bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fixed point approximation for a class of generalized nonexpansive multi-valued mappings in Banach spaces
Authors: Hussain Nawab , Alamri Hind , Alsulami Saud 
Published: October 2022

AbstractIn this paper, we propose a new iteration process, called multi-valued F-iteration process, for the approximation of fixed points. We introduce a new class of multi-valued generalized nonexpansive mappings satisfying a $$B_{\gamma ,\mu }$$

B

γ
,
μ

property. Moreover, we establish certain weak and strong convergence theorems in uniformly convex Banach spaces. We also discuss the stability of the modified F-iteration process. Furthermore, a numerical example is presented to illustrate the superiority of our results.
Attribute dependency graphs: modelling cause and effect in systems design
Authors: Rötzer Sebastian , Schweigert-Recksiek Sebastian , Thoma Dominik , Zimmermann Markus 
Published: October 2022

Abstract
Complexity in product design increases with little understanding of cause and effect. As a consequence, the impact of design decisions (or changes) on the product is difficult to predict and control. This article presents a model of cause and effect for design decisions that avoid circular dependencies: the so-called attribute dependency graph (ADG) models complex system behaviour and properties, and increases transparency by carefully distinguishing between what is realised and what is required. An ADG is a polyhierarchy, with design variables (directly controllable) at the bottom, quantities of interest (not directly controllable) on the top, and intermediate attributes. The dependencies represent causality in a simple sense: assigning values to design variables, representing the cause, will determine the values of the dependent attributes, representing the effect. ADGs do not account for what is required, but for what effects emerge by design activity. A set of rules makes them independent of designers’ views. They provide the structure for so-called INUS conditions, that is, insufficient but necessary parts of unnecessary but sufficient conditions that can be used for requirement development. The modelling approach is applied to one simple synthetic and then to two real-world design problems, the design of a water hose box and a passenger vehicle.
J. R. Seeley in Japan, 1880s–1940s
Authors: Furuta Takuya 
Published: October 2022

AbstractThis article explores how the late nineteenth-century British historian J. R. Seeley was ‘used’ in Japan. The focal points are three translations of his The expansion of England, published in 1899, 1918, and 1942. By placing each translation in context, I attempt to clarify the ideological moves made by those who produced the translations. In the context of the first translation, Seeley was a historian who offered a vision of Japan's future. In the second context, however, he became a lens through which present-day British policy could be understood. In the third context, he became an unintentional detractor of Britain's past colonial policies in India. Through a comparative examination of these three translations, this article uncovers both the ‘potential’ of Seeley's imperial history, which anglophone reception of his work had not exhausted, and the ‘creative’ aspect of translation, thus contributing to intellectual history on both the local and global levels.
Machine learning in requirements elicitation: a literature review
Authors: Cheligeer Cheligeer , Huang Jingwei , Wu Guosong , Bhuiyan Nadia , Xu Yuan , Zeng Yong 
Published: October 2022

Abstract
A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords derived from these research questions led to 975 records initially retrieved from 7 scientific search engines. Finally, 86 articles were selected for inclusion in the review. As the primary research finding, we identified 15 ML-based requirement elicitation tasks and classified them into four categories. Twelve different data sources for building a data-driven model are identified and classified in this literature review. In addition, we categorized the techniques for constructing ML-based requirement elicitation methods into five parts, which are Data Cleansing and Preprocessing, Textual Feature Extraction, Learning, Evaluation, and Tools. More specifically, 3 categories of preprocessing methods, 3 different feature extraction strategies, 12 different families of learning methods, 2 different evaluation strategies, and various off-the-shelf publicly available tools were identified. Furthermore, we discussed the limitations of the current studies and proposed eight potential directions for future research.
Adequacy of sexual care information given to prostate cancer patients receiving radical external beam radiotherapy
Authors: Greenwood-Wilson Sam , Bridge Pete 
Published: October 2022

Abstract

Background:
Despite the acknowledged value of providing prostate radiotherapy patients with sexual dysfunction (SD) information, there is little evidence related to patient perceptions of this or the extent to which information is provided to them. This study aimed to critically evaluate the quality and format of SD information given to patients before, during and after radical EBRT to treat prostate cancer.

