatment potentiated BMDC activation via toll-like receptor (TLR) stimulation without affecting differentiation and viability. Sialic acid blockade further increased the capacity of BMDCs to induce antigen-specific CD8+ T cell proliferation. Transcriptome-wide gene expression analysis revealed that sialic acid mimetic treatment of BMDCs induces differential expression of genes involved in T cell activation, cell-adhesion, and cell–cell interactions. Subsequent cell clustering assays and single cell avidity measurements demonstrated that BMDCs with reduced sialylation form higher avidity interactions with CD8+ T cells. This increased avidity was detectable in the absence of antigens, but was especially pronounced in antigen-dependent interactions. Together, our data show that sialic acid blockade in BMDCs ameliorates maturation and enhances both cognate T cell receptor–MHC-dependent and independent T cell interactions that allow for more robust CD8+ T cell responses.
A20 undermines alternative NF-κB activity and expression of anti-apoptotic genes in Helicobacter pylori infection
Authors: Lim Michelle C. C. , Maubach Gunter , Birkl-Toeglhofer Anna M. , Haybaeck Johannes , Vieth Michael , Naumann Mchael 
Published: January 2022

AbstractA hallmark of infection by the pathogen Helicobacter pylori, which colonizes the human gastric epithelium, is the simultaneous activation of the classical and alternative nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways, underlying inflammation and cell survival. Here, we report that the classical NF-κB target gene product A20 contributes to the negative regulation of alternative NF-κB signaling in gastric epithelial cells infected by H. pylori. Mechanistically, the de novo synthesized A20 protein interacts with tumor necrosis factor receptor-associated factor-interacting protein with forkhead-associated domain (TIFA) and thereby interferes with the association of TIFA with the NIK regulatory complex. We also show that alternative NF-κB activity contributes to the up-regulation of anti-apoptotic genes, such as baculoviral IAP repeat containing 2 (BIRC2), BIRC3 and B-cell lymphoma 2-related protein A1 (BCL2A1) in gastric epithelial cells. Furthermore, the observed over-expression of RelB in human gastric biopsies with type B gastritis and RelB-dependent suppression of apoptotic cell death emphasize an important role of the alternative NF-κB pathway in H. pylori infection.
DNA Methyltransferase 3 (MET3) is regulated by Polycomb group complex during Arabidopsis endosperm development
Authors: Tirot Louis , Bonnet Diane M. V. , Jullien Pauline E. 
Published: January 2022

Abstract
Complex epigenetic changes occur during plant reproduction. These regulations ensure the proper transmission of epigenetic information as well as allowing for zygotic totipotency. In Arabidopsis, the main DNA methyltransferase is called MET1 and is responsible for methylating cytosine in the CG context. The Arabidopsis genome encodes for three additional reproduction-specific homologs of MET1, namely MET2a, MET2b and MET3. In this paper, we show that the DNA methyltransferase MET3 is expressed in the seed endosperm and its expression is later restricted to the chalazal endosperm. MET3 is biallelically expressed in the endosperm but displays a paternal expression bias. We found that MET3 expression is regulated by the Polycomb complex proteins FIE and MSI1. Seed development is not impaired in met3 mutant, and we could not observe significant transcriptional changes in met3 mutant. MET3 might regulates gene expression in a Polycomb mutant background suggesting a further complexification of the interplay between H3K27me3 and DNA methylation in the seed endosperm.

Key message
The DNA METHYLTRANSFERASE MET3 is controlled by Polycomb group complex during endosperm development.
A differentially private indoor localization scheme with fusion of WiFi and bluetooth fingerprints in edge computing
Authors: Zhang Xuejun , He Fucun , Chen Qian , Jiang Xinlong , Bao Junda , Ren Tongwei , Du Xiaogang 
Published: January 2022

