bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting relative efficiency of amide bond formation using multivariate linear regression
Authors: Haas Brittany C. , Goetz Adam E. , Bahamonde Ana , McWilliams J. Christopher , Sigman Matthew S. 
Published: April 2022

Significance
Given the ubiquity of amide coupling reactions, understanding the factors which influence the success of the reaction and having means to predict the reaction rate would streamline synthetic efforts. This study outlines a data science–based workflow for effective statistical modeling with sparse experimental data. We demonstrated informed substrate selection, collection of rate data and interpretable molecular descriptors, and statistical model development for amide coupling rates. The resulting statistical models illuminate substrate features that impact rate and allow for the prediction of untested amide coupling rates.
Metabolic reprogramming of tumor-associated macrophages by collagen turnover promotes fibrosis in pancreatic cancer
Authors: LaRue Madeleine M. , Parker Seth , Puccini Joseph , Cammer Michael , Kimmelman Alec C. , Bar-Sagi Dafna 
Published: April 2022

Significance
The highly desmoplastic and immunosuppressive microenvironment of pancreatic tumors is a major determinant of the aggressive nature and therapeutic resistance of pancreatic cancer. Therefore, improving our understanding of the mechanisms that regulate the composition and function of the pancreatic tumor microenvironment is critical for the design of intervention strategies for this devastating malignancy. This study identifies a modality for the reprogramming of tumor-associated macrophages involving collagen scavenging followed by a metabolic switch toward a profibrotic paracrine phenotype. These findings establish a molecular framework for the elucidation of regulatory processes that could be harnessed to mitigate the stroma-dependent protumorigenic effects in pancreatic cancer.
The ghost of Vulgar Latin
Authors: Versteegh Kees 
Published: April 2022

SummaryThe concept of a colloquial variety of Latin as an intermediate variety between Latin and the Romance languages has a long standing. Sometimes calledVulgarorPopular Latin, this variety is often conceptualized as a discrete linguistic variety, which is held responsible for the changes in the provincial realization of Latin. Since a great deal of evidence for this variety is collected from written texts, studies on the emergence of the Romance languages have tended to ignore the actual process of language acquisition in the provinces of the Roman empire. In the present paper I draw attention to the work of two early scholars, the Italian Celso Cittadini (1533–1627) and the Frenchman Pierre-Nicolas Bonamy (1694–1770), who did concern themselves with the acquisition of Latin, referring to the role of the Roman army in spreading the Latin language throughout the empire. Their suggestions about the process of Latinization can be substantiated with data on the military presence in the provinces of the Roman empire.
Psycholinguistic errors in signed simultaneous interpreting
Authors: Wehrmeyer Ella 
Published: April 2022

AbstractIn this article, errors and repairs in a corpus of English news broadcasts interpreted simultaneously into South African Sign Language are explored from a psycholinguistic perspective according toLevelt’s (1989)cognitive levels (comprehension, conceptualisation, formulation, morphological encoding and articulation). Breaking away from traditional perspectives, the study offers a novel approach to empirical research into sign(ed) language interpreting, with applications relevant to spoken-language interpreting. Most slips involved lemma selection, followed by slips in articulation and conceptualisation (syntactic planning). Significantly fewer errors in comprehension compared to production indicate that professional interpreters have excellent listening skills, although reconceptualising is sometimes problematic. The interpreters mainly repaired incorrect lemma selection and reception errors that resulted in mistranslations, suggesting the existence of a true/false error-detection mechanism, with little attention being paid to other forms of error, possibly owing to time and cognitive pressures. Errors do not increase over time, which suggests cognitive overload rather than fatigue as their cause.
On the status of information structure markers
Authors: Däbritz Chris Lasse 
Published: April 2022

AbstractThe paper at hand deals with morphological marking of information structural relations from the perspective of North-Western Siberian languages. Given many items (morphemes as well as particles and clitics) which have been analyzed as markers of information structure in these languages, I try to discuss whether they indeed mark information structural relations or whether this supposed marking is rather a side effect of other functions expressed. In order to develop criteria for decision marking, I rely on the concepts of sufficiency as well as necessity and sufficient as well as necessary conditions, respectively. Additionally, I argue that the latter can be arranged hierarchically with respect to their reliability for the evaluation of potential markers of information structure, being intertwined with functional and transparency coding principles.
Design and analysis of a wideband and wide angle 3D metamaterial absorber
Authors: Wang Wenjie , Wang Aixia , Liang Jiangang , Wang Zhenxu , Jiang Jinming , Xu Cuilian , Li Yongfeng , Wang Jiafu , Qu Shaobo 
Published: April 2022

