bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reversible intracellular acidification and depletion of NTPs provide a potential physiological origin for centuries of dormancy in an Antarctic freshwater copepod
Authors: Reed Katherine A. , Williamson R. Thomas , Lee Sung Gu , Lee Jun Hyuck , Covi Joseph A. 
Published: August 2023

AbstractA great diversity of crustacean zooplankton found in inland and coastal waters produce embryos that settle into bottom sediments to form an egg bank. Embryos from these banks can remain dormant for centuries, creating a reservoir of genetic diversity. A large body of literature describes the ecological and evolutionary importance of zooplankton egg banks. However, literature on the physiological traits behind dormancy in crustacean zooplankton are limited. Most data on the physiology of dormancy comes from research on one species of anostracan, the brine shrimp, Artemia franciscana. Anoxia-induced dormancy in this species is facilitated by a profound and reversible acidification of the intracellular space. This acidification is accompanied by a reversible depletion of adenosine triphosphate (ATP). The present study demonstrates that acidification of the intracellular space also occurs in concert with a depletion of nucleoside triphosphates (NTPs) in the Antarctic copepod, Boeckella poppei. Like A. franciscana, the depletion of NTPs and acidification are rapidly reversed during aerobic recovery in B. poppei. These data provide the first comparative evidence that extreme dormancy under anoxia in crustacean zooplankton is associated with intracellular acidification and an ability to recover from the depletion of ATP.
Determining regional brain growth in premature and mature infants in relation to age at MRI using deep neural networks
Authors: Beizaee Farzad , Bona Michele , Desrosiers Christian , Dolz Jose , Lodygensky Gregory 
Published: August 2023

AbstractNeonatal MRIs are used increasingly in preterm infants. However, it is not always feasible to analyze this data. Having a tool that assesses brain maturation during this period of extraordinary changes would be immensely helpful. Approaches based on deep learning approaches could solve this task since, once properly trained and validated, they can be used in practically any system and provide holistic quantitative information in a matter of minutes. However, one major deterrent for radiologists is that these tools are not easily interpretable. Indeed, it is important that structures driving the results be detailed and survive comparison to the available literature. To solve these challenges, we propose an interpretable pipeline based on deep learning to predict postmenstrual age at scan, a key measure for assessing neonatal brain development. For this purpose, we train a state-of-the-art deep neural network to segment the brain into 87 different regions using normal preterm and term infants from the dHCP study. We then extract informative features for brain age estimation using the segmented MRIs and predict the brain age at scan with a regression model. The proposed framework achieves a mean absolute error of 0.46 weeks to predict postmenstrual age at scan. While our model is based solely on structural T2-weighted images, the results are superior to recent, arguably more complex approaches. Furthermore, based on the extracted knowledge from the trained models, we found that frontal and parietal lobes are among the most important structures for neonatal brain age estimation.
Global dose distributions of neutrons and gamma-rays on the Moon
Authors: Naito Masayuki , Kusano Hiroki , Kodaira Satoshi 
Published: August 2023

AbstractDose assessment on the lunar surface is important for future long-term crewed activity. In addition to the major radiation of energetic charged particles from galactic cosmic rays (GCRs), neutrons and gamma-rays are generated by nuclear interactions of space radiation with the Moon’s surface materials, as well as natural radioactive nuclides. We obtained neutron and gamma-ray ambient dose distributions on the Moon using Geant4 Monte Carlo simulations combined with the Kaguya gamma-ray spectrometer measurement dataset from February 10 to May 28, 2009. The neutron and gamma-ray dose rates varied in the ranges of 58.7–71.5 mSv/year and 3.33–3.76 mSv/year, respectively, depending on the lunar geological features. The lunar neutron dose was high in the basalt-rich mare, where the iron- and titanium-rich regions are present, due to their large average atomic mass. As expected, the lunar gamma-ray dose map was similar to the distribution of natural radioactive elements (238U, 232Th, and 40K), although the GCR-induced secondary gamma-ray dose was significant at ~ 3.4 mSv/year. The lunar secondary dose contribution resulted in an additional dose of 12–15% to the primary GCR particles. Global dose distributions on the lunar surface will help identify better locations for long-term stays and suggest radiation protection strategies for future crewed missions.
A multiband SSr diode RF rectifier with an improved frequency ratio for biomedical wireless applications
Authors: Muhammad Surajo , Waly Mohamed Ibrahim , AlJarallah Nasser Ali , Ghayoula Ridha , Negm Ahmed S. , Smida Amor , Iqbal Amjad , Tiang Jun Jiat , Roslee Mardeni 
Published: August 2023

