bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lung sparing in MR-guided non-adaptive SBRT treatment of peripheral lung tumors
Authors: Lee Ho Young , Lee Grace , Ferguson Dianne , Hsu Shu-Hui , Hu Yue-Houng , Huynh Elizabeth , Sudhyadhom Atchar , Williams Christopher L , Cagney Daniel N , Fitzgerald Kelly J , Kann Benjamin H , Kozono David , Leeman Jonathan E , Mak Raymond H , Han Zhaohui 
Published: June 2024

Abstract

Objective. We aim to: (1) quantify the benefits of lung sparing using non-adaptive magnetic resonance guided stereotactic body radiotherapy (MRgSBRT) with advanced motion management for peripheral lung cancers compared to conventional x-ray guided SBRT (ConvSBRT); (2) establish a practical decision-making guidance metric to assist a clinician in selecting the appropriate treatment modality. Approach. Eleven patients with peripheral lung cancer who underwent breath-hold, gated MRgSBRT on an MR-guided linear accelerator (MR linac) were studied. Four-dimensional computed tomography (4DCT)-based retrospective planning using an internal target volume (ITV) was performed to simulate ConvSBRT, which were evaluated against the original MRgSBRT plans. Metrics analyzed included planning target volume (PTV) coverage, various lung metrics and the generalized equivalent unform dose (gEUD). A dosimetric predictor for achievable lung metrics was derived to assist future patient triage across modalities. Main results. PTV coverage was high (median V100% > 98%) and comparable for both modalities. MRgSBRT had significantly lower lung doses as measured by V20 (median 3.2% versus 4.2%), mean lung dose (median 3.3 Gy versus 3.8 Gy) and gEUD. Breath-hold, gated MRgSBRT resulted in an average reduction of 47% in PTV volume and an average increase of 19% in lung volume. Strong correlation existed between lung metrics and the ratio of PTV to lung volumes (RPTV/Lungs) for both modalities, indicating that RPTV/Lungs may serve as a good predictor for achievable lung metrics without the need for pre-planning. A threshold value of RPTV/Lungs < 0.035 is suggested to achieve V20 < 10% using ConvSBRT. MRgSBRT should otherwise be considered if the threshold cannot be met. Significance. The benefits of lung sparing using MRgSBRT were quantified for peripheral lung tumors; RPTV/Lungs was found to be an effective predictor for achievable lung metrics across modalities. RPTV/Lungs can assist a clinician in selecting the appropriate modality without the need for labor-intensive pre-planning, which has significant practical benefit for a busy clinic.
Interference voltage measurement and analysis of cardiac implants exposed to electric fields at extremely low frequency
Authors: Zhou Mengxi , Kourtiche Djilali , Claudel Julien , Deschamps Francois , Magne Isabelle , Roth Patrice , Schmitt Pierre , Nadi Mustapha 
Published: June 2024

Abstract

Objective. The possibility of interference by electromagnetic fields in the workplaces with cardiac implants is a concern for both individuals and employers. This article presents an analysis of the interference to which cardiac implants are subjected under high-intensity electric field at the power frequency. Approach. Evaluations of interference were conducted by studying the induced voltages at the device input in the real case study and the substitute study, and establishing an association between them with the equivalence factor F. A funnel-shaped phantom, designed for in vitro testing and representing the electrical characteristics of the locations where cardiac implants are installed, was used in the substitute study. A measuring system was implemented to measure the induced voltage at the device input under high intensity electric fields. Main results. The induced voltages obtained in the experimental measurements align with the findings of the numerical study in the phantom. By applying the equivalence factors derived between the real case study and the substitute study (2.39 for unipolar sensing; 3.64 for bipolar sensing), the induced voltages on the cardiac implants can be determined for the real case using the substitute experimental set-up. Significance. The interference voltages on the cardiac implants under electric field exposures at low frequency were experimentally measured with detailed description. The findings provide evidence for an analysis method to systematically study the electromagnetic interference on the cardiac implants at low frequency.
Simulation of charge-exchange induced NBI losses on EAST
Authors: LIN 林 Zhanhong 展宏 , WANG 王 Feng 丰 , XU 徐 Ming 明 , SANG 桑 Chaofeng 超峰 , ZHANG 张 Chen 晨 , WANG 王 Zhengxiong 正汹 
Published: June 2024

