bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the Digital Disruption of Health Care: An Ethnographic Study of Real-Time Multidisciplinary Clinical Behavior in a New Digital Hospital
Authors: Canfell Oliver J. , Meshkat Yasaman , Kodiyattu Zack , Engstrom Teyl , Chan Wilkin , Mifsud Jayden , Pole Jason D. , Byrne Martin , Raders Ella Van , Sullivan Clair 
Published: November 2022

Abstract
Background Understanding electronic medical record (EMR) implementation in digital hospitals has focused on retrospective “work as imagined” experiences of multidisciplinary clinicians, rather than “work as done” behaviors. Our research question was “what is the behavior of multidisciplinary clinicians during the transition to a new digital hospital?”
Objectives The aim of the study is to: (1) Observe clinical behavior of multidisciplinary clinicians in a new digital hospital using ethnography. (2) Develop a thematic framework of clinical behavior in a new digital hospital.
Methods The setting was the go-live of a greenfield 182-bed digital specialist public hospital in Queensland, Australia. Participants were multidisciplinary clinicians (allied health, nursing, medical, and pharmacy). Clinical ethnographic observations were conducted between March and April 2021 (approximately 1 month post-EMR implementation). Observers shadowed clinicians in real-time performing a diverse range of routine clinical activities and recorded any clinical behavior related to interaction with the digital hospital. Data were analyzed in two phases: (1) content analysis using machine learning (Leximancer v4.5); (2) researcher-led interpretation of the text analytics to generate contextual meaning and finalize themes.
Results A total of 55 multidisciplinary clinicians (41.8% allied health, 23.6% nursing, 20% medical, 14.6% pharmacy) were observed across 58 hours and 99 individual patient encounters. Five themes were derived: (1) Workflows for clinical documentation; (2) Navigating a digital hospital; (3) Digital efficiencies; (4) Digital challenges; (5) Patient experience. There was no observed harm attributable to the digital transition. Clinicians primarily used blended digital and paper workflows to achieve clinical goals. The EMR was generally used seamlessly. New digital workflows affected clinical productivity and caused frustration. Digitization enabled multitasking, clinical opportunism, and benefits to patient safety; however, clinicians were hesitant to trust digital information.
Conclusion This study improves our real-time understanding of the digital disruption of health care and can guide clinicians, managers, and health services toward digital transformation strategies based upon “work as done.”
Influence of isotope effect on radiation resistance of monocrystalline silicon
Authors: Zhang Yuehui , Lu Jingbin , Li Chengqian , Qu Huan , Zhang Xue , Situ Zirui , Liu Xinrui , Liu Yumin 
Published: November 2022

This paper examined the impact of the isotope effect on the lattice structure of monocrystalline silicon, as well as the defects caused by proton irradiation. First, by using the molecular dynamics simulation, the number of point defects of monocrystalline silicon exposed to protons was calculated, and the number of stable defects in 30Si was 11%–14% lower than that in 28Si. Second, the structures of various isotopes at 300 K were simulated through ab initio molecular dynamics simulations based on the density functional theory. In addition, the thermal stability of the two structures was determined. The results indicated that pure 30Si had superior radiation resistance to pure 28Si, which suggested a new idea for the radiation resistance enhancement of silicon materials.
Do registers have different functions for text length?
Authors: Liimatta Aatu 
Published: November 2022

AbstractSimilar to lexical and grammatical choices, the length of a text is also guided by situational constraints and functional needs. Consequently, texts of different lengths are associated with different communicative functions. This study explores the role of register in the functions which are associated with comment lengths on the social media platform Reddit. Since registers differ in their functional and situational makeup, the same text length may also have different functions in different registers. By analyzing variation in the frequencies of register features across comment lengths in a number of popular subreddits in a large-scale dataset of Reddit comments, I show that the functional associations of text length can differ greatly between subreddits, and that comments of the same length can even have virtually opposite functions in different subreddits. Furthermore, some subregisters are clearly differentiated not only by their feature makeup but also by the length of their comments.
Research on foreign object detection method in track area based on Mask-RCNN
Authors: Ji Guoyi , Chen Wen , Zou Jinbai , Wei Shiyan 
Published: November 2022

