bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perspectives of the role of ICRP and the system of protection in meeting the United Nations sustainable development goals
Authors: Bryant Peter A , Clement Chris , Chapple Claire Louise , Martinez Nicole , Lips Marcel , Dowds Christiana 
Published: September 2024

Abstract
Established in 2015 the United Nations (UN) sustainable development goals (SDGs) were agreed with the aim to balance the need to address social and ethical obligations such as ending poverty and other deprivations, while tackling climate change and the other planetary boundaries. In 2018 the International Commission on Radiological Protection (ICRP) initiated a review and revision of the System of Radiological Protection which will lay the foundation for Radiation Protection standards, regulations, guidance and practice worldwide for the next 40 years. Recognising the importance of the UN SDG’s the ICRP has started to consider what the role of the revised system of protection should be in enabling delivery. On the 15 May 2024 the Society for Radiological Protection and World Nuclear Association ran a workshop exploring the intersection of the System of Radiological Protection and the SDG’s. The outputs of the workshop are summarised in this paper showing the views from a variety of practitioners working across the radiation protection sectors on the key factors to be considered in the revision of the system of radiological protection to enable delivery of the UN SDG’s.
Image compression encryption algorithm combining two-dimensional modular hyperchaotic map and compressed sensing
Authors: Yin Hai , Xu Yuliang , Zhang Yongkang , Wu Jianhua 
Published: September 2024

Abstract
Recently, to offer better ensure for image privacy security, numerous new image encryption algorithms have been proposed. However, these algorithms still suffer from the problems of chaotic performance scarcity, low encryption effect, and high consumption of computational resources. To solve the above issues, we first construct a two-dimensional modular hyperchaotic map (2D-MHM). Then, we further develop an image encryption algorithm based on 2D-MHM and compressed sensing (CS). Several chaotic metrics verify the randomness and validity of 2D-MHM. These metrics include bifurcation diagram, Lyapunov exponent, initial value sensitivity, 0–1 test, and NIST test. Specifically, CS significantly reduces the ciphertext image size thereby reducing its resource consumption during transmission. Reality-preserving fractional DCT (RP-Fdct) diffusion is utilized to transform pixels into the frequency domain to enhance the encryption effect. Subsequently, lightweight index confusion and XOR diffusion further improve the algorithm security. The security of the algorithm is verified through various experiments. It is able to encrypt grayscale and color images of different sizes with good results. Notably, this algorithm also implements the encryption requirements for binary images. Due to our designs, it outperforms recently reported encryption algorithms in several areas, especially in reconstruction performance.
Ordering kinetics with long-range interactions: interpolating between voter and Ising models
Authors: Corberi Federico , dello Russo Salvatore , Smaldone Luca 
Published: September 2024

Abstract
We study the ordering kinetics of a generalization of the voter model with long-range interactions, the p-voter model, in one dimension. It is defined in terms of Boolean variables S

i
, agents or spins, located on sites i of a lattice, each of which takes in an elementary move the state of the majority of p other agents at distances r chosen with probability

P
(
r
)
∝

r

−
α

. For p = 2 the model can be exactly mapped onto the case with p = 1, which amounts to the voter model with long-range interactions decaying algebraically. For

3
⩽
p
<
∞

, instead, the dynamics falls into the universality class of the one-dimensional Ising model with long-ranged coupling constant

J
(
r
)
=
P
(
r
)

quenched to small finite temperatures. In the limit

p
→
∞

, a crossover to the (different) behavior of the long-range Ising model quenched to zero temperature is observed. Since for p > 3 a closed set of differential equations cannot be found, we employed numerical simulations to address this case.
Bioengineered larynx and vocal folds: where are we today? A review
Authors: Kaboodkhani Reza , Moghaddam Armaghan , Mehrabani Davood , Khonakdar Hossein Ali 
Published: September 2024

