bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visual question answering with gated relation‐aware auxiliary
Authors: Shao Xiangjun , Xiang Zhenglong , Li Yuanxiang 
Published: January 2022

AbstractThe great advances in computer vision and natural language processing make significant progress in visual question answering. In the visual question answering task, the visual representation is essential for understanding the image content. However, traditional methods rarely exploit the context information of the visual feature related to the question and the relation‐aware information to capture valuable visual representation. Therefore, a gated relation‐aware model is proposed to capture the enhanced visual representation for desiring answer prediction. The gated relation‐aware module can learn relation‐aware information between the visual feature and the context, and a certain object of an image, respectively. In addition, the proposed module can filter out the unnecessary relation‐aware information through the gate guided by the question semantic representation. The results of the conducted experiments show that the gated relation‐aware module makes a significant improvement on all answer categories.
Multi‐label hybrid radar signal recognition based on a feature pyramid network and class activation mapping
Authors: Si Weijian , Luo Jiaji , Deng Zhian 
Published: January 2022

AbstractThe electromagnetic environment of modern battlefields becomes increasingly complex, and radar receivers may receive multiple radar signals simultaneously. However, current deep learning models can only predict a single class and cannot recognize multi‐label mixed radar signals. In this study, a multi‐label hybrid radar signal recognition framework based on the feature pyramid network (FPN) and class activation map (CAM) is proposed. The multi‐label radar signals are recognized by calculating the average value of the CAM corresponding to each class. The proposed method can recognize, localize and separate mixed radar signals in time‐frequency images, which improves the interpretability and transparency of the model. In addition, the FPN is adopted to improve the spatial resolution of the feature maps, and the Mixup data augmentation is utilized to improve the generalization performance of the model. Experiments with eight different modulation types of mixed radar signals show that the recognition accuracy of hybrid radar signals achieves 92.2% at 0 dB.
Adherence to Definitions of Labor Arrest Influence on Primary Cesarean Delivery Rate
Authors: Greenberg Jessica T. , Cross Sarah N. , Raab Cheryl A. , Pettker Christian M. , Illuzzi Jessica L. 
Published: January 2022

Objective The cesarean delivery rate in the United States is 31.9%. One of the leading indications for primary cesarean delivery is labor arrest. A modern understanding of the labor curve supports more time prior to the diagnosis of labor arrest. We conducted this study to examine the impact of adherence to the modern criteria for labor arrest and failed induction on rates of primary cesarean delivery and to identify predictors of meeting these criteria.
Study Design We analyzed rates of primary cesarean deliveries overall and primary cesarean deliveries occurring due to arrest of dilation, arrest of descent, and failed induction among the 17,877 live births at a large academic center from 2010 through 2013. Multiple logistic regression modeling identified predictors of meeting the new criteria for these indications based on guidelines published by the 2012 National Institute of Child Health and Human Development.
Results The primary cesarean delivery rate decreased from 23.5 to 21.1% (p = 0.026) from 2010 to 2013. Primary cesarean delivery rate for labor arrest and failed induction decreased from 8.5 to 6.7% (p = 0.005). The percentage of primary cesarean deliveries meeting the 2012 criteria for labor arrest increased from 18.8 to 34.9% (p = 0.002), and the rate of primary cesarean deliveries due to arrest of dilation decreased from 5.1 to 3.4% (p < 0.0005). The percentage of cases meeting the 2012 criteria for arrest of descent increased from 57.8 to 71.0% (p < 0.007), while primary cesarean delivery rate due to arrest of descent remained relatively unchanged, 3.1 to 2.6% (p = 0.330).
Conclusion A decrease in the primary cesarean rate was attributable to a decrease in cesarean for arrest of dilation in the setting of a significant increase in meeting the 2012 criteria for arrest of dilation. At the end of the study period, 65.2% of cesareans still did not meet the criteria for arrest of dilation. Greater rates of adherence to these guidelines may yield further reductions in the cesarean rate.
Key Points
Principles for Designing and Developing a Workflow Monitoring Tool to Enable and Enhance Clinical Workflow Automation
Authors: Wu Danny T.Y. , Barrick Lindsey , Ozkaynak Mustafa , Blondon Katherine , Zheng Kai 
Published: January 2022

