bluuebunny/crossref_metadata_2025_split huggingface dataset:
AI, Suicide Prevention and the Limits of Beneficence
Authors: Halsband Aurélie , Heinrichs Bert 
Published: November 2022

AbstractIn this paper, we address the question of whether AI should be used for suicide prevention on social media data. We focus on algorithms that can identify persons with suicidal ideation based on their postings on social media platforms and investigate whether private companies like Facebook are justified in using these. To find out if that is the case, we start with providing two examples for AI-based means of suicide prevention in social media. Subsequently, we frame suicide prevention as an issue of beneficence, develop two fictional cases to explore the scope of the principle of beneficence and apply the lessons learned to Facebook’s employment of AI for suicide prevention. We show that Facebook is neither acting under an obligation of beneficence nor acting meritoriously. This insight leads us to the general question of who is entitled to help. We conclude that private companies like Facebook can play an important role in suicide prevention, if they comply with specific rules which we derive from beneficence and autonomy as core principles of biomedical ethics. At the same time, public bodies have an obligation to create appropriate framework conditions for AI-based tools of suicide prevention. As an outlook we depict how cooperation between public and private institutions can make an important contribution to combating suicide and, in this way, put the principle of beneficence into practice.
A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal
Authors: Santos Pedro Pinto , Zêzere José Luís , Pereira Susana , Rocha Jorge , Tavares Alexandre Oliveira 
Published: November 2022

AbstractSocial vulnerability, as one of the risk components, partially explains the magnitude of the impacts observed after a disaster. In this study, a spatiotemporally comparable assessment of social vulnerability and its drivers was conducted in Portugal, at the civil parish level, for three census frames. The first challenging step consisted of the selection of meaningful and consistent variables over time. Data were normalized using the Adjusted Mazziotta-Pareto Index (AMPI) to obtain comparable adimensional-normalized values. A joint principal component analysis (PCA) was applied, resulting in a robust set of variables, interpretable from the point of view of their self-grouping around vulnerability drivers. A separate PCA for each census was also conducted, which proved to be useful in analyzing changes in the composition and type of drivers, although only the joint PCA allows the monitoring of spatiotemporal changes in social vulnerability scores and drivers from 1991 to 2011. A general improvement in social vulnerability was observed for Portugal. The two main drivers are the economic condition (PC1), and aging and depopulation (PC2). The remaining drivers highlighted are uprooting and internal mobility, and daily commuting. Census data proved their value in the territorial, social, and demographic characterization of the country, to support medium- and long-term disaster risk reduction measures.
Mechanisms for Combined Hypoxic Conditioning and Divergent Exercise Modes to Regulate Inflammation, Body Composition, Appetite, and Blood Glucose Homeostasis in Overweight and Obese Adults: A Narrative Review
Authors: Tee Chris Chow Li , Cooke Matthew B. , Chong Mee Chee , Yeo Wee Kian , Camera Donny M. 
Published: November 2022

AbstractObesity is a major global health issue and a primary risk factor for metabolic-related disorders. While physical inactivity is one of the main contributors to obesity, it is a modifiable risk factor with exercise training as an established non-pharmacological treatment to prevent the onset of metabolic-related disorders, including obesity. Exposure to hypoxia via normobaric hypoxia (simulated altitude via reduced inspired oxygen fraction), termed hypoxic conditioning, in combination with exercise has been increasingly shown in the last decade to enhance blood glucose regulation and decrease the body mass index, providing a feasible strategy to treat obesity. However, there is no current consensus in the literature regarding the optimal combination of exercise variables such as the mode, duration, and intensity of exercise, as well as the level of hypoxia to maximize fat loss and overall body compositional changes with hypoxic conditioning. In this narrative review, we discuss the effects of such diverse exercise and hypoxic variables on the systematic and myocellular mechanisms, along with physiological responses, implicated in the development of obesity. These include markers of appetite regulation and inflammation, body conformational changes, and blood glucose regulation. As such, we consolidate findings from human studies to provide greater clarity for implementing hypoxic conditioning with exercise as a safe, practical, and effective treatment strategy for obesity.
A novel non-linear neuron model based on multiplicative aggregation in quaternionic domain
Authors: Kumar Sushil , Singh Rishitosh Kumar , Chaudhary Aryan 
Published: November 2022