Abstract
In this paper, we proposed a three-dimensional (3D) metamaterial absorber joint by lightweight 3D grid structure and traditional magnetic materials, which can achieve wideband and wide-angle perfect absorption at 5–20 GHz. By simulation, the broadband absorption remained almost 90% from 0° to 80° for TM wave. The surface current and power loss distributions were investigated to interpret the physical mechanism of wideband and wide-angle absorption. The broadband and wide-angle absorption were derived from magnetic and electric resonances between the top resistive film, background plane and magnetic loss of magnetic materials. The results proved that different layers of the proposed absorber play different loss roles, and finally contributed to the wideband and wide-angle absorption. The polarization insensitive stability of the proposed absorber was also demonstrated at different polarized angles. The present study provided a new design to achieve a polarization insensitive, wideband and wide-angle absorber. Moreover, the structure absorber has potential applications in other fields, including the solar cell, imaging and detection etc.
Preparation and photoelectric characterization of p-GeSe/p-WS2 heterojunction devices
Authors: Yan Bing , Zhang Guoxin , Ning Bo , Chen Sikai , Zhao Yang , Zhou Dahua , Shi Xuan , Shen Jun , Xiao Zeyun , Zhao Hongquan 
Published: April 2022

Abstract
The construction of van der Waals (vdW) heterojunctions has attracted widespread attention for various strategies in the optoelectronic field due to their band structural advantages. Herein, novel p–p heterojunctions based on p-GeSe and p-WS2 flakes are fabricated on 300 nm-SiO2/Si substrates by means of mechanical exfoliation and micro-area fixed-point transfer of the GeSe flakes onto the WS2 flakes. The thickness and quality of the materials are determined by atomic force microscope and Raman spectroscopy. Considerable photoelectric characteristics are exhibited by exploring the performance of the heterojunctions under a 635 nm laser illumination. The photoresponsivity (

R
λ

), specific detectivity (

D

*

), and external quantum efficiency (

EQE

) of the heterojunctions are measured to be 195.70 mA W−1, 2.879 × 107 Jones, and 38.28%, respectively. The results indicate the strong potential of the p–p type heterojunctions composed of GeSe and WS2 flakes in photoelectric devices, and our work provides parameters and technical support for the development of vdW heterojunction devices.
Analysis of flexochemical effect and its application in scanning probe microscopy
Authors: Zhang Gongxi , Deng Feng , Liu Wenyuan , Shen Shengping 
Published: April 2022

Abstract
Electrochemical processes in solids are affected by the properties of various interfaces, where the flexoelectric effect manifests itself considerably due to the inevitable strong gradient fields. Thus, it is crucial to study the coupling between the electrochemical process and the flexoelectric effect. Based on the continuum theory, we conducted the finite element implementation for the flexochemical effect, being the coupling between flexoelectricity, Vegard effect and chemical reactions. Then, the developed method is employed to investigate the flexochemical effect arising in scanning probe microscopy (SPM), including evaluating the contributions from the flexoelectric effect and Vegard effect to the electromechanical response on material SrTiO3 (STO) in piezoresponse force microscopy (PFM) as well as to mechanical redistribution of oxygen vacancy in STO. It is found that at room temperature the nanoscale electromechanical response of the undoped STO in PFM imaging is mainly induced by the converse flexoelectricity while the contribution of direct Vegard effect is negligible. Furthermore, the contact force exerted by SPM tip in manipulating the redistribution of oxygen vacancies is multifunctional, including diminishing vacancies underneath the contact area and enriching the regions around the tip-surface contact edge and inside the sample below the tip, resulting from the synergy of the converse Vegard effect and the direct flexoelectricity. These analyses explain some experimental observations well. This paper provides a continuum framework for the analysis of electrochemomechanical systems with the flexoelectric effect.
Radiative decay of an emitter due to non-Markovian interactions with dissipating matter
Authors: Jain Kritika , Venkatapathi Murugesan 
Published: April 2022