Abstract
The larynx is responsible for breathing, producing sound, and protecting the trachea against food aspiration through the cough reflex. Nowadays, scaffolding surgery has made it easier to regenerate damaged tissues by facilitating the influx of cells and growth factors. This review provides a comprehensive overview of the current knowledge on tissue engineering of the larynx and vocal folds. It also discusses the achievements and challenges of data sources. In conducting a literature search for relevant papers, we included 68 studies from January 2000 to November 2023, sourced from PubMed and Scholar Google databases. We found a need for collaboration between voice care practitioners, voice scientists, bioengineers, chemists, and biotechnologists to develop safe and clinically valid solutions for patients with laryngeal and vocal fold injuries. It is crucial for patients to be knowledgeable about the available choices of laryngeal tissue engineering for successful tissue repair. Although few human trials have been conducted, future works should build upon previously completed in-vivo studies in an effort to move towards more human models.
Flammable futures—storylines of climatic impacts on wildfire events and palm oil plantations in Indonesia
Authors: Corning Shelby N , Boere Esther , Krasovskiy Andrey , Lessa Derci Augustynczik Andrey , Shepherd Ted , Ghosh Rohit , Kraxner Florian , Havlík Peter 
Published: September 2024

Abstract
Wildfire events are driven by complex interactions of climate and anthropogenic interventions. Predictions of future wildfire events, their extremity, and their impact on the environment and economy must account for the interactions between these drivers. Economic policy and land use decisions influence the susceptibility of an area to climate extremes, the probability of burning, and future decision making. To better understand how climate-driven drought events and adaptation efforts affect burned area, agricultural production losses, and land use decisions, we developed a storyline approach centered on Indonesia’s 2015 fire events, which saw significant (>5%) production losses of palm oil. We explored analogous events under three warming conditions and two storylines (multi-model ensemble mean climate change and high impact). We employed a model chain consisting of CMIP6 climate modeling to quantify climate change impacts, a wildfire climate impacts and adaptation model (FLAM) to predict burned areas, and the Global biosphere management model (GLOBIOM) to predict the resultant production losses and socio-economic consequences in the oil palm sector in Indonesia and, by extension, the EU. FLAM is a mechanistic, modular fire model used to reproduce and project wildfires based on various scenario criteria and input variables, whereas GLOBIOM is a global economic land use model, which assesses competition for land use and provides economic impacts based on scenario data. We found that total burned area and production loss can increase by up to 25% and lead to local price increases up to 70%, with only minor differences beyond 2.5 degrees of warming. Our results highlight the importance of considering the interactions of future warming, drought conditions, and extreme weather events when predicting their impacts on oil palm losses and burned area. This study sets the stage for further exploration on the impacts of land management policies on local and international environments and economies in the context of global warming.
Visualisation of surface coating distribution patterns on modified CaCO3
Authors: He Yi , Li Junhao , Zhou Juying , Zhao Yanzhi , Lu Jianfang , Qi Wen , Yang Aimei , Zhu Yong 
Published: September 2024

Abstract
In this work, the surface modification of calcite-type calcium carbonate using the anionic surfactant sodium stearate was studied. The optimal amount of surfactant and its distribution on the surface of calcium carbonate is of great significance to the actual production. Various techniques were used to characterize these important parameters such as Fourier-transform infrared spectroscopy (FTIR), water contact angle measurements, Raman Mapping visualizationimaging, Raman depth profiling, thermogravimetric analysis (TGA), and atomic force microscopy (AFM). The results of the Fourier Transform Infrared (FTIR) suggest the formation of a coating on the surface of the modified calcium carbonate. Water contact angle measurements, Raman Mapping visualizationimaging, and TGA indicate that the optimal initial dosage of sodium stearate required to form a monolayer coating is about 2 wt%. Here, the hydrophilic heads of the sodium stearate are arranged vertically on the calcium carbonate surface forming the monolayer. As the concentration of sodium stearate increases, the hydrophobic tails of the sodium stearate or calcium stearate connect each other, forming bilayer or multilayer coatings. Furthermore, the surface coating on calcium carbonate originates from the edge vertices and gradually spreads towards the central region as the amount of sodium stearate increases until complete coverage is achieved. Raman depth profiling and AFM visualization results suggest that the thickness of the monolayer coating is approximately 5.25 nm.
Yttrium iron garnet single-crystal particles—a simple and effective synthesis
Authors: Schabikowski M , Laskowska M , Pastukh O , Swiec P , Pawlik K , Pawlik P , Karczmarska A , Kac M , Zielinski P M , Laskowski L 
Published: September 2024