Method:
Members of UK prostate cancer support groups were asked to complete an anonymous online survey tool seeking opinions of the SD information they were given before, during and after external beam radiotherapy (EBRT).

Results:
There were 56 responses to the survey with over 42% of respondents reporting that they had not received any SD information. Of those who did, 78·1% (25/32) received information before the start of EBRT. Physicians were the most involved in the provision of SD information, with nurses and therapeutic radiographers being underutilised. Responses were mostly negative, or neutral regarding the quality of SD information and the information received about impact on relationships, psychological and emotional health. Many participants wanted more information and support.

Conclusion:
This study demonstrates that prostate cancer patients who have undergone radical EBRT have not received adequate information relating to potential sexual function side effects and the psychological and emotional effects of SD. This information should be included in verbal and written information provided at all stages of the radiotherapy pathway.
A Complex Mantle Plume Head Below East Africa‐Arabia Shaped by the Lithosphere‐Asthenosphere Boundary Topography
Authors: Civiero Chiara , Lebedev Sergei , Celli Nicolas L. 
Published: October 2022

AbstractHot plumes rising from Earth's deep mantle are thought to cause uplift, rifting and large igneous province (LIP) emplacement. LIP volcanism in continents often spans tens of Ma and scatters unevenly over broad areas. This has been attributed to lateral flow of hot plume material, but observational evidence on such flow is scarce. New waveform tomography with massive data sets reveals detailed seismic velocity structure beneath the East Africa‐Arabia region, where these processes occur at present. It shows interconnected sub‐lithospheric corridors of hot, partially molten rock, fed by three mantle upwellings beneath Kenya, Afar, and Levant. The spatio‐temporal distribution of the volcanism suggests that we are witnessing an integral plume head, which morphed into a three‐pointed star by ponding and channeling within thin‐lithosphere corridors. Plate reconstructions indicate that it spread south‐to‐north since ∼45 Ma. These results suggest that complex‐shape plume heads can explain the enigmatic, scattered LIP volcanism and are, probably, an inherent feature of plume‐continent interaction.
Eikonal Tomography With Physics‐Informed Neural Networks: Rayleigh Wave Phase Velocity in the Northeastern Margin of the Tibetan Plateau
Authors: Chen Yunpeng , de Ridder Sjoerd A. L. , Rost Sebastian , Guo Zhen , Wu Xiaoyang , Chen Yongshun 
Published: October 2022

AbstractWe present a novel eikonal tomography approach using physics‐informed neural networks (PINNs) for Rayleigh wave phase velocities based on the eikonal equation. The PINN eikonal tomography (pinnET) neural network utilizes deep neural networks as universal function approximators and extracts traveltimes and velocities of the medium during the optimization process. Whereas classical eikonal tomography uses a generic non‐physics based interpolation and regularization step to reconstruct traveltime surfaces, optimizing the network parameters in pinnET means solving a physics constrained traveltime surface reconstruction inversion tackling measurement noise and satisfying physics. We demonstrate this approach by applying it to 25 s surface wave data from ChinArray II sampling the northeastern Tibetan plateau. We validate our results by comparing them to results from conventional eikonal tomography in the same area and find good agreement.
The Impact of Plate Motions on Long‐Wavelength InSAR‐Derived Velocity Fields
Authors: Stephenson Oliver L. , Liu Yuan‐Kai , Yunjun Zhang , Simons Mark , Rosen Paul , Xu Xiaohua 
Published: October 2022