Abstract
It is known that the more tractable Markovian models of coupling suited for weak interactions may overestimate the Rabi frequency notably when applied to the strong-coupling regime. Here, a more significant consequence of the non-Markovian interaction between a photon emitter and dissipating matter such as resonant plasmonic nanoparticles is described. A large increase of radiative decay and a diminished non-radiative loss is shown, which unravels the origin of unexpected large enhancements of surface-enhanced-Raman-spectroscopy, as well as the anomalous enhancements of emission due to extremely small fully absorbing metal nanoparticles less than 10 nm in dimensions. We construct the mixture of pure states of the coupled emitter-nanoparticle system, unlike conventional methods that rely on the orthogonal modes of the nanoparticle alone.
Summary of the 2021 ICRP workshop on the future of radiological protection
Authors: Rühm W , Clement C , Cool D , Laurier D , Bochud F , Applegate K , Schneider T , Bouffler S , Cho K , Hirth G , Kai M , Liu S , Romanov S , Wojcik A 
Published: April 2022

Abstract
The International Commission on Radiological Protection (ICRP) has embarked on a process to review and revise the current System of Radiological Protection (‘the System’). To stimulate discussion, the ICRP published two open-access articles: one on aspects of the System that might require review, and another on research that might improve the scientific foundation of the System. Building on these articles, the ICRP organized a Workshop on the Future of Radiological Protection as an opportunity to engage in the review and revision of the System. This digital workshop took place from 14 October–3 November 2021 and included 20 live-streamed and 43 on-demand presentations. Approximately 1500 individuals from 100 countries participated. Based on the subjects covered by the presentations, this summary is organized into four broad areas: the scientific basis, concepts and application of the System; and the role of the ICRP. Some of the key topics that emerged included the following: classification of radiation-induced effects; adverse outcome pathway methodologies; better understanding of the dose–response relationship; holistic and reasonable approaches to optimization of protection; radiological protection of the environment; ethical basis of the System; clarity, consistency and communication of the System; application of the System in medicine and application of the principles of justification and optimization of protection.
Adaptive singular value decomposition for bearing fault diagnosis under strong noise interference
Authors: Cui Lingli , Liu Yinhang , Zhao Dezun 
Published: April 2022

Abstract
Singular value decomposition (SVD) is an effective tool for analyzing the signals from mechanical systems and for fault diagnosis, which is a non-parametric signal analysis method free from phase shift and waveform distortion. In SVD, the embedding dimension of the Hankel matrix is an important parameter that directly influences the effectiveness of the SVD. However, the embedding dimension is usually determined by experience, which is quite subjective and limits the applicability of SVD. As such, a novel SVD method, named adaptive SVD (ASVD), is proposed in this paper. In ASVD, novel criteria are defined to obtain the specific embedding dimensions for different mechanical signals by means of numerical simulation. A novel phenomenon, that the singular value pairs change periodically with the step size of half-cycle sampling points, is found and it can be used to calculate specific embedding dimension instead of selecting it from a range using experience. Meanwhile, the envelope spectral amplitude ratio index is developed for addressing the issue of excessive decomposition in classic SVD. Lastly, an ASVD-based bearing fault diagnosis method is proposed to adaptively select useful sub-signals and to detect faults. Both simulated signal and experiment signals, collected from different bearing test rigs are used to verify the effectiveness of the proposed method. The results show that the proposed method has a satisfactory ability to eliminate interference noise and detect bearing fault.
Large-area flexible MWCNT/PDMS pressure sensor for ergonomic design with aid of deep learning
Authors: Zhong Hongchuan , Fu Rongda , Chen Shiqi , Zhou Zaiwei , Zhang Yue , Yin Xiangyu , He Bingwei 
Published: April 2022