Abstract
Yttrium iron garnet (YIG) is a ferrimagnetic material which found applications in magnetics, electronics and optics. For those applications, a monocrystalline structure is often required. Although effective methods to grow large YIG single crystals exist, fabricating such structures in a powder form can be challenging. Here, we show a simple procedure to obtain large quantities of monocrystalline Y3Fe5O12 particles based on the precipitation synthesis. The average size of the single crystals was evaluated to be 149(6) nm. The morphology of the particles was analysed using SEM, TEM, DLS and nitrogen adsorption techniques. The material was tested for its structural properties with the use of XRD and electron diffraction methods. The chemical composition was investigated using FTIR, EDS and Raman spectroscopy. Finally, the thermal characteristics were analysed using TGA, while magnetic properties were tested with the use of the SQUID magnetometry. The obtained results are in good agreement with the theoretical values.
Development of electrode and electrolyte materials for solid-state batteries based on Li1.3Al0.3Ti1.7(PO4)3
Authors: Lisovskyi I , Barsukov V , Solopan S , Belous A , Khomenko V , Stryzhakova N , Maletin Y 
Published: September 2024

Abstract
The dependence of the electrochemical characteristics of a layered cathode material containing LiNi0.5Mn0.3Co0.2O2 on the method for applying a protective layer of nanoparticles of the lithium-conducting material Li1.3Al0.3Ti1.7(PO4)3 with a NASICON structure to its surface has been studied. The surface modification has been found to improve the capacity retention in prolonged charge/discharge cycling (up to 15%) and to allow fast charge/discharge processes. The possibility of using a composite electrolyte consisting of a porous ceramic matrix of aluminum-substituted lithium titanium phosphate Li1.3Al0.3Ti1.7(PO4)3 with a transition layer of liquid electrolyte LP-71 has been shown. The use of a thick composite solid electrolyte results in a slight reduction (∼5–7 mAh g−1) in initial capacity compared to laboratory cells with the widely used Celgard 2400 separator impregnated with liquid electrolyte. Laboratory cells assembled with a composite electrolyte showed higher stability during charge/discharge cycling: after 80 deep charge/discharge cycles, the capacity reduction was ∼12% for cells with a composite electrolyte, while for the reference cell it was ∼23%.
Focus on wildfires: impacts on health in the context of climate change
Authors: Reid Colleen E 
Published: September 2024

Abstract
Wildfires are becoming increasingly common in many parts of the world due to a variety of factors including historical fire suppression, increasing drought influenced by climate change, and increasing ignitions from humans. In these regions, wildfire smoke is becoming an increasing source of air pollution people are breathing. Wildfire smoke has been shown to affect numerous physical health outcomes, with clear evidence of impacts on respiratory health but less consistent and comprehensive evidence for effects on cardiovascular disease, mortality, birth outcomes and more. There is a need for more research into which populations are most affected by wildfire smoke; these populations could be affected by where they live and work and how much they are able to protect themselves. Public health interventions that are promoted, such as staying indoors, and using personal air cleaners and masks, may not be equally accessible to all individuals. Additionally, there needs to be research into how best to communicate public health guidance so that it reaches targeted populations. Health impacts from wildfires can also go beyond smoke impacts to include economic and social challenges during recovery when one’s home is lost to on-the-job dangers from wildland firefighters. Articles in this focus issue document scientific studies that address some of these topics.
Is Universal Consciousness Fit for Ground?
Authors: Albahari Miri 
Published: September 2024