AbstractInterferometric Synthetic Aperture Radar (InSAR) measurements are increasingly being used to measure small amplitude tectonic deformations over large spatial scales. Residual signals are often present at these scales and are interpreted to be noise of indeterminate origin, limiting studies of long‐wavelength deformation. Here, we demonstrate the impact of rigid motion by the Earth's tectonic plates on velocity fields derived from InSAR. The range‐dependent incidence angle of the InSAR observations, coupled with plate velocities of centimeters per year, can induce long‐wavelength spatial gradients of millimeters per year over hundreds of kilometers in InSAR velocity fields. We show that, after applying corrections, including for the ionosphere and troposphere, plate motion represents the dominant source of long‐wavelength secular velocity gradients in multi‐year time series for several study areas. This signal can be accounted for using plate motion models, allowing improved detection of regional tectonic strain at continental scales.
Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization
Authors: Zhang Xitong , Reichard‐Flynn Will , Zhang Miao , Hirn Matthew , Lin Youzuo 
Published: October 2022

AbstractAccurate earthquake location and magnitude estimation play critical roles in seismology. Recent deep learning frameworks have produced encouraging results on various seismological tasks (e.g., earthquake detection, phase picking, seismic classification, and earthquake early warning). Many existing machine learning earthquake location methods utilize waveform information from a single station. However, multiple stations contain more complete information for earthquake source characterization. Inspired by recent successes in applying graph neural networks (GNNs) in graph‐structured data, we develop a Spatiotemporal Graph Neural Network (STGNN) for estimating earthquake locations and magnitudes. Our graph neural network leverages geographical and waveform information from multiple stations to construct graphs automatically and dynamically by adaptive message passing based on graphs' edges. Using a recent graph neural network and a fully convolutional neural network as baselines, we apply STGNN to earthquakes recorded by the Southern California Seismic Network from 2000 to 2019 and earthquakes collected in Oklahoma from 2014 to 2015. STGNN yields more accurate earthquake locations than those obtained by the baseline models and performs comparably in terms of depth and magnitude prediction, though the ability to predict depth and magnitude remains weak for all tested models. Our work demonstrates the potential of using GNNs and multiple stations for better automatic estimation of earthquake epicenters.
The oncoprotein MUC1 facilitates breast cancer progression by promoting Pink1-dependent mitophagy via ATAD3A destabilization
Authors: Li Quanfu , Chu Yunkai , Li Shengze , Yu Liping , Deng Huayun , Liao Chunhua , Liao Xiaodong , Yang Chihyu , Qi Min , Cheng Jinke , Chen Guoqiang , Huang Lei 
Published: October 2022

AbstractMitophagy is a vital process that controls mitochondria quality, dysregulation of which can promote cancer. Oncoprotein mucin 1 (MUC1) targets mitochondria to attenuate drug-induced apoptosis. However, little is known about whether and how MUC1 contributes to mitochondrial homeostasis in cancer cells. We identified a novel role of MUC1 in promoting mitophagy. Increased mitophagy is coupled with the translocation of MUC1 to mitochondria, where MUC1 interacts with and induces degradation of ATPase family AAA domain-containing 3A (ATAD3A), resulting in protection of PTEN-induced kinase 1 (Pink1) from ATAD3A-mediated cleavage. Interestingly, MUC1-induced mitophagy is associated with increased oncogenicity of cancer cells. Similarly, inhibition of mitophagy significantly suppresses MUC1-induced cancer cell activity in vitro and in vivo. Consistently, MUC1 and ATAD3A protein levels present an inverse relationship in tumor tissues of breast cancer patients. Our data validate that MUC1/ATAD3A/Pink1 axis-mediated mitophagy constitutes a novel mechanism for maintaining the malignancy of cancer cells, providing a novel therapeutic approach for MUC1-positive cancers.
Drivers of global mangrove loss and gain in social-ecological systems
Authors: Hagger Valerie , Worthington Thomas A. , Lovelock Catherine E. , Adame Maria Fernanda , Amano Tatsuya , Brown Benjamin M. , Friess Daniel A. , Landis Emily , Mumby Peter J. , Morrison Tiffany H. , O’Brien Katherine R. , Wilson Kerrie A. , Zganjar Chris , Saunders Megan I. 
Published: October 2022

