bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative multimodal imaging of extensive macular atrophy with pseudodrusen and geographic atrophy with diffuse trickling pattern
Authors: Antropoli Alessio , Arrigo Alessandro , Bianco Lorenzo , Berni Alessandro , Lamberto La Franca , Saladino Andrea , Bandello Francesco , Battaglia Parodi Maurizio 
Published: February 2023

AbstractTo compare clinical and imaging characteristics of extensive macular atrophy with pseudodrusen-like appearance (EMAP) versus diffuse-trickling geographic atrophy (DTGA) and non-diffuse-trickling geographic atrophy (nDTGA) phenotypes of age-related macular degeneration. Prospective, observational study performed in the Ophthalmology Department of IRCCS San Raffaele Hospital between January 2015 and January 2021. Patients examination included fundus autofluorescence (FAF) and optical coherence tomography at baseline and follow-up visits. We measured subfoveal choroidal thickness (SCT), Sattler/choroid ratio (SCR), choroidal vascularity index and ellipsoid zone disruption distance on OCT scans. We calculated progression rates and circularity of the atrophic lesions on FAF images. These variables were compared between the three groups and correlations with progression rates and visual acuity were assessed. Sixty-three eyes from 63 patients were included: 18 with EMAP, 18 with DTGA and 27 with nDTGA. Mean follow-up was 3.73 ± 2.12 years. EMAP and DTGA shared a faster progression, lower circularity and SCR, and higher EZ disruption distance than nDTGA, while SCT and CVI were similar between the three groups. Baseline circularity and SCR correlated with progression rates. EMAP and DTGA show similar OCT and FAF characteristics, which differ from nDTGA.
Surface-dependent quenching of Qdot emission can be a new tool for high resolution measurements
Authors: Okura Kaoru , Tatsumi Hitoshi 
Published: February 2023

AbstractSingle quantum dots (Qdots) are often used in the field of single-molecule imaging. Qdots are sensitive to changes in the physical interactions between the Qdots and the surrounding materials. However, the spectral changes in a single Qdot emission have not been studied in detail. Low-temperature plasma treatment of glass surfaces reduced the intensity of the 655 nm emission peak of Qdot655 on glass surfaces, but did not significantly change the intensity of the 580 nm emission. Silanization of the glass surface increases the thickness of the silane layer, and the 655 nm emission peak increased. When single Qdots on the untreated glass were imaged, plasma treatment decreased the intensity of red emission and increased yellow emission. When Qdots were brought close to the glass surface in the range of 28–0 nm, the red emission intensity decreased and the yellow emission intensity increased slightly. When single actin filaments were labeled with Qdots, fluctuations of the yellow and red emission of the Qdot were detected, which reflected the very small distance changes. Our results indicate that the local interaction of Qdots with the glass surface improves the spatial and temporal resolution of optical measurements of biomolecules labeled with Qdots.
Efficacy of combined transbronchial lung cryobiopsy and conventional forceps biopsy for lung malignancies: a prospective cohort study
Authors: Kinoshita Kohei , Morikawa Kei , Tsuruoka Hajime , Chosokabe Motohiro , Kida Hirotaka , Handa Hiroshi , Inoue Takeo , Miyazawa Tomoyuki , Saji Hisashi , Mineshita Masamichi 
Published: February 2023