Abstract
As the train speeds up, the damage caused by the collisions between trains and foreign objects are becoming more and more severe. Therefore, it is of great significance to monitor the intrusion of foreign objects in the track environment. In this paper, transfer learning is introduced into Mask-RCNN deep learning model. And the data set of rail image is used to train the model, which improves the effect of rail segmentation. The trained model is used to segment the rail in the picture, and the rail vulnerable area is divided based on the segmentation results. The sliding window ORB feature matching algorithm is used to calculate the similarity of vulnerable area. The detection of foreign objects in the area where is easy to invade is realized, and the detection reliability is improved. Experiments represent that this method has high accuracy, strong practicability, good robustness and universality.
Optimal Design of a Cable Driven Parallel Robot for Upper Limb Rehabilitations
Authors: Liao Bin , Li Jun , Deng Shichao , Li Jianmin , Li Guohui 
Published: November 2022

Abstract
A novel cable driven parallel robot is introduced to assist upper limb in rehabilitation treatments in this paper, which has a lightweight structure. This robot is characterized by a novel and flexible end-effector that is easy to change assembly for different therapies. And it is designed for desktop usage, so its size is not too large. After presenting the structure, the kinematic model is presented for optimal design. Then, the minimal singular value is considered as the velocity transmission index. For upper limb rehabilitation, a new optimal design problem with the transmission index and the robot size is formulated. Last, the optimization presents a design with satisfying performances in velocity transmission capability and robot size.
Optimization prediction and experimental verification of cyclone performance based on BP neural network
Authors: Sun Mochuan , Wang jiangang , He fengqin , Long zhiqiang 
Published: November 2022

Abstract
As a kind of centrifugal separation equipment, hydrocyclone has developed rapidly with the advantages of high economic benefits, good compactness, high processing efficiency, simple process and so on. Hydrocyclone has broad practical significance and application prospects in chemical, light industry, oil mining and refining, environmental protection, medicine, food processing, ship transportation and surface oil spill treatment. BP neural networks are mainly used in the following four aspects: function approximation, pattern recognition, classification, and data compression. In this paper, we introduce the principle of BP neural network, establish an analytical model, apply BP neural network to predict the performance of hydrocyclone, and conduct experimental verification to optimize the hydrocyclone under different working conditions according to the experimental results.
Influence of surface termination groups on electrochemical charge storage of MXene electrodes
Authors: Kawai Kosuke , Fujita Masaki , Iizuka Ryosei , Yamada Atsuo , Okubo Masashi 
Published: November 2022

Abstract
Two-dimensional transition-metal carbides/nitrides (MXenes) have been intensively investigated as electrode materials for electrochemical energy storage devices, such as batteries and supercapacitors, due to their high capacitance, high-rate capability, and good cycle stability. Although MXenes possess various surface termination groups (e.g., –O, –OH, –F, –Cl, and –Br) that directly interact with adsorbed cations to exhibit charge transfer, the influence of each surface termination group on the electrochemical properties of MXene remains elusive because of difficulty in achieving exclusively modified termination. Herein, we report the electrochemical properties of MXenes with surface termination groups controlled by using fluorine-based aqueous solutions and molten salts as etchants. In aqueous electrolytes, Ti3C2Cl
x
and Ti3C2Br
x
synthesized using molten salts show no electrochemical activity in contrast to Ti3C2T
x
(T = O, OH, F, and Cl). Meanwhile, in a nonaqueous electrolyte, Ti3C2Cl
x
and Ti3C2Br
x
undergo amorphization upon the initial lithiation. These results suggest that the –O, –OH, and –F terminations play an important role in the electrochemical properties of MXene electrodes.
Verification of colorable hypergraph states with stabilizer test
Authors: Tao Hong , Zhang Xiaoqian , Shao Lei , Tan Xiaoqing 
Published: November 2022

Abstract
Many-body quantum states, as a matter of fact, are extremely essential to solve certain mathematical problems or simulate quantum systems in measurement-based quantum computation. However, how to verify large-scale quantum states, such as hypergraph states, is an exceedingly hard task for many-body quantum systems. Here, we propose a novel fault-tolerant solution for the verification of colorable hypergraph states by using the stabilizer test. Furthermore, our protocol is dramatically facilitated by making only Pauli-X and Pauli-Z measurements. For geometric structure hypergraph states, the computational complexity of our protocol is polynomial. As to appliance, it will be also applied to blind quantum computing based on the no-signaling principle.
Collisional S-matrix for the vibrational dynamics of H+H2 by quantum computing
Authors: Wang Yulun , Krstic Predrag S 
Published: November 2022