AbstractAs an enabling technology for edge computing scenarios, indoor localization has a broad prospect in a variety of location-based applications, such as tracking, navigating, and monitoring in indoor environments. In order to improve the location accuracy, numerous machine learning (ML)-based indoor localization schemes with fingerprint fusion have been proposed recently, which take advantage of the fusion of signal gathered from multiple wireless technologies (e.g., WiFi and BLE) and require a site survey to construct the fingerprint database. However, most solutions are based on cloud framework and thus pose a serious privacy leakage because users’ sensitive information (e.g., locations) is computed from the fingerprint database by the untrusted localization service provider. Furthermore, the site survey is time-consuming and labor-intensive. In this paper, we propose a differentially private fingerprint fusion semi-supervised extreme learning machine for indoor localization in the edge computing, called Adp-FSELM. The Adp-FSELM firstly employs a multi-level edge network-based privacy-preserving system framework to meet the requirements of ML-based fingerprint indoor localization for lightweight, low latency, and real-time response. Then, the Adp-FSELM extends the $$\varepsilon$$
ε
-differential privacy to the fingerprint fusion semi-supervised extreme learning machine for indoor localization in edge computing through a three-phase private process consisting of private labeled sample obfuscation, differentially private feature fusion, and differentially private model training. Theoretical and comprehensive experimental results in real indoor environments demonstrate that the Adp-FSELM provides a high $$\varepsilon$$
ε
-differential privacy guarantee for users’ location privacy while reducing human calibration effort and effectively resists Bayesian inference attacks. Compared with the existing semi-supervised learning-based localization methods, the mean absolute error of location accuracy of the Adp-FSELM is restricted to 2.22% at most, and the additional time consumption can be almost ignored. Thus, our mechanism can balance the trade-off among location privacy, location accuracy, and time consumption.
Modeling the oxidation of a polymer-derived ceramic with chemo-mechanical coupling and large deformations
Authors: Voges Jannik , Smokovych Iryna , Duvigneau Fabian , Scheffler Michael , Juhre Daniel 
Published: January 2022

AbstractTo get a better insight into the coating behavior of a polymer-derived ceramic material, we model and simulate the diffusion, oxidation and reaction-induced volume expansion of a specimen without outer mechanical loads. In this macroscale approach, we use an oxidation state variable which determines the composition of the starting material and the oxide material. The model contains a reaction rate which is based on the change of the free energy due to a change of the concentrations of the starting material, the oxide material and a diffusing gaseous material. Using this, we model a growing oxide layer in a perhydropolysilazane (PHPS)-based polymer-derived ceramic (PDC), containing silicon filler particles. Within the mechanical part of the modeling, we use the Neo-Hookean material law which allows for the consideration of volume expansion and the diffusion kinematics in terms of finite deformations. We derive this continuum formulation in 3D and reduce it later to 1D, as we show that a 1D formulation is sufficient for thin oxide layers in our consideration. In such a case, the reaction-induced volume expansion is mostly limited to strains orthogonal to the oxide layer, as the bulk material hinders transversal deformation. Both formulations, i.e., 1D and 3D, are implemented in the finite element software FEAP. We perform a parameter study and fit the results with experimental data. We investigate the diffusion kinematics in the presence of volume expansion. Additionally, we discuss the influence of the elastic energy on the reaction rate.
Nanoparticle albumin-bound paclitaxel and ramucirumab versus paclitaxel and ramucirumab as second-line chemotherapy for unresectable advanced or recurrent gastric cancer: a multicenter, propensity score-matched analysis (CROSS SELL study)
Authors: Nakasya Akio , Hagiwara Yuya , Ikoma Tatsuki , Kurioka Yusuke , Matsumoto Toshihiko , Yamamoto Yoshiyuki , Tsuduki Takao , Kajiwara Takeshi , Moriwaki Toshikazu , Nishina Tomohiro , Yamashita Natsumi , Hyodo Ichinosuke 
Published: January 2022

Abstract
Background
Paclitaxel plus ramucirumab (PTX + RAM) is the standard second-line chemotherapy for unresectable advanced or recurrent gastric cancer (AGC). Nanoparticle albumin-bound paclitaxel (nab-PTX) is an improved, more convenient form of PTX and is non-inferior to PTX. Although some retrospective and single-arm phase II studies regarding nab-PTX + RAM have been reported, comparative studies are lacking. Here, we compared the efficacy and toxicity of nab-PTX + RAM and PTX + RAM using propensity score matching.

