bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-pulse H-mode operation with stored-energy monitoring for detachment feedback control with a new lower tungsten divertor in EAST
Authors: Tao Y.Q. , Xu G.S. , Wu K. , Yang Q.Q. , Wang L. , Yuan Q.P. , Wang Y.F. , Lin X. , Meng L.Y. , Ding G.F. , Yu L. , Chen R. , Liu J.B. , Yan N. , Lan H. , Sun P.J. , Li K.D. , Xu J.C. , Duan Y.M. , Zang Q. , Jin Y.F. , Zhang L. , Wang S.X. , Geng K.N. , Liang R.R. 
Published: April 2023

Abstract
One of the key challenges for future fusion research is to mitigate the high steady-state heat load on the divertor target plates, and divertor detachment offers a promising solution. The Experimental Advanced Superconducting Tokamak (EAST) has developed several feedback control methods for divertor detachment. However, when an off-normal event momentarily disturbs the main plasma, impurity seeding may still be conducted by these methods for detachment, which probably drives the main plasma further away from its stable equilibrium or even causes the disruption. These off-normal events include excessive impurity seeding, loss of heating and dust droplets, which are not rare in current tokamak experiments, especially in long-pulse operation. To compensate for the drawbacks of these methods, we propose and develop a module of stored-energy monitoring to ensure stable plasmas in long-pulse operation. The stored energy usually decreases when the main plasma is away from its stable equilibrium, which is suitable for monitoring the state of the main plasma. Once the stored energy falls below a certain threshold, the module actively switches off the impurity seeding system. Without impurity seeding, the main plasma can recover with the increase in the stored energy. Only when the stored energy exceeds another threshold does the module switch on the impurity seeding to continue the detachment operation. The module function has been verified during the EAST radiative divertor experiments in the newly-upgraded lower tungsten divertor. A typical ∼20 s discharge in grassy-ELM H-mode regime with ∼5 MW source heating power is demonstrated with divertor partial detachment and good energy confinement by active impurity seeding (50% neon, 50% D2). The energy confinement factor is maintained at a high level, i.e.

H

98
,
y
2

∼
1.1.

The electron temperature in the core region only has a slight change after the impurity seeding, while the electron density has a ∼10% increase. Furthermore, the ion temperature near the axis also has a remarkable increase. These achievements provide an important demonstration of the actively controlled radiative divertor mitigating the heat loads with good core confinement, which is an essential step toward steady-state operation of fusion reactors.
Towards the use of satellite-based tropical forest disturbance alerts to assess selective logging intensities
Authors: Welsink Anne-Juul , Reiche Johannes , de Sy Veronique , Carter Sarah , Slagter Bart , Suarez Daniela Requena , Batros Ben , Peña-Claros Marielos , Herold Martin 
Published: April 2023

AbstractIllegal logging is an important driver of tropical forest loss. A wide range of organizations and interested parties wish to track selective logging activities and verify logging intensities as reported by timber companies. Recently, free availability of 10 m scale optical and radar Sentinel data has resulted in several satellite-based alert systems that can detect increasingly small-scale forest disturbances in near-real time. This paper provides insight in the usability of satellite-based forest disturbance alerts to track selective logging in tropical forests. We derive the area of tree cover loss from expert interpretations of monthly PlanetScope mosaics and assess the relationship with the RAdar for Detecting Deforestation (RADD) alerts across 50 logging sites in the Congo Basin. We do this separately for various aggregation levels, and for tree cover loss from felling and skidding, and logging roads. A strong linear relationship between the alerts and visually identified tree cover loss indicates that with dense time series satellite data at 10 m scale, the area of tree cover loss in logging concessions can be accurately estimated. We demonstrate how the observed relationship can be used to improve near-real time tree cover loss estimates based on the RADD alerts. However, users should be aware that the reliability of estimations is relatively low in areas with few disturbances. In addition, a trade-off between aggregation level and accuracy requires careful consideration. An important challenge regarding remote verification of logging activities remains: as opposed to tree cover loss area, logging volumes cannot yet be directly observed by satellites. We discuss ways forward towards satellite-based assessment of logging volumes at high spatial and temporal detail, which would allow for better remote sensing based verification of reported logging intensities and tracking of illegal activities.
Seasonal characteristics and spatio-temporal variations of the extreme precipitation-air temperature relationship across China
Authors: Li Xiangmin , Wang Taihua , Zhou Ziyi , Su Jiaping , Yang Dawen 
Published: April 2023