AbstractThis paper described a four-band implantable RF rectifier with simplified circuit complexity. Each RF-rectifier cell is sequentially matched to the four operational frequencies to accomplish the proposed design. The proposed RF rectifier can harvest RF signals at 1.830, 2.100, and white space Wi-Fi bands between 2.38 to 2.68 GHz, respectively. At 2.100 GHz, the proposed RF harvester achieved a maximum (radio frequency direct current) RF-to-DC power conversion efficiency (PCE) of 73.00% and an output DC voltage $$V_{DC}$$

V

DC

of 1.61 V for an RF power of 2 dBm. The outdoor performance of the rectenna shows a $$V_{DC}$$

V

DC

of 0.440 V and drives a low-power bq25504-674 evaluation module (EVM) at 1.362 V. The dimension of the RF-rectifier on the FR-4 PCB board is 0.27$$\lambda _{g}$$

λ
g

$$\times$$
×
0.29$$\lambda _{g}$$

λ
g

. The RF-rectifier demonstrates the capacity to effectively utilize the frequency domain by employing multi-band operation and exhibiting a good impedance bandwidth through a sequential matching technique. Thus, by effectively controlling the rectenna’s ambient performance, the proposed design holds the potential for powering a range of low-power biomedical implantable devices. (BIDs).
ENSO skewness hysteresis and associated changes in strong El Niño under a CO2 removal scenario
Authors: Liu Chao , An Soon-Il , Jin Fei-Fei , Stuecker Malte F. , Zhang Wenjun , Kug Jong-Seong , Yuan Xinyi , Shin Jongsoo , Xue Aoyun , Geng Xin , Kim Soong-Ki 
Published: August 2023

AbstractEl Niño-Southern Oscillation (ENSO) sea surface temperature (SST) anomaly skewness encapsulates the nonlinear processes of strong ENSO events and affects future climate projections. Yet, its response to CO2 forcing remains not well understood. Here, we find ENSO skewness hysteresis in a large ensemble CO2 removal simulation. The positive SST skewness in the central-to-eastern tropical Pacific gradually weakens (most pronounced near the dateline) in response to increasing CO2, but weakens even further once CO2 is ramped down. Further analyses reveal that hysteresis of the Intertropical Convergence Zone migration leads to more active and farther eastward-located strong eastern Pacific El Niño events, thus decreasing central Pacific ENSO skewness by reducing the amplitude of the central Pacific positive SST anomalies and increasing the scaling effect of the eastern Pacific skewness denominator, i.e., ENSO intensity, respectively. The reduction of eastern Pacific El Niño maximum intensity, which is constrained by the SST zonal gradient of the projected background El Niño-like warming pattern, also contributes to a reduction of eastern Pacific SST skewness around the CO2 peak phase. This study highlights the divergent responses of different strong El Niño regimes in response to climate change.
Online repositories of photographs and videos provide insights into the evolution of skilled hindlimb movements in birds
Authors: Gutiérrez-Ibáñez Cristián , Amaral-Peçanha Clara , Iwaniuk Andrew N. , Wylie Douglas R. , Baron Jerome 
Published: August 2023