Abstract
Background Automation of health care workflows has recently become a priority. This can be enabled and enhanced by a workflow monitoring tool (WMOT).
Objectives We shared our experience in clinical workflow analysis via three cases studies in health care and summarized principles to design and develop such a WMOT.
Methods The case studies were conducted in different clinical settings with distinct goals. Each study used at least two types of workflow data to create a more comprehensive picture of work processes and identify bottlenecks, as well as quantify them. The case studies were synthesized using a data science process model with focuses on data input, analysis methods, and findings.
Results Three case studies were presented and synthesized to generate a system structure of a WMOT. When developing a WMOT, one needs to consider the following four aspects: (1) goal orientation, (2) comprehensive and resilient data collection, (3) integrated and extensible analysis, and (4) domain experts.
Discussion We encourage researchers to investigate the design and implementation of WMOTs and use the tools to create best practices to enable workflow automation and improve workflow efficiency and care quality.
PCaGuard: A Software Platform to Support Optimal Management of Prostate Cancer
Authors: Tamposis Ioannis , Tsougos Ioannis , Karatzas Anastasios , Vassiou Katerina , Vlychou Marianna , Tzortzis Vasileios 
Published: January 2022

Abstract
Background and Objective Prostate cancer (PCa) is a severe public health issue and the most common cancer worldwide in men. Early diagnosis can lead to early treatment and long-term survival. The addition of the multiparametric magnetic resonance imaging in combination with ultrasound (mpMRI-U/S fusion) biopsy to the existing diagnostic tools improved prostate cancer detection. Use of both tools gradually increases in every day urological practice. Furthermore, advances in the area of information technology and artificial intelligence have led to the development of software platforms able to support clinical diagnosis and decision-making using patient data from personalized medicine.
Methods We investigated the current aspects of implementation, architecture, and design of a health care information system able to handle and store a large number of clinical examination data along with medical images, and produce a risk calculator in a seamless and secure manner complying with data security/accuracy and personal data protection directives and standards simultaneously. Furthermore, we took into account interoperability support and connectivity to legacy and other information management systems. The platform was implemented using open source, modern frameworks, and development tools.
Results The application showed that software platforms supporting patient follow-up monitoring can be effective, productive, and of extreme value, while at the same time, aiding toward the betterment medicine clinical workflows. Furthermore, it removes access barriers and restrictions to specialized care, especially for rural areas, providing the exchange of medical images and patient data, among hospitals and physicians.
Conclusion This platform handles data to estimate the risk of prostate cancer detection using current state-of-the-art in eHealth systems and services while fusing emerging multidisciplinary and intersectoral approaches. This work offers the research community an open architecture framework that encourages the broader adoption of more robust and comprehensive systems in standard clinical practice.
Transcendence, fast and slow: Infinite Jest and the dynamics of a cultural splash
Authors: Medvetz Thomas 
Published: January 2022

AbstractThis paper builds on two leading models of artistic practice, the “network-building” and “autonomous sphere” approaches, to show how an expressive work can reverse the normal antinomy between artistic recognition and commercial success and become an immediate crossover hit. Focusing on a single “pointy” case from the world of literature—the 1996 novelInfinite Jest, by David Foster Wallace—I ask whether a set of unique social dynamics attends the process of making a “cultural splash.” In the case ofInfinite Jest, success came from occupying an intermediate position in the “space between fields” and eliciting a complex, mutually referential response from cultural intermediaries. In this way, the book attracted samplings of recognition and renown, the contrasting reputational ingredients associated with an enduring cultural appeal. Nevertheless, the novel’s declining reputation in recent years suggests that we should differentiate a cultural splash from the better-known dynamics of canonization and classicization. In the paper’s final section, I conceptualize a cultural splash as an effect generated by works that undergo a “fast transcendence” by unmooring themselves temporarily from the limiting effects of being counted as “art” or “pop.”
Identification of factors associated with various types of impaired driving
Authors: Rezapour Mahdi , Ksaibati Khaled 
Published: January 2022