AbstractMangrove forests store high amounts of carbon, protect communities from storms, and support fisheries. Mangroves exist in complex social-ecological systems, hence identifying socioeconomic conditions associated with decreasing losses and increasing gains remains challenging albeit important. The impact of national governance and conservation policies on mangrove conservation at the landscape-scale has not been assessed to date, nor have the interactions with local economic pressures and biophysical drivers. Here, we assess the relationship between socioeconomic and biophysical variables and mangrove change across coastal geomorphic units worldwide from 1996 to 2016. Globally, we find that drivers of loss can also be drivers of gain, and that drivers have changed over 20 years. The association with economic growth appears to have reversed, shifting from negatively impacting mangroves in the first decade to enabling mangrove expansion in the second decade. Importantly, we find that community forestry is promoting mangrove expansion, whereas conversion to agriculture and aquaculture, often occurring in protected areas, results in high loss. Sustainable development, community forestry, and co-management of protected areas are promising strategies to reverse mangrove losses, increasing the capacity of mangroves to support human-livelihoods and combat climate change.
Feature-based volumetric defect classification in metal additive manufacturing
Authors: Poudel Arun , Yasin Mohammad Salman , Ye Jiafeng , Liu Jia , Vinel Aleksandr , Shao Shuai , Shamsaei Nima 
Published: October 2022

AbstractVolumetric defect types commonly observed in the additively manufactured parts differ in their morphologies ascribed to their formation mechanisms. Using high-resolution X-ray computed tomography, this study analyzes the morphological features of volumetric defects, and their statistical distribution, in laser powder bed fused Ti-6Al-4V. The geometries of three common types of volumetric defects; i.e., lack of fusions, gas-entrapped pores, and keyholes, are quantified by nine parameters including maximum dimension, roundness, sparseness, aspect ratio, and more. It is shown that the three defect types share overlaps of different degrees in the ranges of their morphological parameters; thus, employing only one or two parameters cannot uniquely determine a defect’s type. To overcome this challenge, a defect classification methodology incorporating multiple morphological parameters has been proposed. In this work, by employing the most discriminating parameters, this methodology has been shown effective when implemented into decision tree (>98% accuracy) and artificial neural network (>99% accuracy).
A robot-assisted acoustofluidic end effector
Authors: Durrer Jan , Agrawal Prajwal , Ozgul Ali , Neuhauss Stephan C. F. , Nama Nitesh , Ahmed Daniel 
Published: October 2022

AbstractLiquid manipulation is the foundation of most laboratory processes. For macroscale liquid handling, both do-it-yourself and commercial robotic systems are available; however, for microscale, reagents are expensive and sample preparation is difficult. Over the last decade, lab-on-a-chip (LOC) systems have come to serve for microscale liquid manipulation; however, lacking automation and multi-functionality. Despite their potential synergies, each has grown separately and no suitable interface yet exists to link macro-level robotics with micro-level LOC or microfluidic devices. Here, we present a robot-assisted acoustofluidic end effector (RAEE) system, comprising a robotic arm and an acoustofluidic end effector, that combines robotics and microfluidic functionalities. We further carried out fluid pumping, particle and zebrafish embryo trapping, and mobile mixing of complex viscous liquids. Finally, we pre-programmed the RAEE to perform automated mixing of viscous liquids in well plates, illustrating its versatility for the automatic execution of chemical processes.
The co-evolution of the genome and epigenome in colorectal cancer
Authors: Heide Timon , Househam Jacob , Cresswell George D. , Spiteri Inmaculada , Lynn Claire , Mossner Maximilian , Kimberley Chris , Fernandez-Mateos Javier , Chen Bingjie , Zapata Luis , James Chela , Barozzi Iros , Chkhaidze Ketevan , Nichol Daniel , Gunasri Vinaya , Berner Alison , Schmidt Melissa , Lakatos Eszter , Baker Ann-Marie , Costa Helena , Mitchinson Miriam , Piazza Rocco , Jansen Marnix , Caravagna Giulio , Ramazzotti Daniele , Shibata Darryl , Bridgewater John , Rodriguez-Justo Manuel , Magnani Luca , Graham Trevor A. , Sottoriva Andrea 
Published: October 2022

AbstractColorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4–7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.
Neoadjuvant relatlimab and nivolumab in resectable melanoma
Authors: Amaria Rodabe N. , Postow Michael , Burton Elizabeth M. , Tetzlaff Michael T. , Ross Merrick I. , Torres-Cabala Carlos , Glitza Isabella C. , Duan Fei , Milton Denái R. , Busam Klaus , Simpson Lauren , McQuade Jennifer L. , Wong Michael K. , Gershenwald Jeffrey E. , Lee Jeffrey E. , Goepfert Ryan P. , Keung Emily Z. , Fisher Sarah B. , Betof-Warner Allison , Shoushtari Alexander N. , Callahan Margaret , Coit Daniel , Bartlett Edmund K. , Bello Danielle , Momtaz Parisa , Nicholas Courtney , Gu Aidi , Zhang Xuejun , Korivi Brinda Rao , Patnana Madhavi , Patel Sapna P. , Diab Adi , Lucci Anthony , Prieto Victor G. , Davies Michael A. , Allison James P. , Sharma Padmanee , Wargo Jennifer A. , Ariyan Charlotte , Tawbi Hussein A. 
Published: October 2022

AbstractRelatlimab and nivolumab combination immunotherapy improves progression-free survival over nivolumab monotherapy in patients with unresectable advanced melanoma1. We investigated this regimen in patients with resectable clinical stage III or oligometastatic stage IV melanoma (NCT02519322). Patients received two neoadjuvant doses (nivolumab 480 mg and relatlimab 160 mg intravenously every 4 weeks) followed by surgery, and then ten doses of adjuvant combination therapy. The primary end point was pathologic complete response (pCR) rate2. The combination resulted in 57% pCR rate and 70% overall pathologic response rate among 30 patients treated. The radiographic response rate using Response Evaluation Criteria in Solid Tumors 1.1 was 57%. No grade 3–4 immune-related adverse events were observed in the neoadjuvant setting. The 1- and 2-year recurrence-free survival rate was 100% and 92% for patients with any pathologic response, compared to 88% and 55% for patients who did not have a pathologic response (P = 0.005). Increased immune cell infiltration at baseline, and decrease in M2 macrophages during treatment, were associated with pathologic response. Our results indicate that neoadjuvant relatlimab and nivolumab induces a high pCR rate. Safety during neoadjuvant therapy is favourable compared to other combination immunotherapy regimens. These data, in combination with the results of the RELATIVITY-047 trial1, provide further confirmation of the efficacy and safety of this new immunotherapy regimen.
Computerised prediction of healing for venous leg ulcers
Authors: Ngo Quoc Cuong , Ogrin Rajna , Kumar Dinesh Kant 
Published: October 2022

AbstractEarly prediction of delayed healing for venous leg ulcers could improve management outcomes by enabling earlier initiation of adjuvant therapies. In this paper, we propose a framework for computerised prediction of healing for venous leg ulcers assessed in home settings using thermal images of the 0 week. Wound data of 56 older participants over 12 weeks were used for the study. Thermal images of the wounds were collected in their homes and labelled as healed or unhealed at the 12th week follow up. Textural information of the thermal images at week 0 was extracted. Thermal images of unhealed wounds had a higher variation of grey tones distribution. We demonstrated that the first three principal components of the textural features from one timepoint can be used as an input to a Bayesian neural network to discriminate between healed and unhealed wounds. Using the optimal Bayesian neural network, the classification results showed 78.57% sensitivity and 60.00% specificity. This non-contact method, incorporating machine learning, can provide a computerised prediction of this delay in the first assessment (week 0) in participants’ homes compared to the current method that is able to do this in 3rd week and requires contact digital planimetry.