Abstract
The neutral beam injection is widely adopted in tokamaks as a key heating tool, playing a crucial role in generating burning plasmas. However, the loss of beam ions can damage the first wall and reduce the heating efficiency, resulting in failure to maintain steady-state conditions. In this work, the effect of neutral particles in the edge on fast ions generated by NBI in the Experimental Advanced Superconducting Tokamak (EAST) device is studied using the particle tracer code (PTC). The poloidal distribution of neutral particles is calculated by edge plasma simulation code SOLPS-ITER. In this simulation, four beam lines in EAST are considered: co-current tangential (co-tang), co-current perpendicular (co-perp), counter-current tangential (ctr-tang) and counter-current perpendicular (ctr-perp). It is shown that, in the absence of neutral particles, the loss fraction of ctr-injection is considerably higher than that of the co-injection. When considering the neutral particles, it is found that the ctr-perp injection demonstrates a significant variation in particles loss fraction (ranging from 18.56% to 25.42%) compared to the other three injection configurations. In terms of the loss fraction induced by neutral particles, ctr-injection exceeds co-injection, and perpendicular configuration exceeds tangential configuration. Furthermore, the difference of charge exchange ratios of three different energy (full energy, half energy, one third energy) of the four injections can be attributed to variations in the poloidal trajectories associated with each of these injections. Moreover, approximately half of fast ions which undergo neutralization directly lose to the first wall while the rest re-enter the bulk plasma and re-ionize. Except for the ctr-tang injection, the reionization ions from the other three injections exhibit effective confinement.
AI and the next medical revolution: deep learning’s uncharted healthcare promise
Authors: L B Krithika , S Vishnu , Kotei Evans , Gadde Ashok , Kothamasu Ganga Abhirup , Nallabantu Sri Charan , J Guruprakash 
Published: June 2024

Abstract
Deep learning has shown tremendous potential for transforming healthcare by enabling more accurate diagnoses, improved treatment planning and better patient outcome predictions. In this comprehensive survey, we provide a detailed overview of the state-of-the-art deep learning techniques and their applications across the healthcare ecosystem. We first introduce the fundamentals of deep learning and discuss its key advantages compared to traditional machine learning approaches. We then present an in-depth review of major applications of deep learning in medical imaging, electronic health record analysis, genomics, medical robotics and other domains. For each application, we summarize key advancements, outline the technical details of state-of-the-art methods, discuss challenges and limitations and highlight promising directions for future work. We examine cross-cutting challenges in deploying deep learning in clinical settings, including interpretability, bias and data scarcity. We conclude by proposing a roadmap to accelerate the translation and adoption of high-impact healthcare applications of deep learning. Overall, this survey provides a comprehensive reference for researchers and practitioners working at the intersection of deep learning and healthcare.
Track fastener detection in special scenarios based on TSR-Net
Authors: Bai Tangbo , Duan Jiaming , Fu Haochen , Zong Hao 
Published: June 2024

Abstract
The traditional method of detecting track fasteners can lead to erroneous results due to the presence of rail bolts, wires, and extraneous objects such as stones. Consequently, the study of fastener detection in specific environments is essential. To address these issues, the TSR-Net target detection model is introduced, which employs an efficient vision transformer as a backbone to increase the speed of feature extraction. The global image perception of the network is enhanced by integrating translation convolutions and inverted residual blocks within the neck network. A detection head with a self-supervised equivariant attention mechanism is designed to deal with the occlusion challenges of small fastener targets. The model is implemented on edge AI computing devices. Technical validation indicates that TSR-Net achieves 94.2% detection precision and operates at 47 frames per second, thereby enabling accurate, real-time detection of small-target occlusion fasteners.
The R-mAtrIx Net
Authors: Lal Shailesh , Majumder Suvajit , Sobko Evgeny 
Published: June 2024