AbstractDespite significant progress in reducing impaired driving, impaired drivers are still a public threat to themselves and others. Studying all types of drivers’ impairment is especially important as impairment in the literature has been mainly looked at from an angle of the driving under the influence (DUI). In other words, there is a definitional ambiguity regarding the impaired driving in the literature review. Addressing that unclarity is especially important as while many considered impaired driving such as distraction and fatigued driving are similar to DUI, they account for a higher proportion of fatalities on roadway, compared with DUI. Thus, first we highlight links between DUI and other impaired driving based on the literature review, and then this study highlighted factors associated with various impaired driving so drivers’ actions and behaviors could be addressed more efficiently. Here, in addition to DUI, impaired drivers are defined as whether drivers were fatigued, distracted, or under some emotional conditions at the time of crashes. Multinomial logit model (MNL) was extended to a model excluding or equating some coefficients across categories, making parameters’ estimates more robust. The analysis results highlighted, for instance, types of vehicles that the drivers own, drivers’ gender, age, seatbelt use, and various drivers’ actions such as failure to keep the proper lane and following too close are associated with various impaired drivers’ actions. These associations are expected to be related to unseen drivers’ characteristics that were not recorded at the time of crashes. This is one of the earliest comprehensive studies, investigating the association of various factors and different types of impaired driving.
Template switching in DNA replication can create and maintain RNA hairpins
Authors: Mönttinen Heli A. M. , Löytynoja Ari 
Published: January 2022

Significance
RNA hairpin structures require perfect pairing between consecutive bases of the opposite sides of the stem. Random mutations are unlikely to create complex structures, so the origin of long stems and the maintenance of their perfect base pairing through compensatory substitutions have puzzled evolutionary biologists. We reconstructed ancestral sequence histories of RNA sequences and found mutation patterns consistent with template switching in DNA replication. We propose the template switch mutation mechanism as the explanation for the evolution of perfect stem structures and show that the mechanism also provides an elegant explanation for multinucleotide jumps in the sequence space and for the observed asymmetry in the stem base pair frequencies.
Universal adaptability: Target-independent inference that competes with propensity scoring
Authors: Kim Michael P. , Kern Christoph , Goldwasser Shafi , Kreuter Frauke , Reingold Omer 
Published: January 2022

Significance
We revisit the problem of ensuring statistically valid inferences across diverse target populations from a single source of training data. Our approach builds a surprising technical connection between the inference problem and a technique developed for algorithmic fairness, called “multicalibration.” We derive a correspondence between the fairness goal, to protect subpopulations from miscalibrated predictions, and the statistical goal, to ensure unbiased estimates on target populations. We derive a single-source estimator that provides inferences in any downstream target population, whose performance is comparable to the popular target-specific approach of propensity score reweighting. Our approach can extend the benefits of evidence-based decision-making to communities that do not have the resources to collect high-quality data on their own.
Fundamental limitations on efficiently forecasting certain epidemic measures in network models
Authors: Rosenkrantz Daniel J. , Vullikanti Anil , Ravi S. S. , Stearns Richard E. , Levin Simon , Poor H. Vincent , Marathe Madhav V. 
Published: January 2022

Significance
We show that under widely believed complexity theoretic hypotheses, one cannot expect to find provably correct and efficient algorithms for predicting epidemic dynamics on general networks. These results hold even under idealized problem formulations, where all the model parameters are known and are insensitive to changes in environment. Further, they hold even for a small time horizon with just one random parameter, namely, the transmission probability. Thus, computational complexity poses an inherent challenge to effective and efficient epidemic forecasting in network models. Our results do not rule out heuristics that work well in practice or algorithms that provide provable guarantees for restricted networks. Rather, they suggest that algorithms working across a range of inputs should exploit properties of problem instances.
Ultrasound controlled mechanophore activation in hydrogels for cancer therapy
Authors: Kim Gun , Wu Qiong , Chu James L. , Smith Emily J. , Oelze Michael L. , Moore Jeffrey S. , Li King C. 
Published: January 2022