Abstract
It is assumed that extreme precipitation (P) increases with air temperature (T) by a scaling rate close to 7%/°C without moisture limitation according to the Clausius-Clapeyron (C-C) relationship. However, the spatial distribution of the P-T relationship in China is subject to divergent conclusions including both sub-C-C (<7%/°C) and super-C-C (>7%/°C) scaling with reasons yet to be examined. Based on the long-term observations, here we show that P-T relationships with peak structure exist in most regions across China. The scaling rate in the wet season shows a decreasing spatial pattern from the southeast to the northwest, while sub-C-C scaling in the dry season dominates most regions across China. Mixing precipitation events from different seasons could lead to miscalculation of the P-T scaling rate. Furthermore, significant increases in peak precipitation at high percentiles have been observed in southern regions of China during the historical period, indicating that the peak structure does not imply a potential upper limit for precipitation extremes. Our results highlight the importance of considering seasonal characteristics in analyzing the extreme precipitation-temperature relationship in a changing climate.
Quiver Yangians and
-algebras for generalized conifolds
Authors: Bao Jiakang 
Published: April 2023

Abstract
We focus on quiver Yangians for most generalized conifolds. We construct a coproduct of the quiver Yangian following the similar approach by Guay–Nakajima–Wendlandt. We also prove that the quiver Yangians related by Seiberg duality are indeed isomorphic. Then we discuss their connections to

-algebras analogous to the study by Ueda. In particular, the universal enveloping algebras of the

-algebras are truncations of the quiver Yangians, and therefore they naturally have truncated crystals as their representations.
Paths towards synchronization: analytical treatment of completely connected networks
Authors: España Andrea , Leoncini Xavier , Ugalde Edgardo 
Published: April 2023

Abstract
We describe the transient regime of synchronizing flows defined over a network, introducing a codification of the paths towards synchronization. In all cases, the collection of paths toward synchronization defines a combinatorial structure: the transition diagram. In this paper, besides introducing this general framework, we study in full detail the case of completely connected networks where a monotonic convergence towards synchronization takes place. For these systems we are able to supply a detailed analytical description of the transition diagram describing both, the Laplacian flow and a special case of the Kuramoto model on the same network. This constitutes a first instance of a full symbolic description of the path towards synchronization and illustrates the hidden complexity of the transient regime.
Ultralow-power spiking neural networks for 1024-ary orbital angular momentum shift keying free-space optical communication
Authors: Li Baoli , Chen Qinyu , Su Hang , Cheng Ke , Luan Haitao , Gu Min , Fang Xinyuan 
Published: April 2023

Abstract
The theoretical unbounded orbital angular momentum (OAM) states can be exploited as data bits in the OAM shift keying (OAM-SK) free-space optical (FSO) communications. In order to cope with the atmospheric turbulence (AT) and misalignment in practical applications, various machine learning algorithms, or neural networks (NNs), have been put forward to decode the OAM states. However, to recognize the hybrid spatial modes representing a large bit states, the massive learnable nodes, longer computation time and more training parameters are required to improve the capability of the NNs, resulting in energy efficiency burden to the hardware device. In this paper, the event-based spiking neural network (SNN) is utilized to recognize the hybrid spatial modes consisting of superposed coaxial Laguerre–Gaussian modes with l ranging from 0 to 9 and p = 0, which is termed as spiking OAM-recognition neural network (Spiking-ORNN). In comparison to the previous solution of running deep NNs on graphics processing units, the neuromorphic solution of running Spiking-ORNN on neuromorphic chips exhibits 4300× higher energy efficiency without obvious sacrifice of recognition accuracy (less than 0.5%). Moreover, we experimentally demonstrate a 10 m 1024-ary OAM-SK FSO communication for the transmission of an image with a 10 bit grey level, wherein the peak signal-to-noise ratio of the received image can exceed 41.4 dB under the AT of