Abstract
We provide a novel neural network architecture that can: i) output R-matrix for a given quantum integrable spin chain, ii) search for an integrable Hamiltonian and the corresponding R-matrix under assumptions of certain symmetries or other restrictions, iii) explore the space of Hamiltonians around already learned models and reconstruct the family of integrable spin chains which they belong to. The neural network training is done by minimizing loss functions encoding Yang–Baxter equation, regularity and other model-specific restrictions such as hermiticity. Holomorphy is implemented via the choice of activation functions. We demonstrate the work of our neural network on the spin chains of difference form with two-dimensional local space. In particular, we reconstruct the R-matrices for all 14 classes. We also demonstrate its utility as an Explorer, scanning a certain subspace of Hamiltonians and identifying integrable classes after clusterisation. The last strategy can be used in future to carve out the map of integrable spin chains with higher dimensional local space and in more general settings where no analytical methods are available.
Deep learning methods for Hamiltonian parameter estimation and magnetic domain image generation in twisted van der Waals magnets
Authors: Lee Woo Seok , Song Taegeun , Kim Kyoung-Min 
Published: June 2024

Abstract
The application of twist engineering in van der Waals magnets has opened new frontiers in the field of two-dimensional magnetism, yielding distinctive magnetic domain structures. Despite the introduction of numerous theoretical methods, limitations persist in terms of accuracy or efficiency due to the complex nature of the magnetic Hamiltonians pertinent to these systems. In this study, we introduce a deep-learning approach to tackle these challenges. Utilizing customized, fully connected networks, we develop two deep-neural-network kernels that facilitate efficient and reliable analysis of twisted van der Waals magnets. Our regression model is adept at estimating the magnetic Hamiltonian parameters of twisted bilayer CrI3 from its magnetic domain images generated through atomistic spin simulations. The ‘generative model’ excels in producing precise magnetic domain images from the provided magnetic parameters. The trained networks for these models undergo thorough validation, including statistical error analysis and assessment of robustness against noisy injections. These advancements not only extend the applicability of deep-learning methods to twisted van der Waals magnets but also streamline future investigations into these captivating yet poorly understood systems.
Laughter Means Sympathy?
Authors: Ward Matthew 
Published: June 2024

Abstract
Opening with Thomas Carlyle’s unusual suggestion in 1840 that ‘laughter means sympathy’, this chapter explores the complicated and ambivalent place of laughter within the culture of feeling of the eighteenth century and Romantic period. For many at the time, to be a man of feeling was to be a man of humour, while humour was ‘regarded as the finest perfection of poetic genius’. Yet laughter had a troubled relation to sympathy and Romantic poetry, not least on account of its association with ridicule, and restive, disruptive energies. This chapter uncovers how writers resort to a language of feeling to try and account for the vagaries of ludicrous and inexplicable emotions. It thus establishes the animating tensions and strange incongruities at the heart of the laughter of feeling, where a laugh is both an articulation or embodiment of sympathy and a strange resistance to it. Laughter shows the complicated position of sympathy in the era as something to pursue and promote, and retain a sceptical, ironic sense of humour about.
Critical care pharmacist perspectives on optimal practice models and prioritization of professional activities: A cross-sectional survey
Authors: Smith Zachary R , Palm Nicole M , Smith Susan E , Dixit Deepali , Keats Kelli , Ciapala Stephanie R , Tran Tien , Sikora Andrea , Heavner Mojdeh S 
Published: June 2024

Abstract

Purpose
Critical care pharmacists (CCPs) are essential members of the multidisciplinary critical care team. Professional activities of the CCP are outlined in a 2020 position paper on critical care pharmacy services. This study looks to characterize CCP perspectives for priorities in optimizing pharmacy practice models and professional activities.

Methods
This was a cross-sectional survey conducted from July 24 to September 20, 2023. A 41-question survey instrument was developed to assess 7 domains: demographics, CCP resource utilization, patient care, quality improvement, research and scholarship, training and education, and professional development. This voluntary survey was sent to members of the American College of Clinical Pharmacy’s Critical Care Practice and Research Network. The survey was open for a total of 6 weeks.