AbstractThere are few prospective reports of transbronchial lung cryobiopsy (TBLC) for malignant tumors in combination with forceps biopsy. We investigated the clinical parameters in which TBLC is superior to forceps biopsy. This is a prospective cohort study to analyse the efficacy of TBLC for suspected malignancy. TBLC was performed after brushing cytology and forceps biopsy, and the diagnostic yield for TBLC, brushing cytology, and forceps biopsy were examined. Adverse events were defined as those requiring additional procedures. Next-generation sequencing (NGS) analysis was performed in each case of non-small cell lung cancer. Of the 100 patients, malignancy was confirmed in 94 cases. The diagnostic yield for TBLC/forceps biopsy/brushing cytology was 86/81/82% respectively, while the diagnostic yield for all procedures combined was 94%. There was no significant difference in the diagnostic yield between TBLC and forceps biopsy. When comparing the biopsy site, the diagnostic yield for TBLC at the lower lobe was significantly higher than forceps biopsy (P < 0.01). Endobronchial ultrasonography imaging using a guide-sheath did not significantly differ in the diagnostic yield of TBLC. The success rate of NGS for TBLC specimens was 100% (26 cases). Adverse events included two cases of severe bleeding. TBLC of peripheral lesions may improve the diagnostic yield when combined with forceps biopsy and brushing cytology. The diagnostic yield of TBLC was higher at the lower lobes. Furthermore, TBLC provided sufficient specimen quality for NGS.
Unveiling the complex structure-property correlation of defects in 2D materials based on high throughput datasets
Authors: Huang Pengru , Lukin Ruslan , Faleev Maxim , Kazeev Nikita , Al-Maeeni Abdalaziz Rashid , Andreeva Daria V. , Ustyuzhanin Andrey , Tormasov Alexander , Castro Neto A. H. , Novoselov Kostya S. 
Published: February 2023

AbstractModification of physical properties of materials and design of materials with on-demand characteristics is at the heart of modern technology. Rare application relies on pure materials—most devices and technologies require careful design of materials properties through alloying, creating heterostructures of composites, or controllable introduction of defects. At the same time, such designer materials are notoriously difficult to model. Thus, it is very tempting to apply machine learning methods to such systems. Unfortunately, there is only a handful of machine learning-friendly material databases available these days. We develop a platform for easy implementation of machine learning techniques to materials design and populate it with datasets on pristine and defected materials. Here we introduce the 2D Material Defect (2DMD) datasets that include defect properties of represented 2D materials such as MoS2, WSe2, hBN, GaSe, InSe, and black phosphorous, calculated using DFT. Our study provides a data-driven physical understanding of complex behaviors of defect properties in 2D materials, holding promise for a guide to the development of efficient machine learning models. In addition, with the increasing enrollment of datasets, our database could provide a platform for designing materials with predetermined properties.
Predicting chemical exfoliation: fundamental insights into the synthesis of MXenes
Authors: Björk Jonas , Halim Joseph , Zhou Jie , Rosen Johanna 
Published: February 2023

AbstractThe factors controlling the top-down synthesis of MXenes, by selectively removing the A elements from parent MAX phases, is still under debate. In particular, understanding why some MAX phases can be used for creating MXenes, while others cannot, is of immense interest and would greatly support computational screening and identification of new two-dimensional materials that could also be created by chemical exfoliation. Here we computationally study the etching of MAX phases in hydrofluoric acid, considering the complete exfoliation process and competing processes during the initial steps of the synthesis. The results are compared to experiments and MAX phases successfully converted to MXenes, as well as so far unsuccessful attempts, including previously unpublished experimental data, rationalizing why some MAX phases are exfoliable while others are not. Our results provide an improved understanding of the synthesis of MXenes under acid conditions, anticipated to be vital for our ability to discover novel two-dimensional materials.
When the dynamical writing of coupled memories with reinforcement learning meets physical bounds
Authors: Jules Théo , Michel Laura , Douin Adèle , Lechenault Frédéric 
Published: February 2023

AbstractBits manipulation in traditional memory writing is commonly done through quasi-static operations. While simple to model, this method is known to reduce memory capacity. We demonstrate how a reinforcement learning agent can exploit the dynamical response of a simple multi-bit mechanical system to restore its memory. To do so, we introduce a model framework consisting of a chain of bi-stable springs manipulated on one end by the external action of the agent. We show that the agent learns how to reach all available states for three springs, even though some states are not reachable through adiabatic manipulation, and that training is significantly improved using transfer learning techniques. Interestingly, the agent also points to an optimal system design by taking advantage of the underlying physics. Indeed, the control time exhibits a non-monotonic dependence on the internal dissipation, reaching a minimum at a cross-over shown to verify a mechanically motivated scaling relation.
Understanding congestion propagation by combining percolation theory with the macroscopic fundamental diagram
Authors: Ambühl Lukas , Menendez Monica , González Marta C. 
Published: February 2023