Methods
Clinical data of 265 patients treated for AGC with nab-PTX + RAM or PTX + RAM were retrospectively collected. Nab-PTX was administered at dosages of 100 mg/m2, replacing PTX in the standard PTX + RAM regimen. Progression-free survival (PFS), overall survival (OS), and toxicity were compared using 1:1 propensity score matching.

Results
In total, 190 (72%) patients were matched. The median PFS was 5.3 [95% confidence interval (CI) 4.4–6.3] and 4.7 (95% CI 3.2–5.3) months in the nab-PTX + RAM and PTX + RAM groups, respectively [hazard ratio (HR) = 0.76, 95% CI 0.56–1.03, p = 0.07]. The median OS was 11.5 (95% CI 9.2–15.0) and 9.9 (95% CI 8.0–12.7) months, respectively (HR = 0.78, 95% CI 0.56–1.07, p = 0.12). Grade 3 and 4 neutropenia was observed more frequently in the nab-PTX + RAM group (72% vs. 56%, p = 0.03). No treatment-related deaths occurred.

Conclusions
Nab-PTX + RAM exhibited more favorable trends in terms of PFS and OS but was more myelosuppressive than PTX + RAM. As neutropenia is commonly manageable toxicity, nab-PTX + RAM presents a treatment alternative for AGC. Further studies including randomized, controlled studies are warranted.
Evaluation of a 2D UNet-Based Attenuation Correction Methodology for PET/MR Brain Studies
Authors: Presotto Luca , Bettinardi Valentino , Bagnalasta Matteo , Scifo Paola , Savi Annarita , Vanoli Emilia Giovanna , Fallanca Federico , Picchio Maria , Perani Daniela , Gianolli Luigi , De Bernardi Elisabetta 
Published: January 2022

AbstractDeep learning (DL) strategies applied to magnetic resonance (MR) images in positron emission tomography (PET)/MR can provide synthetic attenuation correction (AC) maps, and consequently PET images, more accurate than segmentation or atlas-registration strategies. As first objective, we aim to investigate the best MR image to be used and the best point of the AC pipeline to insert the synthetic map in. Sixteen patients underwent a 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) and a PET/MR brain study in the same day. PET/CT images were reconstructed with attenuation maps obtained: (1) from CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with a 2D UNet trained on MR image/attenuation map pairs. As for MR, T1-weighted and Zero Time Echo (ZTE) images were considered; as for attenuation maps, CTs and 511 keV low-resolution attenuation maps were assessed. As second objective, we assessed the ability of DL strategies to provide proper AC maps in presence of cranial anatomy alterations due to surgery. Three 11C-methionine (METH) PET/MR studies were considered. PET images were reconstructed with attenuation maps obtained: (1) from diagnostic coregistered CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with 2D UNets trained on the sixteen FDG anatomically normal patients. Only UNets taking ZTE images in input were considered. FDG and METH PET images were quantitatively evaluated. As for anatomically normal FDG patients, UNet AC models generally provide an uptake estimate with lower bias than atlas-based or segmentation-based methods. The intersubject average bias on images corrected with UNet AC maps is always smaller than 1.5%, except for AC maps generated on too coarse grids. The intersubject bias variability is the lowest (always lower than 2%) for UNet AC maps coming from ZTE images, larger for other methods. UNet models working on MR ZTE images and generating synthetic CT or 511 keV low-resolution attenuation maps therefore provide the best results in terms of both accuracy and variability. As for METH anatomically altered patients, DL properly reconstructs anatomical alterations. Quantitative results on PET images confirm those found on anatomically normal FDG patients.
Blockade of Myd88 signaling by a novel MyD88 inhibitor prevents colitis-associated colorectal cancer development by impairing myeloid-derived suppressor cells
Authors: Wang Lu , Hu Dan , Xie Bin , Xie Lin 
Published: January 2022