C
n
2

=10−15 m−2/3. We anticipate that our results can stimulate further researches on the utilization of the brain-like SNN chips to reduce the energy consumptions based on the artificial-intelligence-enhanced optoelectronic systems.
On-chip mixing of cancer cells and drug using LED enabled 2D opto-wetting droplet platforms
Authors: Thomas Tony , Govindharaj Mano , Unni Harikrishnan Narayanan , Kumari Neema , Rath Subha Narayan 
Published: April 2023

Abstract
Droplets of microliter size serve as miniaturized reaction chambers for practical lab on a chip (LoC) applications. The transportation and coalescence of droplets are indispensable for realizing microfluidic mixing. Light can be used as an effective tool for droplet manipulation. We report a novel platform for LED-based transport and mixing of cell-encapsulated microdroplets for evaluating dose response of cancer drugs. Microcontroller enabled LEDs (Light-emitting diodes) were used to actuate droplet movement on Azobenzene coated planar silicon substrates. Droplet transport was initiated by the spatial gradient in solid-liquid interfacial tension developed through LED triggered photoisomerization of Azobenzene substrate. Detailed UV-Visible characterization of Azobenzene molecule was performed for different LED light intensities and wavelengths. A complete standalone opto-wetting toolbox was developed by integrating various components such as a microcontroller, UV LED (385 nm), blue LED (465 nm), and Azobenzene coated photoresponsive substrate. 2D transport of DI water droplets (10–30 μl) along simple trajectories was demonstrated using this device. Subsequently, the proposed opto-wetting platform was used for performing drug evaluation through on-chip mixing of droplets containing cancer cells (A549—Lung cancer cells) and cancer drug (paclitaxel). Separate cell viability analysis was performed using MTT assays, where the cytocompatibility of Azobenzene and UV light (385 nm) on A549 cells were studied. The dosage response of paclitaxel drug was studied using both MTT (3-(4,5-Dimethylthiazolyl-2)−2,5-diphenyltetrazolium bromide) and live-dead cell assays. The results obtained indicate the potential use of our device as a cost-effective, reliable opto-wetting microfluidic platform for drug screening experiments.
Prediabetes, diabetes and loss of disability-free survival in a community-based older cohort: a post-hoc analysis of the ASPirin in Reducing Events in the Elderly trial
Authors: Zhou Zhen , Curtis Andrea J , Owen Alice , Wolfe Rory , Murray Anne M , Tonkin Andrew M , Ernst Michael E , Orchard Suzanne G , Zhu Chao , Carr Prudence R , Reid Christopher M , Espinoza Sara E , Shah Raj C , Woods Robyn L , Ryan Joanne , McNeil John J , Nelson Mark R , Zoungas Sophia 
Published: April 2023

Abstract

Background
Evidence for the prognostic implications of hyperglycaemia in older adults is inconsistent.

Objective
To evaluate disability-free survival (DFS) in older individuals by glycaemic status.

Methods
This analysis used data from a randomised trial recruiting 19,114 community-based participants aged ≥70 years, who had no prior cardiovascular events, dementia and physical disability. Participants with sufficient information to ascertain their baseline diabetes status were categorised as having normoglycaemia (fasting plasma glucose [FPG] &lt; 5.6 mmol/l, 64%), prediabetes (FPG 5.6 to &lt;7.0 mmol/l, 26%) and diabetes (self-report or FPG ≥ 7.0 mmol/l or use of glucose-lowering agents, 11%). The primary outcome was loss of disability-free survival (DFS), a composite of all-cause mortality, persistent physical disability or dementia. Other outcomes included the three individual components of the DFS loss, as well as cognitive impairment-no dementia (CIND), major adverse cardiovascular events (MACE) and any cardiovascular event. Cox models were used for outcome analyses, with covariate adjustment using inverse-probability weighting.

Results
We included 18,816 participants (median follow-up: 6.9 years). Compared to normoglycaemia, participants with diabetes had greater risks of DFS loss (weighted HR: 1.39, 95% CI 1.21–1.60), all-cause mortality (1.45, 1.23–1.72), persistent physical disability (1.73, 1.35–2.22), CIND (1.22, 1.08–1.38), MACE (1.30, 1.04–1.63) and cardiovascular events (1.25, 1.02–1.54) but not dementia (1.13, 0.87–1.47). The prediabetes group did not have an excess risk for DFS loss (1.02, 0.93–1.12) or other outcomes.