AbstractThe learning algorithm for a three-layered neural structure with novel non-linear quaternionic-valued multiplicative (QVM) neurons is proposed in this paper. The computing capability of non-linear aggregation in the cell body of biological neurons inspired the development of a non-linear neuron model. However, unlike linear neuron models, most non-linear neuron models are built on higher order aggregation, which is more mathematically complex and difficult to train. As a result, building non-linear neuron models with a simple structure is a difficult and time-consuming endeavor in the neurocomputing field. The concept of a QVM neuron model was influenced by the non-linear neuron model, which has a simple structure and the great computational ability. The suggested neuron’s linearity is determined by the weight and bias associated with each quaternionic-valued input. Non-commutative multiplication of all linearly connected quaternionic input-weight terms accommodates the non-linearity. To train three-layered networks with QVM neurons, the standard quaternionic-gradient-based backpropagation (QBP) algorithm is utilized. The computational and generalization capabilities of the QVM neuron are assessed through training and testing in the quaternionic domain utilizing benchmark problems, such as 3D and 4D chaotic time-series predictions, 3D geometrical transformations, and 3D face recognition. The training and testing outcomes are compared to conventional and root-power mean (RPM) neurons in quaternionic domain using training–testing MSEs, network topology (parameters), variance, and AIC as statistical measures. According to these findings, networks with QVM neurons have greater computational and generalization capabilities than networks with conventional and RPM neurons in quaternionic domain.
Bioinspired MXene-Based Soft Actuators Exhibiting Angle-Independent Structural Color
Authors: Xue Pan , Chen Yuanhao , Xu Yiyi , Valenzuela Cristian , Zhang Xuan , Bisoyi Hari Krishna , Yang Xiao , Wang Ling , Xu Xinhua , Li Quan 
Published: November 2022

AbstractIn nature, many living organisms exhibiting unique structural coloration and soft-bodied actuation have inspired scientists to develop advanced structural colored soft actuators toward biomimetic soft robots. However, it is challenging to simultaneously biomimic the angle-independent structural color and shape-morphing capabilities found in the plum-throated cotinga flying bird. Herein, we report biomimetic MXene-based soft actuators with angle-independent structural color that are fabricated through controlled self-assembly of colloidal SiO2 nanoparticles onto highly aligned MXene films followed by vacuum-assisted infiltration of polyvinylidene fluoride into the interstices. The resulting soft actuators are found to exhibit brilliant, angle-independent structural color, as well as ultrafast actuation and recovery speeds (a maximum curvature of 0.52 mm−1 can be achieved within 1.16 s, and a recovery time of ~ 0.24 s) in response to acetone vapor. As proof-of-concept illustrations, structural colored soft actuators are applied to demonstrate a blue gripper-like bird’s claw that can capture the target, artificial green tendrils that can twine around tree branches, and an artificial multicolored butterfly that can flutter its wings upon cyclic exposure to acetone vapor. The strategy is expected to offer new insights into the development of biomimetic multifunctional soft actuators for somatosensory soft robotics and next-generation intelligent machines.
The future of coastal monitoring through satellite remote sensing
Authors: Vitousek Sean , Buscombe Daniel , Vos Kilian , Barnard Patrick L. , Ritchie Andrew C. , Warrick Jonathan A. 
Published: November 2022

AbstractSatellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.
Micro-level network dynamics of scientific collaboration and impact: Relational hyperevent models for the analysis of coauthor networks
Authors: Lerner Jürgen , Hâncean Marian-Gabriel 
Published: November 2022