Abstract
The Perennial Philosophy centres around what is said to be a recurring mystical insight: that our inherent nature is actually pure, unconditioned consciousness, identical to the ground of all being. Perennial Idealism, the name the author gives to a metaphysical system she has been building, extrapolates from the Perennial Philosophy to explain how the world could be configured if it were in fact true. Among the most serious challenges faced is that of articulating and defending the very notion that our world is grounded in universal consciousness. This chapter further develops a line of reply to what the author thinks are four major objections to the idea that universal consciousness grounds all being. The author calls these the Thales Objection, the Problem of the One and the Many, the Self-defeating Objection, and the Power Challenge.
Idealism and the Interface Theory
Authors: Lee Geoffrey 
Published: September 2024

Abstract
The chapter argues that there is a non-standard but theoretically important notion of “veridicality,” on which perception is only veridical if it does not scramble the objective physical structure of the environment. It argues that non-veridicality in this sense is compatible with veridicality in more familiar senses, and motivates the importance of the notion. For example, a certain kind of realism about the scientific enterprise (that it can uncover nature’s natural joints), requires that perception is veridical in this sense. The chapter suggests that the best reconstruction of Hoffman, Singh and Prakah’s “Interface Theory” is as the view that perception is non-veridical in this non-standard sense—a view that is reasonably understood as a kind of transcendental idealism, because it makes the objective structure of the world unknowable to us. They offer debunking arguments against perceptual veridicality (in this special sense). The chapter responds to these arguments, and sketches a realist alternative.
Inner Acquaintance Theories of Consciousness
Authors: Giustina Anna 
Published: September 2024

Abstract
Most philosophical theories of consciousness account for it in terms of representation, the bulk of the debate revolving around whether (suitably) representing something is sufficient for consciousness (as per first-order representationalism) or some further (meta-)representation is needed (as per higher-order representationalism and self-representationalism). This chapter explores an alternative theory of consciousness, one that aims to explain consciousness not in terms of representation but in terms of the epistemically and metaphysically direct relation of acquaintance. The author calls this the Inner Acquaintance Theory of consciousness (IAT). Roughly, on IAT, what makes a mental state conscious is its subject being acquainted with it. The main goal of this chapter is to take some steps toward developing the details of IAT, illustrate its potential explanatory power, and put it forward as a plausible alternative to representational theories.
Revelation and the Appearance/Reality Distinction
Authors: Liu Michelle 
Published: September 2024

Abstract
It is often said that there is no appearance/reality distinction with respect to consciousness. Call this claim ‘nard’. In contemporary discussions, nard is closely connected to the thesis of revelation, the claim that the essences of phenomenal properties are revealed in experience, though the connection between the two requires clarification. This chapter distinguishes different versions of nard and homes in on a particular version that is closely connected to revelation. It shows how revelation and the related version of nard pose a threat to physicalism. Responses from physicalism and their limitations are also considered.
The Conscious Theory of Higher-Orderness
Authors: Silins Nicholas 
Published: September 2024

Abstract
The massive debate in philosophy and psychology and neuroscience about higher-order theories of consciousness has not adequately distinguished between the following two claims: (i) (Necessary Awareness): For any conscious mental state M and subject S, if S is in M, then S is aware of M; and (ii) (The Higher-Order Theory): For any conscious mental state M and subject S, if S is in M, then M is conscious because S is aware of M. While the chapter will assume that the first claim is true, it will argue that we should reject higher-order theories of consciousness. We should turn them on their head to go with the following theory: (The Ascending Road): For any conscious mental state M and subject S, if S is in M, then S is aware of M because M is conscious.
Simulation: Its Metaphysics and Epistemology
Authors: Peacocke Christopher 
Published: September 2024

Abstract
Dogmatic slumbers are as much a danger for us now as they were in Kant’s time. David Chalmers’ immensely stimulating and engaging book Reality+ ought to wake many of us from our own contemporary slumbers. Chalmers is Hume in this analogy; I am certainly not going to pretend to be Kant. But I will elaborate a disagreement on an issue in metaphysics and on an interrelated issue in epistemology, and indeed these disagreements do broadly concern the conditions of possibility of experience. I disagree with Chalmers’ statements that “Simulations are not illusions. Virtual worlds are real. Virtual objects really exist” (12) when applied to simulations that represent the world as spatial. That is the disagreement in metaphysics. I also question his position on a closely related matter of epistemology, his thesis that “We can’t know that we’re not in a simulation” (11). I take the metaphysical issue first.
AI-based IsAb2.0 for antibody design
Authors: Liang Tianjian , Sun Ze-Yu , Hines Margaret G , Penrose Kerri Jo , Hao Yixuan , Chu Xiaojie , Mellors John W , Dimitrov Dimiter S , Xie Xiang-Qun , Li Wei , Feng Zhiwei 
Published: September 2024