SummaryBackground. In cancer, myeloid-derived suppressor cells (MDSCs) are known to escape the host immune system by developing a highly suppressive environment. However, little is known about the molecular mechanism behind MDSC-mediated tumor cell evasion of the immune system. Toll-like receptor (TLR) signaling elicited in the tumor microenvironment has the potential to induce MDSC differentiations in different organs. Therefore, MDSC elimination by blocking the action of myeloid differentiation factor 88 (MyD88), which is a key adaptor-signaling molecule that affects TLR activity, seems to be an ideal tumor immunotherapy. Previous studies have proven that blocking MyD88 signaling with a novel MyD88 inhibitor (TJ-M2010-5, synthesized by Zhou’s group) completely prevented colitis-associated colorectal cancer (CAC) development in mice. Methods. In the present study, we investigated the impact of the novel MyD88 inhibitor on the number, phenotype, and function of MDSC in the mice model of CAC. Results. We showed that CAC growth inhibition was involved in diminished MDSC generation, expansion, and suppressive function and that MDSC-mediated immune escape was dependent on MyD88 signaling pathway activation. MyD88 inhibitor treatment decreased the accumulation of CD11b+Gr1+ MDSCs in mice with CAC, thereby reducing cytokine (GM-CSF, G-CSF, IL-1β, IL-6 and TGF-β) secretion associated with MDSC accumulation, and reducing the expression of molecules (iNOS, Arg-1 and IDO) associated with the suppressive capacity of MDSCs. In addition, MyD88 inhibitor treatment reduced the differentiation of MDSCs from myeloid cells and the suppressive capacity of MDSCs on the proliferation of activated CD4+ T cells in vitro. Conclusion. MDSCs are primary cellular targets of a novel MyD88 inhibitor during CAC development. Our findings prove that MyD88 signaling is involved in the regulation of the immunosuppressive functions of MDSCs. The novel MyD88 inhibitor TJ-M2010-5 is a new and effective agent that modulates MyD88 signaling to overcome MDSC suppressive functions, enabling the development of successful antitumor immunotherapy.
Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education
Authors: Kim Jinhee , Lee Hyunkyung , Cho Young Hoan 
Published: January 2022

AbstractPreparing students to collaborate with AI remains a challenging goal. As AI technologies are new to K-12 schools, there is a lack of studies that inform how to design learning when AI is introduced as a collaborative learning agent to classrooms. The present study, therefore, aimed to explore teachers’ perspectives on what (1) curriculum design, (2) student-AI interaction, and (3) learning environments are required to design student-AI collaboration (SAC) in learning and (4) how SAC would evolve. Through in-depth interviews with 10 Korean leading teachers in AI in Education (AIED), the study found that teachers perceived capacity and subject-matter knowledge building as the optimal learning goals for SAC. SAC can be facilitated through interdisciplinary learning, authentic problem solving, and creative tasks in tandem with process-oriented assessment and collaboration performance assessment. While teachers expressed instruction on AI principles, data literacy, error analysis, AI ethics, and AI experiences in daily life were crucial support, AI needs to offer an instructional scaffolding and possess attributes as a learning mate to enhance student-AI interaction. In addition, teachers highlighted systematic AIED policy, flexible school system, the culture of collaborative learning, and a safe to fail environment are significant. Teachers further anticipated students would develop collaboration with AI through three stages: (1) learn about AI, (2) learn from AI, and (3) learn together. These findings can provide a more holistic understanding of the AIED and implications for the educational policies, educational AI design as well as instructional design that are aimed at enhancing SAC in learning.
Compressions of kth-order slant Toeplitz operators to model spaces
Authors: Łanucha Bartosz , Michalska Małgorzata 
Published: January 2022

AbstractIn this paper, we consider compressions of kth-order slant Toeplitz operators to the backward shift-invariant subspaces of the classical Hardy space H2. In particular, we characterize these operators using compressed shifts and finite-rank operators of special kind.
Quantum illumination with three-mode Gaussian state
Authors: Jung Eylee , Park DaeKil 
Published: January 2022

AbstractThe quantum illumination is examined by making use of the three-mode maximally entangled Gaussian state, which involves one signal and two idler beams. It is shown that the quantum Bhattacharyya bound between $$\rho $$
ρ
(state for target absence) and $$\sigma $$
σ
(state for target presence) is less than the previous result derived by two-mode Gaussian state when $$N_S$$

N
S

, average photon number per signal, is less than 0.295. This indicates that the quantum illumination with three-mode Gaussian state gives less error probability compared to that with two-mode Gaussian state when $$N_S < 0.295$$

N
S

<
0.295

.