AbstractWe discuss a recently proposed family of statistical network models—relational hyperevent models (RHEMs)—for analyzing team selection and team performance in scientific coauthor networks. The underlying rationale for using RHEM in studies of coauthor networks is that scientific collaboration is intrinsically polyadic, that is, it typically involves teams of any size. Consequently, RHEM specify publication rates associated with hyperedges representing groups of scientists of any size. Going beyond previous work on RHEM for meeting data, we adapt this model family to settings in which relational hyperevents have a dedicated outcome, such as a scientific paper with a measurable impact (e.g., the received number of citations). Relational outcome can on the one hand be used to specify additional explanatory variables in RHEM since the probability of coauthoring may be influenced, for instance, by prior (shared) success of scientists. On the other hand, relational outcome can also serve as a response variable in models seeking to explain the performance of scientific teams. To tackle the latter, we propose relational hyperevent outcome models that are closely related with RHEM to the point that both model families can specify the likelihood of scientific collaboration—and the expected performance, respectively—with the same set of explanatory variables allowing to assess, for instance, whether variables leading to increased collaboration also tend to increase scientific impact. For illustration, we apply RHEM to empirical coauthor networks comprising more than 350,000 published papers by scientists working in three scientific disciplines. Our models explain scientific collaboration and impact by, among others, individual activity (preferential attachment), shared activity (familiarity), triadic closure, prior individual and shared success, and prior success disparity among the members of hyperedges.
The GLEAMing of the first supermassive black holes: II. A new sample of high-redshift radio galaxy candidates
Authors: Broderick J. W. , Drouart G. , Seymour N. , Galvin T. J. , Wright N. , Carnero Rosell A. , Chhetri R. , Dannerbauer H. , Driver S. P. , Morgan J. S. , Moss V. A. , Prabu S. , Afonso J. M. , De Breuck C. , Emonts B. H. C. , Franzen T. M. O. , Gutiérrez C. M. , Hancock P. J. , Heald G. H. , Hurley-Walker N. , Ivison R. J. , Lehnert M. D. , Noirot G. , Read M. , Shabala S. S. , Stern D. , Sutherland W. J. , Sutorius E. , Turner R. J. , Vernet J. 
Published: November 2022

AbstractWhile unobscured and radio-quiet active galactic nuclei are regularly being found at redshifts$z > 6$, their obscured and radio-loud counterparts remain elusive. We build upon our successful pilot study, presenting a new sample of low-frequency-selected candidate high-redshift radio galaxies (HzRGs) over a sky area 20 times larger. We have refined our selection technique, in which we select sources with curved radio spectra between 72–231 MHz from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey. In combination with the requirements that our GLEAM-selected HzRG candidates have compact radio morphologies and be undetected in near-infrared$K_{\rm s}$-band imaging from the Visible and Infrared Survey Telescope for Astronomy Kilo-degree Infrared Galaxy (VIKING) survey, we find 51 new candidate HzRGs over a sky area of approximately$1200\ \mathrm{deg}^2$. Our sample also includes two sources from the pilot study: the second-most distant radio galaxy currently known, at$z=5.55$, with another source potentially at$z \sim 8$. We present our refined selection technique and analyse the properties of the sample. We model the broadband radio spectra between 74 MHz and 9 GHz by supplementing the GLEAM data with both publicly available data and new observations from the Australia Telescope Compact Array at 5.5 and 9 GHz. In addition, deep$K_{\rm s}$-band imaging from the High-Acuity WidefieldK-band Imager (HAWK-I) on the Very Large Telescope and from the SouthernHerschelAstrophysical Terahertz Large Area Survey Regions$K_{\rm s}$-band Survey (SHARKS) is presented for five sources. We discuss the prospects of finding very distant radio galaxies in our sample, potentially within the epoch of reionisation at$z \gtrsim 6.5$.
Embodiment in distributed information processing: “Solid” plants versus “liquid” ant colonies
Authors: van Schijndel Laura , Snoek Basten L. , ten Tusscher Kirsten 
Published: November 2022

Abstract
Information processing is an essential part of biology, enabling coordination of intra-organismal processes such as development, environmental adaptation and inter-organismal communication. Whilst in animals with specialised brain tissue a substantial amount of information processing occurs in a centralised manner, most biological computing is distributed across multiple entities, such as cells in a tissue, roots in a root system or ants in a colony. Physical context, called embodiment, also affects the nature of biological computing. While plants and ant colonies both perform distributed computing, in plants the units occupy fixed positions while individual ants move around. This distinction, solid versus liquid brain computing, shapes the nature of computations. Here we compare information processing in plants and ant colonies, highlighting how similarities and differences originate in, as well as make use of, the differences in embodiment. We end with a discussion on how this embodiment perspective may inform the debate on plant cognition.
Multispectral satellite imaging improves detection of large individual fossils
Authors: Ghezzo Elena , Massironi Matteo , Davis Edward B. 
Published: November 2022