Significance
Biomedical application of mechanophores is the next frontier in polymer mechanochemistry. We report the concept, mechanochemical dynamic therapy (MDT), that utilizes remote, ultrasound-triggered mechanophore activation to enable anticancer activities. We selected an azo-based mechanophore to generate reactive free radicals (FRs) under the control of high-intensity focused ultrasound (HIFU), which subsequently produced ROS. We investigated two sets of in vitro mouse cancer models: 1) melanoma (B16F10) and 2) breast cancer (E0771). Inhibition of growth and decreases in viabilities of both B16F10 and E0771 were observed in correlation to the release of ROS by mechanophore activation. By circumventing the known issues in photodynamic therapy and sonodynamic therapy, we anticipate MDT to be a powerful anticancer tool complementary to other existing cancer treatments.
Structure and function of an effector domain in antiviral factors and tumor suppressors SAMD9 and SAMD9L
Authors: Peng Shuxia , Meng Xiangzhi , Zhang Fushun , Pathak Prabhat Kumar , Chaturvedi Juhi , Coronado Jaime , Morales Marisol , Mao Yuanhui , Qian Shu-Bing , Deng Junpeng , Xiang Yan 
Published: January 2022

Significance
SAMD9 and SAMD9L (SAMD9/9L) are important innate immune defenders against viruses and the development of myeloid tumors. They form a crucial host barrier that poxviruses must overcome for successful infection. A myriad of human diseases including many pediatric myelodysplastic syndromes are caused by mutations in SAMD9/9L. However, the molecular functions of SAMD9/9L and how their functions are executed are unknown, hindering progress in developing effective therapies for SAMD9/9L-associated human diseases. Here, we identified the structure and function of a SAMD9/9L effector domain that is essential for their physiological functions as well as the pathogenic effects exerted by patient-derived mutations. Our study revealed a potential therapeutic target for SAMD9/9L-associated human diseases.
A descriptive study on Chinese-English subtitling of extralinguistic culture-bound references in Empresses in the Palace
Authors: Xie Ying 
Published: January 2022

Abstract
The American version of Empresses in the Palace (《甄嬛传》) can be seen as a representative example of Chinese-to-English subtitled ancient costume drama, and an effective source of study as to how Extralinguistic Culture-bound References (ECRs) (Pedersen, 2005, 2011) in the source-language subtitles can emphasize and embody the essence of ancient Chinese culture. Based on Pedersen’s (2005, 2011) theory of the Transculturality level of ECRs and through statistical as well as textual analysis, this paper aims to conduct a descriptive study of extralinguistic culture-bound references (ECRs) in Empresses in the Palace and the Chinese-English subtitling strategies of the ECRs. It found that Monocultural ECRs account for a substantial proportion of the ECRs, with eight ECR domains covered, and that the Source Language (SL)-oriented Strategies as well as Substitution are the foremost translation strategies adopted for rendering Monocultural ECRs. Eventually, based on textual analysis of the Monocultural ECRs rendered by the SL-oriented Strategies and Substitution, from the perspective of the target audience’s plot interpretation of the drama, this paper concludes that an obvious disadvantage as a result of the Monocultural ECR’s interlingual subtitling in Empresses in the Palace is that the plot revealed in the target-language subtitles becomes logically incoherent.
Morphological shift of hyperbolic patterns in the Quran, with reference to English translation
Authors: Najjar Ibrahim , Kadhim Kais Amir , Al-Heeh Sami 
Published: January 2022

AbstractThis study addresses the use of hyperbole in the Quran at the word level and its English translation. It investigates the morphological shift of hyperbolic patterns such as ‘Fa’uul (فعول), Fa’eel (فعيل) and Fa’aal’ (فعال) and their corresponding English translations. We attempt to determine the implications underlying the translation strategies for the translation quality of the data under study. Under this circumstance, the translator applied a series of translation strategies, such as literal translation, paraphrase, transposition, and morphological strategies, with transposition being the most employed strategy. Such strategies were in some cases a problem for the functions of the Quranic hyperboles. As such, the translation quality was occasionally poor.
An inversion algorithm for P-functions with applications to multi-energy CT
Authors: Bal Guillaume , Gong Ruoming , Terzioglu Fatma 
Published: January 2022