AbstractThe ability to manipulate objects with limbs has evolved repeatedly among land tetrapods. Several selective forces have been proposed to explain the emergence of forelimb manipulation, however, work has been largely restricted to mammals, which prevents the testing of evolutionary hypotheses in a comprehensive evolutionary framework. In birds, forelimbs have gained the exclusive function of flight, with grasping transferred predominantly to the beak. In some birds, the feet are also used in manipulative tasks and appear to share some features with manual grasping and prehension in mammals, but this has not been systematically investigated. Here we use large online repositories of photographs and videos to quantify foot manipulative skills across a large sample of bird species (>1000 species). Our results show that a complex interaction between niche, diet and phylogeny drive the evolution of manipulative skills with the feet in birds. Furthermore, we provide strong support for the proposition that an arboreal niche is a key element in the evolution of manipulation in land vertebrates. Our systematic comparison of foot use in birds provides a solid base for understanding morphological and neural adaptations for foot use in birds, and for studying the convergent evolution of manipulative skills in birds and mammals.
Neural network interatomic potential for laser-excited materials
Authors: Plettenberg Pascal , Bauerhenne Bernd , Garcia Martin E. 
Published: August 2023

AbstractData-driven interatomic potentials based on machine-learning approaches have been increasingly used to perform large-scale, first-principles quality simulations of materials in the electronic ground state. However, they are not able to describe situations in which the electrons are excited, like in the case of material processing by means of femtosecond laser irradiation or ion bombardment. In this work, we propose a neural network interatomic potential with an explicit dependency on the electronic temperature. Taking silicon as an example, we demonstrate its capability of reproducing important physical properties with first-principles accuracy and use it to simulate laser-induced surface modifications on a thin film at time and length scales that are impossible to reach with first-principles approaches like density functional theory. The method is general and can be applied not only to other laser-excited materials but also to condensed and liquid matter under non-equilibrium situations in which electrons and ions exhibit different temperatures.
Unlocking phonon properties of a large and diverse set of cubic crystals by indirect bottom-up machine learning approach
Authors: Rodriguez Alejandro , Lin Changpeng , Shen Chen , Yuan Kunpeng , Al-Fahdi Mohammed , Zhang Xiaoliang , Zhang Hongbin , Hu Ming 
Published: August 2023

AbstractAlthough first principles based anharmonic lattice dynamics is one of the most common methods to obtain phonon properties, such method is impractical for high-throughput search of target thermal materials. We develop an elemental spatial density neural network force field as a bottom-up approach to accurately predict atomic forces of ~80,000 cubic crystals spanning 63 elements. The primary advantage of our indirect machine learning model is the accessibility of phonon transport physics at the same level as first principles, allowing simultaneous prediction of comprehensive phonon properties from a single model. Training on 3182 first principles data and screening 77,091 unexplored structures, we identify 13,461 dynamically stable cubic structures with ultralow lattice thermal conductivity below 1 Wm−1K−1, among which 36 structures are validated by first principles calculations. We propose mean square displacement and bonding-antibonding as two low-cost descriptors to ease the demand of expensive first principles calculations for fast screening ultralow thermal conductivity. Our model also quantitatively reveals the correlation between off-diagonal coherence and diagonal populations and identifies the distinct crossover from particle-like to wave-like heat conduction. Our algorithm is promising for accelerating discovery of novel phononic crystals for emerging applications, such as thermoelectrics, superconductivity, and topological phonons for quantum information technology.
Social innovation supports inclusive and accelerated energy transitions with appropriate governance
Authors: Sovacool Benjamin K. , Brugger Heike , Brunzema Iska , Dańkowska Alicja , Wemyss Devon , Vernay Anne-Lorène , Betz Regina , Avelino Flor , de Geus Tessa , Dembek Agata , Duetschke Elisabeth , Hielscher Sabine , Iskandarova Marfuga , Müller Leticia , Musiolik Jörg , Ranville Adélie , Schleich Joachim , Stasik Agata , Strumińska-Kutra Marta , Winzer Christian , Wittmayer Julia , Rogge Karoline S. 
Published: August 2023