Conclusions
Among older people, diabetes was associated with reduced DFS, and higher risk of CIND and cardiovascular outcomes, whereas prediabetes was not. The impact of preventing or treating diabetes in this age group deserves closer attention.
Characterization of Tissue Histology for the Injectable Cellulite Treatment Collagenase Clostridium Histolyticum-aaes: Results in Swine
Authors: Shridharani Sachin M , Vijayan Saji , Napekoski Karl M , Dalton Shannon R , Bhatia Ashish C 
Published: April 2023

Abstract

Background
Cellulite is a common aesthetic condition that affects predominantly females. Collagenase clostridium histolyticum-aaes (CCH-aaes) injections disrupt native collagen structures, resulting in an improvement in cellulite appearance. However, injection-site bruising is a frequently occurring adverse event with CCH-aaes treatment.

Objectives
To characterize tissue histology following CCH-aaes injection in Yorkshire pigs.

Methods
In an animal study, female swine with 10 defined dosing sites on the ventral-lateral aspect received 1 or 2 CCH-aaes (0.07 mg/0.3 mL) or placebo subcutaneous injections at a single site at designated time points before tissue sampling.

Results
Injection with CCH-aaes was associated with lysis of mature, collagen-rich septa in the subcutaneous layer at and adjacent to the injection site as early as Day 1. On Day 4, an increase in inflammatory cells and a decrease in hemorrhage (vs Day 2) were observed, with inflammation and hemorrhage decreased by Day 8. By Day 21, deposition of new collagen and reorganization of fat lobules were observed. Observations with repeat CCH-aaes treatment were comparable with 1 course of CCH-aaes treatment.

Conclusions
In this animal study, targeted enzymatic subcision of collagenous bands and remodeling of subcutaneous tissue were observed following CCH-aaes injection.

Level of Evidence: 3
Vocal performance increases rapidly during the dawn chorus in Adelaide’s warbler (Setophaga adelaidae)
Authors: Vazquez-Cardona Juleyska , Bonnell Tyler R , Mower Peter C , Medina Orlando J , Jiskoot Hester , Logue David M 
Published: April 2023

Abstract
Many songbirds sing intensely during the early morning, resulting in a phenomenon known as the dawn chorus. We tested the hypothesis that male Adelaide’s warblers (Setophaga adelaidae) warm up their voices during the dawn chorus. If warming up the voice is one of the functions of the dawn chorus, we predicted that vocal performance would increase more rapidly during the dawn chorus compared to the rest of the morning and that high song rates during the dawn chorus period contribute to the increase in vocal performance. The performance metrics recovery time, voiced frequency modulation, and unvoiced frequency modulation were low when birds first began singing, increased rapidly during the dawn chorus, and then leveled off or gradually diminished after dawn. These changes are attributable to increasing performance within song types. Reduction in the duration of the silent gap between notes is the primary driver of improved performance during the dawn chorus. Simulations indicated that singing at a high rate during the dawn chorus period increases performance in two of the three performance measures (recovery time and unvoiced frequency modulation) relative to singing at a low rate during this period. These findings are consistent with the hypothesis that vocal warm-up is one benefit of participation in the dawn chorus.
Machine learning for RNA 2D structure prediction benchmarked on experimental data
Authors: Justyna Marek , Antczak Maciej , Szachniuk Marta 
Published: April 2023

Abstract
Since the 1980s, dozens of computational methods have addressed the problem of predicting RNA secondary structure. Among them are those that follow standard optimization approaches and, more recently, machine learning (ML) algorithms. The former were repeatedly benchmarked on various datasets. The latter, on the other hand, have not yet undergone extensive analysis that could suggest to the user which algorithm best fits the problem to be solved. In this review, we compare 15 methods that predict the secondary structure of RNA, of which 6 are based on deep learning (DL), 3 on shallow learning (SL) and 6 control methods on non-ML approaches. We discuss the ML strategies implemented and perform three experiments in which we evaluate the prediction of (I) representatives of the RNA equivalence classes, (II) selected Rfam sequences and (III) RNAs from new Rfam families. We show that DL-based algorithms (such as SPOT-RNA and UFold) can outperform SL and traditional methods if the data distribution is similar in the training and testing set. However, when predicting 2D structures for new RNA families, the advantage of DL is no longer clear, and its performance is inferior or equal to that of SL and non-ML methods.
Benchmarking of analytical combinations for COVID-19 outcome prediction using single-cell RNA sequencing data
Authors: Cao Yue , Ghazanfar Shila , Yang Pengyi , Yang Jean 
Published: April 2023