Results
There was a response rate of 20.7% (332 of 1,605 invitees), with 66.6% of respondents (n = 221) completing at least 90% of the survey questions. Most respondents were clinical specialists (58.2%) and/or practiced at an academic medical center (58.5%). Direct patient care, quality improvement and medication safety, and teaching and precepting were identified as the CCP activities of highest importance to CCPs. The CCP-to-patient ratios considered ideal were 1:11-15 (selected by 49.8% of respondents) and 1:16-20 (33.9% of respondents). The ideal percentage of time dedicated to direct patient care activities, as identified by survey respondents, was 50% (interquartile range, 40-50).

Conclusion
These findings highlight the professional activities viewed as having the highest priority by CCPs. Future research is needed to define optimal CCP practice models for the delivery of patient care in real-world settings.
Integration of protein sequence and protein–protein interaction data by hypergraph learning to identify novel protein complexes
Authors: Xia Simin , Li Dianke , Deng Xinru , Liu Zhongyang , Zhu Huaqing , Liu Yuan , Li Dong 
Published: June 2024

AbstractProtein–protein interactions (PPIs) are the basis of many important biological processes, with protein complexes being the key forms implementing these interactions. Understanding protein complexes and their functions is critical for elucidating mechanisms of life processes, disease diagnosis and treatment and drug development. However, experimental methods for identifying protein complexes have many limitations. Therefore, it is necessary to use computational methods to predict protein complexes. Protein sequences can indicate the structure and biological functions of proteins, while also determining their binding abilities with other proteins, influencing the formation of protein complexes. Integrating these characteristics to predict protein complexes is very promising, but currently there is no effective framework that can utilize both protein sequence and PPI network topology for complex prediction. To address this challenge, we have developed HyperGraphComplex, a method based on hypergraph variational autoencoder that can capture expressive features from protein sequences without feature engineering, while also considering topological properties in PPI networks, to predict protein complexes. Experiment results demonstrated that HyperGraphComplex achieves satisfactory predictive performance when compared with state-of-art methods. Further bioinformatics analysis shows that the predicted protein complexes have similar attributes to known ones. Moreover, case studies corroborated the remarkable predictive capability of our model in identifying protein complexes, including 3 that were not only experimentally validated by recent studies but also exhibited high-confidence structural predictions from AlphaFold-Multimer. We believe that the HyperGraphComplex algorithm and our provided proteome-wide high-confidence protein complex prediction dataset will help elucidate how proteins regulate cellular processes in the form of complexes, and facilitate disease diagnosis and treatment and drug development. Source codes are available at https://github.com/LiDlab/HyperGraphComplex.
biotextgraph: graphical summarization of functional similarities from textual information
Authors: Sato Noriaki , Zhang Yao-zhong , Gu Zuguang , Imoto Seiya 
Published: June 2024

Abstract

Summary
Functional interpretation of biological entities such as differentially expressed genes is one of the fundamental analyses in bioinformatics. The task can be addressed by using biological pathway databases with enrichment analysis (EA). However, textual description of biological entities in public databases is less explored and integrated in existing tools and it has a potential to reveal new mechanisms. Here, we present a new R package biotextgraph for graphical summarization of omics’ textual description data which enables assessment of functional similarities of the lists of biological entities. We illustrate application examples of annotating gene identifiers in addition to EA. The results suggest that the visualization based on words and inspection of biological entities with text can reveal a set of biologically meaningful terms that could not be obtained by using biological pathway databases alone. The results suggest the usefulness of the package in the routine analysis of omics-related data. The package also offers a web-based application for convenient querying.