AbstractAccelerating energy transitions that are both sustainable and just remains an important challenge, and social innovation can have a key role in this transition. Here, we examine the diversity and potential of social innovation in energy systems transformation, synthesizing original mixed methods data from expert interviews, document analysis, social innovation experiments, a representative survey, and an expert survey. Based on a thematic analysis of these data, we advance four key findings: (1) the diversity of social innovation in energy is best understood when recognizing core social practices (thinking, doing, and organizing) and accounting for changes in social relations (cooperation, exchange, competition, and conflict); (2) governance, policy networks, and national context strongly shape social innovation dynamics; (3) processes of social innovation are implicated by multidimensional power relations that can result in transformative changes; and (4) social innovation in energy generally has strong social acceptance among citizens, benefits local communities and is legitimized in key community and city organizations. We discuss an agenda for 9 future research directions on social innovation in energy, and conclude with insights related to national context, governance, and acceleration.
A novel design of DNA duplex containing programmable sensing sites for nanopore-based length-resolution reading and applications for Pb2+ and cfDNA analysis
Authors: Wang Jiahai , Gui Cenlin , Zhu Jianji , Zhu Baian , Zhu Zhuobin , Jiang Xiwen , Chen Daqi 
Published: August 2023

A novel design of dsDNA block contained a programmable sensing site inside is proposed, which can be programmed with different sequences to respond to multiple target molecules (e.g. Pb2+ and cfDNA) by being cleaved into two smaller DNA blocks.
Reversibly photoswitchable catalysts for high regioselectivity and enantioselectivity in polymerization of allenes
Authors: Zhou Li , Wu Yong-Jie , Chen Kun , Zhou Xing-Yu , Zou Hui , Kang Shu-Ming , Liu Na , Wu Zong-Quan 
Published: August 2023

Two enantiomers Ni(ii)/LR-azo and Ni(ii)/LS-azo could be used as reversible photo-switchable catalysts for the high regioselectivity and enantioselectivity polymerization of allene monomers.
MiR-21 attenuates FAS-mediated cardiomyocyte apoptosis by regulating HIPK3 expression
Authors: Wang Xinyu , Zhang Tingting , Zhai Jianlong , Wang Zhongli , Wang Yan , He Lili , Ma Sai , Xing Hanying , Guo Yifang 
Published: August 2023

Abstract
MicroRNA-21 (miR-21) plays an anti-apoptotic role following ischemia–reperfusion (I/R) injury (IRI) in vivo; however, its underlying mechanism remains unclear. The present study explored the effects of miR-21 and homeodomain interacting protein kinase 3 (HIPK3) on cardiomyocyte apoptosis induced by hypoxia/reoxygenation (H/R) in vitro. To this end, the rat cardiomyocyte H9C2 cell line was exposed to H/R and the roles of miR-21 and HIPK3 in regulating cell viability and apoptosis were evaluated by cell counting kit-8 assay, terminal-deoxynucleotidyl-transferase-mediated dUTP nick end labeling, and flow cytometry. Immunofluorescence and Western blotting were performed to detect the expression/phosphorylation of apoptosis-related proteins. miR-21 expression was measured with quantitative real-time polymerase chain reaction. The putative interaction between miR-21 and HIPK3 was evaluated using the luciferase reporter assay. Our results showed that (i) miR-21 overexpression or HIPK3 down-regulation significantly attenuated H9C2 cells apoptosis after H/R, (ii) suppression of miR-21 expression promoted apoptosis, (iii) miR-21 overexpression inhibited HIPK3 expression, (iv) HIPK3 was the direct and main target of miR-21, (v) miR-21/HIPK3 formed part of a reciprocal, negative feedback loop, and (vi) HIPK3 down-regulation decreased FAS-mediated apoptosis by inhibiting the phosphorylation of FADD, which subsequently inhibited the expression of BAX and cleaved caspase-3 and increased the expression of BCL2. Our study indicates that miR-21 attenuates FAS-mediated cardiomyocyte apoptosis by regulating HIPK3 expression, which could eventually have important clinical implications for patients with acute myocardial infarction.
Trend analysis of traffic management based on literature data mining and graph analysis tools
Authors: Ding Xiaoe , Liu Wenke , Wang Chengcheng , Kong Delan , Tang Wei , Xu Run , Zhang Changyong 
Published: August 2023