Abstract
An algorithm and a system of quantum circuits are developed and applied to compute accurately the S matrix for the transitions between vibrational states of H2 for collisions with H. The algorithm was applied to 100 eV laboratory collision energy at a quantum circuit simulator. The effects of the discretized dissociative continuum to the transition cross sections are carefully studied and accuracy and convergence of the results with the chosen parameters of the algorithm and the collision system are verified by comparison with a solution of the time-dependent Schrodinger equation using the classical algorithm as well as comparison with a few results from the literature.
Evolutionary algorithm-based multiobjective reservoir operation policy optimisation under uncertainty
Authors: Wu Wenyan , Zhou Yuerong , Leonard Michael 
Published: November 2022

Abstract
Reservoir operation optimisation is a decision support tool to assist reservoir operators with water release decisions to achieve management objectives, such as maximising water supply security, mitigating flood risk, and maximising hydroelectric power generation. The effectiveness of reservoir operation decisions is subject to uncertainty in system inputs, such as inflow and therefore, methods such as stochastic dynamic programming (SDP) have been traditionally used. However, these methods suffer from the three curses of dimensionality, modelling, and multiple objectives. Evolutionary algorithm (EA)-based simulation-optimisation frameworks such as the Evolutionary Multi-Objective Direct Policy Search (EMODPS) offer a new paradigm for multiobjective reservoir optimisation under uncertainty, directly addressing the shortcomings of SDP-based methods. They also enable the consideration of input uncertainty represented using ensemble forecasts that have become more accessible recently. However, there is no universally agreed approach to incorporate uncertainty into EA-based multiobjective reservoir operation policy optimisation and it is not clear which approach is more effective. Therefore, this study conducts a comparative analysis to demonstrate the advantages and limitations of different approaches to account for uncertainty in multiobjective reservoir operation policy optimisation via a real-world case study; and provide guidance on the selection of appropriate approaches. Based on the results obtained, it is evident that each approach has both advantages and limitations. A suitable approach needs to be carefully selected based on the needs of the study, e.g., whether a hard constraint is required, or a well-established decision-making process exists. In addition, potential gaps for future research are identified.
Municipal climate communication as a tool in amplifying local climate action and developing a place brand
Authors: Nousiainen Niina , Riekkinen Venla , Meriläinen Teemu 
Published: November 2022

AbstractBoth climate communication and place branding are familiar concepts, whose potentials have been recognized. Cities have engaged in communication and climate work for several years, yet studies linking municipal climate action and communication are scarce. We conducted targeted interviews and a broader survey of climate workers and communicators of forerunner municipalities in Finland and found gaps between climate action and communication. Synergies could be achieved if the two functioned in synchronicity rather than separate tasks, as words require actions, but full impacts of actions fall short without communication. Municipalities have progressed on both fronts but are hindered by lacking time and human resources. Results revealed several opportunities of climate communication in amplifying local climate action and strengthening municipal brand image, but many remain underexploited. Sufficient resources and stronger legitimacy are still needed for climate matters to be better integrated into everything the municipality does and communicates.
Incompleteness of graph neural networks for points clouds in three dimensions
Authors: Pozdnyakov Sergey N , Ceriotti Michele 
Published: November 2022

Abstract
Graph neural networks (GNN) are very popular methods in machine learning and have been applied very successfully to the prediction of the properties of molecules and materials. First-order GNNs are well known to be incomplete, i.e. there exist graphs that are distinct but appear identical when seen through the lens of the GNN. More complicated schemes have thus been designed to increase their resolving power. Applications to molecules (and more generally, point clouds), however, add a geometric dimension to the problem. The most straightforward and prevalent approach to construct graph representation for molecules regards atoms as vertices in a graph and draws a bond between each pair of atoms within a chosen cutoff. Bonds can be decorated with the distance between atoms, and the resulting ‘distance graph NNs’ (dGNN) have empirically demonstrated excellent resolving power and are widely used in chemical ML, with all known indistinguishable configurations being resolved in the fully-connected limit, which is equivalent to infinite or sufficiently large cutoff. Here we present a counterexample that proves that dGNNs are not complete even for the restricted case of fully-connected graphs induced by 3D atom clouds. We construct pairs of distinct point clouds whose associated graphs are, for any cutoff radius, equivalent based on a first-order Weisfeiler-Lehman (WL) test. This class of degenerate structures includes chemically-plausible configurations, both for isolated structures and for infinite structures that are periodic in 1, 2, and 3 dimensions. The existence of indistinguishable configurations sets an ultimate limit to the expressive power of some of the well-established GNN architectures for atomistic machine learning. Models that explicitly use angular or directional information in the description of atomic environments can resolve this class of degeneracies.
High Satisfaction With a Virtual Assistant for Plastic Surgery Frequently Asked Questions
Authors: Avila Francisco R , Boczar Daniel , Spaulding Aaron C , Quest Daniel J , Samanta Arindam , Torres-Guzman Ricardo A , Maita Karla C , Garcia John P , Eldaly Abdullah S , Forte Antonio J 
Published: November 2022