AbstractThe science of cities aims to model urban phenomena as aggregate properties that are functions of a system’s variables. Following this line of research, this study seeks to combine two well-known approaches in network and transportation science: (i) The macroscopic fundamental diagram (MFD), which examines the characteristics of urban traffic flow at the network level, including the relationship between flow, density, and speed. (ii) Percolation theory, which investigates the topological and dynamical aspects of complex networks, including traffic networks. Combining these two approaches, we find that the maximum number of congested clusters and the maximum MFD flow occur at the same moment, precluding network percolation (i.e. traffic collapse). These insights describe the transition of the average network flow from the uncongested phase to the congested phase in parallel with the percolation transition from sporadic congested links to a large, congested cluster of links. These results can help to better understand network resilience and the mechanisms behind the propagation of traffic congestion and the resulting traffic collapse.
The Chemical Story of Olive Oil: From Grove to Table
Authors: Blatchly Richard , Delen Zeynep , O'Hara Patricia 
Published: February 2023

Despite the growing interest in olive oil, most people know very little about what it is or how it is made. This book provides a comprehensive treatment of olive oil from the tree to table, from a molecular and personal perspective.
Growers often do not know what is happening at a molecular level or why certain practices produce superior or inferior results, for example, why adjusting a temperature rewards them with winning oils. This book aims to provide some of the answers as well as the importance of the chemicals responsible for the flavour and health effects. Readers will also get a deeper understanding of what makes an extra virgin olive oil authentic and how scientists are helping to fight fraud regarding this valuable commodity.
Including anecdotes from growers of olives and producers of oils, the authors provide an accessible text for a wide audience from food science students to readers interested in the human story of olive oil production.
Improving anion-exchange efficiency and spectrum stability of perovskite quantum dots via an Al3+ bonding-doping synergistic effect
Authors: Yang Linxiang , Shan Qingsong , Zhang Shuai , Zhou Yihui , Li Yan , Zou Yousheng , Zeng Haibo 
Published: February 2023

We report an Al3+ bonding-doping synergistic strategy by anion exchange for stable deep-blue perovskite QD and QLED. The QD exhibits superior stability against moisture and electric field, the spectrum-stable QLED achieves an EQE of 1.38% at 463 nm.
SAE‐CenterNet: Self‐attention enhanced CenterNet for small dense object detection
Authors: Li Yaoshun , Liu Lizhi , Lu Tongwei 
Published: February 2023

AbstractThe existing object detection models have not been sufficiently optimized for small dense objects. One of the most common solutions is to extract multi‐scale features via feature pyramid network (FPN). However, the information loss of downsampling in multi‐scale feature extraction will seriously affect the detection accuracy. Therefore, a dynamic attention convolution (DAC) for downsampling is developed, which can embed regional information for each single pixel. Besides, an attention fusion module (AFM) is also designed to alleviate the data inconsistency from different layers during multi‐scale feature fusion. Based on these, the proposed model, SAE‐CenterNet, has achieved optimal performance in the mainstream object detection models on the small dense rebar dataset. For example, with 6 FPS decreasing, the , , and of SAE‐CenterNet is 87.3%, 57.6%, 88.6% and 67.2%, respectively, which are 8.0%, 13.5%, 8.3% and 10.4% higher than the baseline CenterNet, respectively.
Sensitivity assessment of a novel earth fault location method with optimally placed distributed measurements for MV networks
Authors: Bach Alexandre , Le Trung Dung , Petit Marc 
Published: February 2023