AbstractStudites on traffic management is crucial for the development of intelligent transportation systems and smart cities. However, identifying the development stages of traffic management field based on bibliometric analysis is still lacking. In this study, CiteSpace and VOSviewer software are used to explore “traffic management” field by summarizing development process and predicting future research trend. A total of 3,028 relevant documents over the past 40 years were collected from Web of Science. Results show that (1) studies on traffic management were mainly published by researchers from USA (30.55%), China (20.90%), and some European countries; (2) the key traffic management research contents can be classified into four categories, that is, background requirements, traffic problems, method models, and control strategies; (3) the evolution process can be divided into four stages, that is, budding stage (1990–1994), development stage (1995–2003), calm stage (2004–2010), and maturation stage (2011–); (4) machine learning, deep learning and other intelligent algorithms have played more important roles in recent years, and connected vehicle management is also a potential development trend. Results suggest that cooperative vehicle‐infrastructure systems or machine learning‐based studies might be the hotspots on traffic management studies.
Closing the loop for AI-ready radiology
Authors: Fuchs Moritz , Gonzalez Camila , Frisch Yannik , Hahn Paul , Matthies Philipp , Gruening Maximilian , Pinto dos Santos Daniel , Dratsch Thomas , Kim Moon , Nensa Felix , Trenz Manuel , Mukhopadhyay Anirban 
Published: August 2023

Background In recent years, AI has made significant advancements in medical diagnosis and prognosis. However, the incorporation of AI into clinical practice is still challenging and under-appreciated. We aim to demonstrate a possible vertical integration approach to close the loop for AI-ready radiology.
Method This study highlights the importance of two-way communication for AI-assisted radiology. As a key part of the methodology, it demonstrates the integration of AI systems into clinical practice with structured reports and AI visualization, giving more insight into the AI system. By integrating cooperative lifelong learning into the AI system, we ensure the long-term effectiveness of the AI system, while keeping the radiologist in the loop.
Results We demonstrate the use of lifelong learning for AI systems by incorporating AI visualization and structured reports. We evaluate Memory Aware-Synapses and Rehearsal approach and find that both approaches work in practice. Furthermore, we see the advantage of lifelong learning algorithms that do not require the storing or maintaining of samples from previous datasets.
Conclusion In conclusion, incorporating AI into the clinical routine of radiology requires a two-way communication approach and seamless integration of the AI system, which we achieve with structured reports and visualization of the insight gained by the model. Closing the loop for radiology leads to successful integration, enabling lifelong learning for the AI system, which is crucial for sustainable long-term performance.
Key Points:
Social networks, disinformation and diplomacy: a dynamic model for a current problem
Authors: Guzmán Rincón Alfredo , Barragán Moreno Sandra , Rodríguez-Canovas Belén , Carrillo Barbosa Ruby Lorena , Africano Franco David Ricardo 
Published: August 2023

AbstractThe potential of social networks for the circulation of disinformation as a strategy of diplomacy has been of great interest to the academic community, but the way in which it is propagated and modelled is still in its beginnings. This article aimed to simulate the propagation of disinformation in social networks derived from the diplomacy strategy, based on the elements of the system. The main research question that was opened up was how do the elements of disinformation derived from the social media diplomacy strategy interact to affect a susceptible population? For the design of the simulation model, system dynamics was used as the main technique in the re-search methodology in conjunction with statistical analysis. Five computational simulations were run for the adoption methods of susceptible and uninformed population, misinformation techniques and echo chamber. The model developed found that the diplomacy disinformation agent is able to spread its message efficiently through the bot outreach mechanism and only a part of the susceptible population unsubscribes to the disinformation agent’s account. Significant differences were identified in the absence of paid outreach, bots and trolls in the propagation of information, and in the variation in the timing of disinformation propagation. Consequently, the developed model allows the understanding of the problem of disinformation as a strategy of diplomacy from international rather than local dynamics, as well as the effects of the use of each element in the system.