AbstractPalaeontological field surveys in remote regions are a challenge, because of uncertainty in finding new specimens, high transportation costs, risks for the crew and a long time commitment. The effort can be facilitated by using high-resolution satellite imagery. Here we present a new opportunity to investigate remote fossil localities in detail, mapping the optical signature of individual fossils. We explain a practical workflow for detecting fossils using remote-sensing platforms and cluster algorithms. We tested the method within the Petrified Forest National Park, where fossil logs are sparse in a large area with mixed lithologies. We ran both unsupervised and supervised classifications, obtaining the best estimations for the presence of fossil logs using the likelihood and spectral angle mapper algorithms. We recognized general constraints and described logical and physical pros and cons of each estimated map. We also explained how the outcomes should be critically evaluated with consistent accuracy tests. Instead of searching for fossiliferous outcrops, our method targets single fossil specimens (or highly condensed accumulations), obtaining a significant increase in potential efficiency and effectiveness of field surveys. When repeatedly applied to the same region over time, it could also be useful for monitoring palaeontological heritage localities. Most importantly, the method here described is feasible, easily applicable to both fossil logs and bones, and represents a step towards standard best practices for applying remote sensing in the palaeontological field.
Central Counterparty Default Waterfalls and Systemic Loss
Authors: Ghamami Samim , Paddrik Mark , Zhang Simpson 
Published: November 2022

AbstractCentral counterparty (CCP) default waterfalls act as the last lines of defense in over-the-counter markets by managing and allocating resources to cover payment defaults. This article examines the impact of variations in waterfall design on financial system losses in the presence of payment network dependencies and frictions in the cleared and noncleared portion of the system. Through the development of a structural model, we draw several theoretical conclusions about the effectiveness of CCP default waterfalls under severe payment stress. These findings are empirically quantified by testing the model using supervisory data for the U.S. credit default swap market.
Imperial inheritance: The transnational lives of Gurkha families in Asian contexts, 1948–1971
Authors: Kiruppalini Hema 
Published: November 2022

AbstractWhile there is burgeoning scholarship on the transnational lives of Nepali Gurkhas and their families, research on their migration history and lived experiences in Asian contexts is few and far between. Building upon Vron Ware’s concept of Gurkha families as ‘military migrants’ and using an inter-Asia approach as a framework, this article foregrounds the interconnections between military service and migrant pathways during the period of decolonization, particularly in Southeast Asia, and in so doing, offers a gendered perspective on labour migration. Drawing on multi-sited archival and ethnographic research, it seeks to argue that from 1948 to 1971, the Asian region(s) were a dominant feature in the global migration process of Gurkha families who circulated within the arc of a declining British empire. The article further advances that their gendered mobility patterns problematizes the ‘migration–left behind’ nexus as binary opposites as Gurkha wives and children engaged with mobility and mediated their transnational lives in complex ways. It also expands upon the notion of dukha—meaning ‘sadness’ or ‘suffering’ in Nepali—as an analytical theme to yield further insights into their lived experiences and to revisit colonial historiography about Gurkha society.
Rural electrification in Spain: territorial expansion and effects on the agricultural sector (c. 1900–c. 2000)
Authors: Garrués-Irurzun Josean , Iriarte-Goñi Iñaki 
Published: November 2022

AbstractRural electrification is closely linked one way or another to rural development, and enables the understanding of the complexity of social and economic development paths. The objective of this work is to analyse rural electrification in a European peripherical country like Spain throughout the twentieth century, contributing to the international debate on the issue. The article studies the territorial expansion of electricity in the Spanish countryside, tracing different phases and explaining the delay in the construction of a national network. It also analyses the relationship that arose in the long term between electrification and the evolution of the agricultural sector. The article concludes that, in the Spanish case, rural electrification played a modest role in agricultural change until the 1980s and was, to a great extent, the consequence, rather than the cause, of the modernisation of the sector to these years.
Sensing, Sharing, and Listening to Musicking Animals across the Sonic Environments of Social Media
Authors: GALLOWAY KATE 
Published: November 2022

AbstractThis article explores the strategies employed by user-creators as they listen to, sense, make, and share digital audiovisual memes of musicking non-human animals on social media. Memes, reels, and other forms of audiovisual social media posts are a form of cultural expression that reveals the varied ways humans relate to, connect with, and represent non-human animals – especially their pets – through sound, music, and the moving image. By listening to the plurality of musicking animals circulating on social media platforms and networks, I argue that user-creators conspicuously use music and performance to express alternative ideas of what it means to be musical, to feel closer to and connect with the important animals in their lives, and to explore the ways they can represent non-human animals using sound and music to explore musical concepts. Using a varied selection of viral musicking animal memes shared across social media platforms such as TikTok, Instagram, and Twitter, I frame musicking animal participatory media as a creative space for exploring different approaches to listening, performing with, and scoring sound and music to the behaviour, movement, and acoustic communication of the non-human animal. Non-human animal musicking takes a variety of forms across this particular kind of participatory media making by online user-creators.