Abstract
The advances of single-cell transcriptomic technologies have led to increasing use of single-cell RNA sequencing (scRNA-seq) data in large-scale patient cohort studies. The resulting high-dimensional data can be summarized and incorporated into patient outcome prediction models in several ways; however, there is a pressing need to understand the impact of analytical decisions on such model quality. In this study, we evaluate the impact of analytical choices on model choices, ensemble learning strategies and integrate approaches on patient outcome prediction using five scRNA-seq COVID-19 datasets. First, we examine the difference in performance between using single-view feature space versus multi-view feature space. Next, we survey multiple learning platforms from classical machine learning to modern deep learning methods. Lastly, we compare different integration approaches when combining datasets is necessary. Through benchmarking such analytical combinations, our study highlights the power of ensemble learning, consistency among different learning methods and robustness to dataset normalization when using multiple datasets as the model input.
Maternal serotonin: implications for the use of selective serotonin reuptake inhibitors during gestation
Authors: Domingues Rafael R , Wiltbank Milo C , Hernandez Laura L 
Published: April 2023

Abstract
Maternal use of antidepressants has increased throughout the last decades; selective serotonin reuptake inhibitors (SSRI) are the most prescribed antidepressants. Despite the widespread use of SSRI by women during reproductive age and pregnant women, an increasing amount of research warns of possible detrimental effects of maternal use of SSRI during pregnancy including low birthweight/small for gestational age and preterm birth. In this review, we revisited the impact of maternal use of SSRI during pregnancy, its impact on serotonin homeostasis in the maternal and fetal circulation and the placenta, and its impact on pregnancy outcomes—particularly intrauterine growth restriction and preterm birth. Maternal use of SSRI increases maternal and fetal serotonin. The increase in maternal circulating serotonin and serotonin signaling likely promotes vasoconstriction of the uterine and placental vascular beds decreasing blood perfusion to the uterus and consequently to the placenta and fetus with potential impact on placental function and fetal development. Several adverse pregnancy outcomes are similar between women, sheep, and rodents (decreased placental size, decreased birthweight, shorter gestation length/preterm birth, neonatal morbidity, and mortality) highlighting the importance of animal studies to assess the impacts of SSRI. Herein, we address the complex interactions between maternal SSRI use during gestation, circulating serotonin, and the regulation of blood perfusion to the uterus and fetoplacental unit, fetal growth, and pregnancy complications.
Shared decision-making and satisfaction with care: a population-based study in patients with acne with skin of colour in the USA
Authors: Kingston Paige , Yee Danielle , Huang Margaret Y , Korouri Edwin , Peterson Hannah , Lee Kathryn  , Agüero Rosario , Armstrong April W 
Published: April 2023

Abstract
Little is known about differences in shared decision-making and patient satisfaction with acne care among different ethnicities and races. We conducted a cross-sectional study to determine differences between patients with acne who are White and those with skin of colour (SOC), i.e. (i) engagement in shared decision-making, and (ii) patient satisfaction with care, using the 2009–2017 and 2019 Medical Panel Expenditure Survey. Patients with acne with SOC were nearly two times more likely to engage in high shared decision-making compared with White patients [adjusted odds ratio 1.80, 95% confidence interval (CI) 1.30–2.51, P &lt; 0.001]. Patients with SOC with acne reported lower satisfaction with care compared with White patients (β = –0.38, 95% CI –0.69 to –0.06, P = 0.02). Patients with SOC who had acne reported higher levels of shared decision-making than White patients. However, compared with the White patients, patients with SOC report lower satisfaction with their care. There may be other factors contributing to lower satisfaction with care in patients with SOC who have acne.