Abstract
The achievement of well-performing pressure sensors with low pressure detection, high sensitivity, large-scale integration, and effective analysis of the subsequent data remains a major challenge in the development of flexible piezoresistive sensors. In this study, a simple and extendable sensor preparation strategy was proposed to fabricate flexible sensors on the basis of multiwalled carbon nanotube/polydimethylsiloxane (MWCNT/PDMS) composites. A dispersant of tetrahydrofuran (THF) was added to solve the agglomeration of MWCNTs in PDMS, and the resistance of the obtained MWCNT/PDMS conductive unit with 7.5 wt.% MWCNTs were as low as 180 Ω/hemisphere. Sensitivity (0.004 kPa−1), excellent response stability, fast response time (36 ms), and excellent electromechanical properties were demonstrated within the pressure range from 0 to 100 kPa. A large-area flexible sensor with 8 × 10 pixels was successfully adopted to detect the pressure distribution on the human back and to verify its applicability. Combining the sensor array with deep learning, inclination of human sitting was easily recognized with high accuracy, indicating that the combined technology can be used to guide ergonomic design.
Electromagnetic forces in nanoparticles made of multilayer hyperbolic metamaterials
Authors: Zhu Sheng-Qing , Zhang Yi 
Published: April 2022

Abstract
We theoretically study the electromagnetic forces (optical gradient force, optical torque and vacuum friction) acting on a spherical anisotropic nanoparticle, which can be characterized by multilayer hyperbolic metamaterials (mHMMs). We find three important results about these forces: (i) Firstly, we theoretically demonstrate that the optical gradient force produced on a mHMMs nanoparticle can be flexibly tuned, from pushing the particle to pulling it, just via changing incident angle of illuminating plane light wave. (ii) Secondly, we find the optical torque acting on the mHMMs nanoparticle (its filling factor is around 0.3) can be tuned between positive and negative via changing the incident angle of circularly polarized plane light. Therefore, the rotating mHMMs nanoparticle with designed filling factor can be accelerated or decelerated by the optical torque. (iii) Finally, due to the large fluctuations of dipole polarizability of mHMMs nanoparticle with appropriate filling factor, we propose a new method to obtain the large enhancement of vacuum friction torque by designing the filling factor of the rotating mHMMs nanoparticle.
Heavy-water-based moderator design for an AB-BNCT unit using a topology optimization algorithm
Authors: Chabod Sébastien , Giraud Julien , Hervé Marine , Santos Daniel , Sauzet Nadine 
Published: April 2022

Abstract

Objective. The design of neutron moderators for BNCT treatment units currently relies on parametric approaches, which yield quality results but are ultimately limited by human imagination. Efficient but non-intuitive design solutions may thus be missed out. This limitation needs to be addressed. Approach. To overcome this limitation, we propose to use a topology optimization algorithm coupled with a state-of-the-art Monte-Carlo transport code. This approach recently proved capable of finding complex optimal configurations of particle propagators with limited human intervention. Main results. In this study, we apply this algorithmic solution to optimize some heavy-water neutron moderators for a specific AB-BNCT treatment unit. The moderators thus generated are compact yet succeed in limiting the exposure of patient’s healthy tissues to levels below recommended limits. They present subtle, original geometries inaccessible to standard parametric approaches or human intuition. Significance. This approach could be used to automatically fit the design of a BNCT moderator to the location and shape of the tumor or to the morphology of the patient to be treated, opening a path for more targeted BNCT treatment.
Endoscopy image enhancement method by generalized imaging defect models based adversarial training
Authors: Li Wenjie , Fan Jingfan , Li Yating , Hao Pengcheng , Lin Yucong , Fu Tianyu , Ai Danni , Song Hong , Yang Jian 
Published: April 2022