Abstract
Therapeutic antibody design has garnered widespread attention, highlighting its interdisciplinary importance. Advancements in technology emphasize the critical role of designing nanobodies and humanized antibodies in antibody engineering. However, current experimental methods are costly and time-consuming. Computational approaches, while progressing, faced limitations due to insufficient structural data and the absence of a standardized protocol. To tackle these challenges, our lab previously developed IsAb1.0, an in silico antibody design protocol. Yet, IsAb1.0 lacked accuracy, had a complex procedure, and required extensive antibody bioinformation. Moreover, it overlooked nanobody and humanized antibody design, hindering therapeutic antibody development. Building upon IsAb1.0, we enhanced our design protocol with artificial intelligence methods to create IsAb2.0. IsAb2.0 utilized AlphaFold-Multimer (2.3/3.0) for accurate modeling and complex construction without templates and employed the precise FlexddG method for in silico antibody optimization. Validated through optimization of a humanized nanobody J3 (HuJ3) targeting HIV-1 gp120, IsAb2.0 predicted five mutations that can improve HuJ3-gp120 binding affinity. These predictions were confirmed by commercial software and validated through binding and neutralization assays. IsAb2.0 streamlined antibody design, offering insights into future techniques to accelerate immunotherapy development.
Multimodal functional deep learning for multiomics data
Authors: Zhou Yuan , Geng Pei , Zhang Shan , Xiao Feifei , Cai Guoshuai , Chen Li ,   For the Alzheimer’s Disease Neuroimaging Initiative, Lu Qing 
Published: September 2024

Abstract
With rapidly evolving high-throughput technologies and consistently decreasing costs, collecting multimodal omics data in large-scale studies has become feasible. Although studying multiomics provides a new comprehensive approach in understanding the complex biological mechanisms of human diseases, the high dimensionality of omics data and the complexity of the interactions among various omics levels in contributing to disease phenotypes present tremendous analytical challenges. There is a great need of novel analytical methods to address these challenges and to facilitate multiomics analyses. In this paper, we propose a multimodal functional deep learning (MFDL) method for the analysis of high-dimensional multiomics data. The MFDL method models the complex relationships between multiomics variants and disease phenotypes through the hierarchical structure of deep neural networks and handles high-dimensional omics data using the functional data analysis technique. Furthermore, MFDL leverages the structure of the multimodal model to capture interactions between different types of omics data. Through simulation studies and real-data applications, we demonstrate the advantages of MFDL in terms of prediction accuracy and its robustness to the high dimensionality and noise within the data.
MEHunter: transformer-based mobile element variant detection from long reads
Authors: Jiang Tao , Zhou Zuji , Zhang Zhendong , Cao Shuqi , Wang Yadong , Liu Yadong 
Published: September 2024

Abstract

Summary
Mobile genetic elements (MEs) are heritable mutagens that significantly contribute to genetic diseases. The advent of long-read sequencing technologies, capable of resolving large DNA fragments, offers promising prospects for the comprehensive detection of ME variants (MEVs). However, achieving high precision while maintaining recall performance remains challenging mainly brought by the variable length and similar content of MEV signatures, which are often obscured by the noise in long reads. Here, we propose MEHunter, a high-performance MEV detection approach utilizing a fine-tuned transformer model adept at identifying potential MEVs with fragmented features. Benchmark experiments on both simulated and real datasets demonstrate that MEHunter consistently achieves higher accuracy and sensitivity than the state-of-the-art tools. Furthermore, it is capable of detecting novel potentially individual-specific MEVs that have been overlooked in published population projects.

Availability and implementation
MEHunter is available from https://github.com/120L021101/MEHunter.