AbstractThis paper extends the study of a zero‐sequence impedance‐based fault location method (FLM) designed for medium voltage (MV) distribution feeders whose principle has been presented in a previous work Bach et al. This method is able to locate any type of earth fault with any type of neutral grounding inside a convex set of nodes forming the solution area. The total length of the lines inside this area is statistically computable a priori and depends only on the number and location of additional voltage measurements deployed on some remote end secondary substations. To be efficiently applied to the most challenging rural feeders presenting a lot of ramifications, simulations have shown a need for synchronized measurements, such as the ones obtained using phasor measurement units. Besides, this paper addresses the coupling potential of this method with more traditional ones such as Takagi‐based FLMs to enhance the performances of both, solving the multiple estimation problem while potentially locating the fault within one node. Finally, an extensive sensitivity analysis has been carried out, showing a good robustness with respect to impedance estimation errors or fault impedance values while showing the need for synchronization, especially on some remote measurement locations.
A novel 24 GHz circularly polarised metasurface rectenna
Authors: Huang Wei , Du Jinxin , Yang Xue‐Xia , Che Wenquan , Gao Steven 
Published: February 2023

AbstractA novel 24 GHz circularly polarised metasurface rectenna for wireless power transmission is designed in this study. Based on experimental measurements and retro‐simulation, an effective approach is proposed to extract the parasitic parameters of a Schottky diode. A highly efficient millimetre wave rectifier with a measured efficiency of 63% is constructed based on the exact equivalent circuit parameters of a diode. A circularly polarised metasurface antenna is adopted as the receiving antenna, and the gain is enhanced by introducing metal vias around the metasurface. The antenna and the rectifier are connected directly via a microstrip line. Measurements show that the metasurface antenna has a gain of 11.3 dBic and an axial ratio of 2.5 dB at 24 GHz. The measured conversion efficiency of the rectenna reaches 63% at 300 Ω load when the input power is 15.2 dBm. The rectenna has the advantages of low profile, which can be conformal to the electrical equipment.
Cosmic-ray sputtering of interstellar ices in the electronic regime
Authors: Dartois E. , Chabot M. , da Costa C. A. P. , Nguyen T. , Rojas J. , Duprat J. , Augé B. , Domaracka A. , Rothard H. , Boduch P. 
Published: February 2023

Aims. With this article, we aim to provide the sputtering yields for molecular species of potential astrophysical interest and in the electronic regime of interaction characteristic of cosmic rays. We specifically target molecules that are constitutive of interstellar ice mantles.Methods. We used a compendium of existing data on electronic sputtering to calculate the prefactors leading to the generalisation of the stopping-power-dependent sputtering yield for many species condensing at low temperature. In addition, we present new experimental results to constrain the yield for solid CH4, C6, and CH3CN.Results. Electronic sputtering is constrained using literature data for H2, HD, D2, Ne, N2, CO, Ar, O2, Kr, Xe, CO2, SO2, NH3, S, H2O, D2O, CH3OH, Leucine, C20H12, C24H12, and C60. A first-order relation with the sublimation enthalpy is derived, which allows us to predict the sputtering yield within an order of magnitude for most species. The fluctuations around the mean are partly assignable to the differences in resilience towards radiolysis for individual species, and partly to the micro-physics details of the energy transfer to the lattice.
Application of a neural network classifier for the generation of clean Small Magellanic Cloud stellar samples
Authors: Jiménez-Arranz Ó. , Romero-Gómez M. , Luri X. , Masana E. 
Published: February 2023