Availability and implementation
The package, documentation, and web server are available at: https://github.com/noriakis/biotextgraph.
The Sacrificed Children: Listening to the Voices of Former Young Carers Supporting Parents with Mental Illness
Authors: Yuan Esabella Hsiu-Wen , Ku Yeun-Wen 
Published: June 2024

Abstract
Numerous studies have indicated that parents who are affected by mental illness experience emotional/behavioural difficulties which can have major impacts on parenting and the child–parent relationship. However, research on the experiences of young carers living with a mentally ill parent and the adversity they face remains comparatively limited. This article reports findings from a qualitative and retrospective study undertaken with nineteen Taiwanese adults who were young carers of parents with mental illness to capture their entire childhood experiences. The study was guided by social constructionism with the aim to listen to the voices of former young carers and explore their sense of responsibility, their response to family and societal expectations and how these affected their lives. The study finds the young carers’ sense of responsibility was grounded on the principle of filial piety, which greatly influenced young carers not only actively in response to the parent’s needs but also in prioritising the parent’s demands. Participants felt responsibility and sacrifice interwoven in the context of their lives. Implications for social services and policy makers are suggested in order to meet the needs of young carers and their families.
The Social Media, Online and Digital Abuse and Harassment of Social Workers, Probation Officers and Social Work Students in Ireland: A National Survey
Authors: Burns Kenneth , Halvey Olwen , Ó Súilleabháin Fiachra , O’Callaghan Elaine , Coelho Gabriel 
Published: June 2024

Abstract
An estimated five billion people use social media globally. The digital world enables networking and community-building beyond geographical and jurisdictional boundaries, it can facilitate information-sharing and knowledge development, and facilitates speedy access and communications links. On the other hand, digital and social media platforms can also be sources and purveyors of hurt, discrimination, defamation, hatred, abuse, cyberbullying and disinformation. Their increased usage within professional practice has become a nascent area for scholarly debate and research. Our scoping literature search indicated that there are very few studies examining this issue within the profession. This article seeks to address a considerable gap in the research by reporting the findings from an exploratory study in Ireland focusing on social workers, probation officers and social work students. Three hundred seventy-nine participants completed an online survey on their experiences of using social media, with eighty-three (21.9 per cent) participants indicating that they had experienced online and digital abuse and harassment. Facebook, Twitter (now X), and email were the top three sources of abuse and harassment by platform.
Downregulation of the silent potassium channel Kv8.1 increases motor neuron vulnerability in amyotrophic lateral sclerosis
Authors: Huang Xuan , Lee Seungkyu , Chen Kuchuan , Kawaguchi Riki , Wiskow Ole , Ghosh Sulagna , Frost Devlin , Perrault Laura , Pandey Roshan , Klim Joseph R , Boivin Bruno , Hermawan Crystal , Livak Kenneth J , Geschwind Daniel H , Wainger Brian J , Eggan Kevin C , Bean Bruce P , Woolf Clifford J 
Published: June 2024

Abstract
While voltage-gated potassium channels have critical roles in controlling neuronal excitability, they also have non-ion–conducting functions. Kv8.1, encoded by the KCNV1 gene, is a ‘silent’ ion channel subunit whose biological role is complex since Kv8.1 subunits do not form functional homotetramers but assemble with Kv2 to modify its ion channel properties. We profiled changes in ion channel expression in amyotrophic lateral sclerosis patient–derived motor neurons carrying a superoxide dismutase 1(A4V) mutation to identify what drives their hyperexcitability. A major change identified was a substantial reduction of KCNV1/Kv8.1 expression, which was also observed in patient-derived neurons with C9orf72 expansion. We then studied the effect of reducing KCNV1/Kv8.1 expression in healthy motor neurons and found it did not change neuronal firing but increased vulnerability to cell death. A transcriptomic analysis revealed dysregulated metabolism and lipid/protein transport pathways in KCNV1/Kv8.1-deficient motor neurons. The increased neuronal vulnerability produced by the loss of KCNV1/Kv8.1 was rescued by knocking down Kv2.2, suggesting a potential Kv2.2-dependent downstream mechanism in cell death. Our study reveals, therefore, unsuspected and distinct roles of Kv8.1 and Kv2.2 in amyotrophic lateral sclerosis–related neurodegeneration.