Abstract

Background
Most of a surgeon's office time is dedicated to patient education, preventing an appropriate patient-physician relationship. Telephone-accessed artificial intelligent virtual assistants (AIVAs) that simulate a human conversation and answer preoperative frequently asked questions (FAQs) can be effective solutions to this matter. An AIVA capable of answering preoperative plastic surgery–related FAQs has previously been described by the authors.

Objectives
The aim of this paper was to determine patients’ perception and satisfaction with an AIVA.

Methods
Twenty-six adult patients from a plastic surgery service answered a 3-part survey consisting of: (1) an evaluation of the answers’ correctness, (2) their agreement with the feasibility, usefulness, and future uses of the AIVA, and (3) a section on comments. The first part made it possible to measure the system's accuracy, and the second to evaluate perception and satisfaction. The data were analyzed with Microsoft Excel 2010 (Microsoft Corporation, Redmond, WA).

Results
The AIVA correctly answered the patients’ questions 98.5% of the time, and the topic with the lowest accuracy was “nausea.” Additionally, 88% of patients agreed with the statements of the second part of the survey. Thus, the patients’ perception was positive and overall satisfaction with the AIVA was high. Patients agreed the least with using the AIVA to select their surgical procedure. The comments provided improvement areas for subsequent stages of the project.

Conclusions
The results show that patients were satisfied and expressed a positive experience with using the AIVA to answer plastic surgery FAQs before surgery. The system is also highly accurate.
Metadensity: a background-aware python pipeline for summarizing CLIP signals on various transcriptomic sites
Authors: Her Hsuan-Lin , Boyle Evan , Yeo Gene W 
Published: November 2022

Abstract

Motivation
Cross-linking and immunoprecipitation (CLIP) is a technology to map the binding sites of RNA-binding proteins (RBPs). The region where an RBP binds within RNA is often indicative of its molecular function in RNA processing. As an example, the binding sites of splicing factors are found within or proximal to alternatively spliced exons. To better reveal the function of RBPs, we developed a tool to visualize the distribution of CLIP signals around various transcript features.

Results
Here, we present Metadensity (https://github.com/YeoLab/Metadensity), a software that allows users to generate metagene plots. Metadensity allows users to input features such as branchpoints and preserves the near-nucleotide resolution of CLIP technologies by not scaling the features by length. Metadensity normalizes immunoprecipitated libraries with background controls, such as size-matched inputs, then windowing in various user-defined features. Finally, the signals are averaged across a provided set of transcripts.

Availability and implementation
Metadensity is available at https://github.com/YeoLab/Metadensity, with example notebooks at https://metadensity.readthedocs.io/en/latest/tutorial.html.

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
CAPG: comprehensive allopolyploid genotyper
Authors: Kulkarni Roshan , Zhang Yudi , Cannon Steven B , Dorman Karin S 
Published: November 2022

Abstract

Motivation
Genotyping by sequencing is a powerful tool for investigating genetic variation in plants, but many economically important plants are allopolyploids, where homoeologous similarity obscures the subgenomic origin of reads and confounds allelic and homoeologous SNPs. Recent polyploid genotyping methods use allelic frequencies, rate of heterozygosity, parental cross or other information to resolve read assignment, but good subgenomic references offer the most direct information. The typical strategy aligns reads to the joint reference, performs diploid genotyping within each subgenome, and filters the results, but persistent read misassignment results in an excess of false heterozygous calls.

Results
We introduce the Comprehensive Allopolyploid Genotyper (CAPG), which formulates an explicit likelihood to weight read alignments against both subgenomic references and genotype individual allopolyploids from whole-genome resequencing data. We demonstrate CAPG in allotetraploids, where it performs better than Genome Analysis Toolkit’s HaplotypeCaller applied to reads aligned to the combined subgenomic references.

Availability and implementation
Code and tutorials are available at https://github.com/Kkulkarni1/CAPG.git.

Supplementary information
Supplementary data are available at Bioinformatics online.