Abstract
Multi-energy computed tomography (ME-CT) is an x-ray transmission imaging technique that uses the energy dependence of x-ray photon attenuation to determine the elemental composition of an object of interest. Mathematically, forward ME-CT measurements are modeled by a nonlinear integral transform. In this paper, local conditions for global invertibility of the ME-CT transform are studied, and explicit stability estimates quantifying the error propagation from measurements to reconstructions are provided. Motivated from the inverse problem of image reconstruction in ME-CT, an iterative inversion algorithm for the so-called P-functions is proposed. Numerical simulations for ME-CT, in two and three materials settings with an equal number of energy measurements, confirm the theoretical predictions.
Influence of plasma density on radiative recombination cross sections of oxygen ions
Authors: Ribière Maxime 
Published: January 2022

Abstract
Radiative recombination cross sections of oxygen ions from O+ to O6+ are calculated by an atomic model assuming central field and Hartree–Fock–Slater approximation for exchange potential. The recombining ions are considered on their ground states, to form recombined ions on their ground states as well as on several subshells up to 4d. The effect of plasma density on the cross sections is taken into account by varying the Wigner–Seitz cell representing the atomic volume containing bound and free electrons. It is shown that the increase of plasma density significantly enhances the cross sections involving excited states of the recombined ions at atmospheric pressures and beyond. These cross sections may be used in collisional-radiative models for fully ionized plasma simulations in the frame work of, for example, switches in Marx generator and laser-induced plasmas in air.
Tuning superconductivity with spin–orbit coupling and proximity effects in ferromagnet/superconductor/ heavy metal heterostructures
Authors: Zhao Duo , Wang Xiaolei , Wang Zhijie , Wei Dahai 
Published: January 2022

Abstract
In superconducting/ferromagnet heterostructures, spin-triplet Cooper pairs that carry spin information are crucial for the realization of superconducting spintronics. It has been theoretically proposed that they can be generated and controlled by the magnetic proximity effect and spin–orbit coupling (SOC), resulting in a change in the critical temperature (T
C). However, experiments are still lacking, which limits the development of device applications. Here, we fabricate a series of Co/Nb/Pt heterostructures and reference samples, where the SOC and magnetic proximity can be independently controlled. We found the suppression of T
C up to 11% by the different Rashba-SOC at the Nb/Pt and Nb/Cu interfaces, and the normalized T
C/T
C
0 was successfully tuned by 24% with the coeffect of SOC and magnetic proximity. Through rigorous comparison, we attribute the tuning of superconductivity to the spin-triplet Cooper pairs, which is controlled by both the SOC strength and magnetic proximity. Our results offer a new pathway to control superconductivity with SOC and pave a new direction for the design of superconducting spintronics devices.
Ultra-slow electron spin-lattice relaxation in a low magnetic field enables massive optical spin polarization in the 4A2 ground state of Cr3+
in ruby*
Authors: Riesen Hans 
Published: January 2022

Abstract
Ruby (α-Al2O3 doped with Cr3+) has been an archetypal material in the development of optical spectroscopy of the solid state for the last 150 years and was the first material that was demonstrated to lase. Notwithstanding the vast literature on ruby, one effect was somehow missed: in a magnetic field B
∥c ∼ 235 mT, the spin-lattice relaxation time T
1 for the |+3/2⟩ level in the 4A2 ground state is massively lengthened to ∼12 s at 1.4 K as demonstrated in this study. This very long relaxation time enables optical pumping of the |+3/2⟩ level via the R
1(±1/2) lines and a considerable +3/2 spin polarization of ∼95% is readily achieved. The observed magnetic field dependence can be quantitatively described using the one-phonon relaxation process.