Abstract

Objective. Smoke, uneven lighting, and color deviation are common issues in endoscopic surgery, which have increased the risk of surgery and even lead to failure. Approach. In this study, we present a new physics model driven semi-supervised learning framework for high-quality pixel-wise endoscopic image enhancement, which is generalizable for smoke removal, light adjustment, and color correction. To improve the authenticity of the generated images, and thereby improve the network performance, we integrated specific physical imaging defect models with the CycleGAN framework. No ground-truth data in pairs are required. In addition, we propose a transfer learning framework to address the data scarcity in several endoscope enhancement tasks and improve the network performance. Main results. Qualitative and quantitative studies reveal that the proposed network outperforms the state-of-the-art image enhancement methods. In particular, the proposed method performs much better than the original CycleGAN, for example, the structural similarity improved from 0.7925 to 0.8648, feature similarity for color images from 0.8917 to 0.9283, and quaternion structural similarity from 0.8097 to 0.8800 in the smoke removal task. Experimental results of the proposed transfer learning method also reveal its superior performance when trained with small datasets of target tasks. Significance. Experimental results on endoscopic images prove the effectiveness of the proposed network in smoke removal, light adjustment, and color correction, showing excellent clinical usefulness.
Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning
Authors: Scholey Jessica , Vinas Luciano , Kearney Vasant , Yom Sue , Larson Peder Eric Zufall , Descovich Martina , Sudhyadhom Atchar 
Published: April 2022

Abstract

Objective. Kilovoltage computed tomography (kVCT) is the cornerstone of radiotherapy treatment planning for delineating tissues and towards dose calculation. For the former, kVCT provides excellent contrast and signal-to-noise ratio. For the latter, kVCT may have greater uncertainty in determining relative electron density (

ρ

e

) and proton stopping power ratio (SPR). Conversely, megavoltage CT (MVCT) may result in superior dose calculation accuracy. The purpose of this work was to convert kVCT HU to MVCT HU using deep learning to obtain higher accuracy

ρ

e

and SPR. Approach. Tissue-mimicking phantoms were created to compare kVCT- and MVCT-determined

ρ

e

and SPR to physical measurements. Using 100 head-and-neck datasets, an unpaired deep learning model was trained to learn the relationship between kVCTs and MVCTs, creating synthetic MVCTs (sMVCTs). Similarity metrics were calculated between kVCTs, sMVCTs, and MVCTs in 20 test datasets. An anthropomorphic head phantom containing bone-mimicking material with known composition was scanned to provide an independent determination of

ρ

e

and SPR accuracy by sMVCT. Main results. In tissue-mimicking bone,

ρ

e

errors were 2.20% versus 0.19% and SPR errors were 4.38% versus 0.22%, for kVCT versus MVCT, respectively. Compared to MVCT, in vivo mean difference (MD) values were 11 and 327 HU for kVCT and 2 and 3 HU for sMVCT in soft tissue and bone, respectively.

ρ

e

MD decreased from 1.3% to 0.35% in soft tissue and 2.9% to 0.13% in bone, for kVCT and sMVCT, respectively. SPR MD decreased from 1.8% to 0.24% in soft tissue and 6.8% to 0.16% in bone, for kVCT and sMVCT, respectively. Relative to physical measurements,

ρ

e

and SPR error in anthropomorphic bone decreased from 7.50% and 7.48% for kVCT to <1% for both MVCT and sMVCT. Significance. Deep learning can be used to map kVCT to sMVCT, suggesting higher accuracy

ρ

e

and SPR is achievable with sMVCT versus kVCT.
Machine learning for continuous quantum error correction on superconducting qubits
Authors: Convy Ian , Liao Haoran , Zhang Song , Patel Sahil , Livingston William P , Nguyen Ho Nam , Siddiqi Irfan , Whaley K Birgitta 
Published: April 2022

Abstract
Continuous quantum error correction has been found to have certain advantages over discrete quantum error correction, such as a reduction in hardware resources and the elimination of error mechanisms introduced by having entangling gates and ancilla qubits. We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identify bit-flip errors from continuous noisy syndrome measurements. The algorithm is designed to operate on measurement signals deviating from the ideal behavior in which the mean value corresponds to a code syndrome value and the measurement has white noise. We analyze continuous measurements taken from a superconducting architecture using three transmon qubits to identify three significant practical examples of non-ideal behavior, namely auto-correlation at temporal short lags, transient syndrome dynamics after each bit-flip, and drift in the steady-state syndrome values over the course of many experiments. Based on these real-world imperfections, we generate synthetic measurement signals from which to train the recurrent neural network, and then test its proficiency when implementing active error correction, comparing this with a traditional double threshold scheme and a discrete Bayesian classifier. The results show that our machine learning protocol is able to outperform the double threshold protocol across all tests, achieving a final state fidelity comparable to the discrete Bayesian classifier.