Context. Previous attempts to separate Small Magellanic Cloud (SMC) stars from the Milky Way (MW) foreground stars are based only on the proper motions of the stars.
Aims. In this paper, we aim to develop a statistical classification technique to effectively separate the SMC stars from the MW stars using a wider set of Gaia data. We aim to reduce the possible contamination from MW stars compared to previous strategies.
Methods. The new strategy is based on a neural network classifier, applied to the bulk of the Gaia DR3 data. We produce three samples of stars flagged as SMC members, with varying levels of completeness and purity, obtained by application of this classifier. Using different test samples, we validated these classification results and compared them with the results of the selection technique employed in the Gaia Collaboration papers, which was based solely on the proper motions.
Results. The contamination of the MW in each of the three SMC samples is estimated to be in the 10–40% range; the “best case” in this range is obtained for bright stars (G < 16), which belong to the Vlos sub-samples, and the “worst case” for the full SMC sample determined by using very stringent criteria based on StarHorse distances. A further check based on the comparison with a nearby area with uniform sky density indicates that the global contamination in our samples is probably close to the low end of the range, around 10%.
Conclusions. We provide three selections of SMC star samples with different degrees of purity and completeness, for which we estimate a low contamination level and which we have successfully validated using SMC RR Lyrae, SMC Cepheids, and SMC-MW StarHorse samples.
Fragmentation of SO2q+ (q = 2–4) induced by 1 keV electron collision
Authors: Chen Lei , Wang Enliang , Zhao Wenchao , Gong Maomao , Shan Xu , Chen Xiangjun 
Published: February 2023

We report an investigation on the fragmentation dynamics of SO2q+ (q = 2–4) induced by 1 keV electron collision utilizing an ion momentum imaging spectrometer. Six complete Coulomb explosion channels were observed using the time-of-flight correlation map. The kinetic energy release distributions for these channels were obtained and compared with those available in the literature. The fragmentation mechanisms of the three-body dissociation channels were analyzed by the Dalitz plots and Newton diagrams. Both concerted breakup and sequential fragmentation pathways were identified in the channel SO23+ → O+ + O+ + S+, whereas only the concerted breakup mechanism was confirmed for the channels SO24+ → O+ + O+ + S2+ and SO24+ → O2+ + O+ + S+. Using the Coulomb explosion model, we determined the molecular geometry from the concerted fragmentation channels, and the obtained bond lengths and angles from the higher kinetic energy release peaks are close to that of the neutral SO2 obtained by high-level quantum chemical calculation. The present results indicate that the electron impact experiment is a potential tool for the Coulomb explosion imaging of small molecules.
Endogenous circadian reporters reveal functional differences of
PERIOD
paralogs and the significance of PERIOD:CK1 stable interaction
Authors: Park Jiyoung , Lee Kwangjun , Kim Hyeongseok , Shin Heungsop , Lee Choogon 
Published: February 2023

Adverse consequences from having a faulty circadian clock include compromised sleep quality and poor performance in the short-term, and metabolic diseases and cancer in the long-term. However, our understanding of circadian disorders is limited by the incompleteness of our molecular models and our dearth of defined mutant models. Because it would be prohibitively expensive to develop live animal models to study the full range of complicated clock mechanisms, we developed
PER1-luc
and
PER2-luc
endogenous circadian reporters in a validated clock cell model, U-2 OS, where the genome can be easily manipulated, and functional consequences of mutations can be accurately studied. When major clock genes were knocked out in these cells, circadian rhythms were modulated similarly compared with corresponding mutant mice, validating the platform for genetics studies. Using these reporter cells, we uncovered critical differences between two paralogs of
PER
. Although
PER1
and
PER2
are considered redundant and either one can serve as a pacemaker alone, they were dramatically different in biochemical parameters such as stability and phosphorylation kinetics. Consistently, circadian phase was dramatically different between
PER1
and
PER2
knockout reporter cells. We further showed that the stable binding of casein kinase1δ/ε to PER is not required for PER phosphorylation itself, but is critical for delayed timing of phosphorylation. Our system can be used as an efficient platform to study circadian disorders associated with pathogenic mutations and their underlying molecular mechanisms.
Recent progress on polyphenylene oxide-based thermoset systems for high-performance copper-clad laminates
Authors: Qin Yijing , Yu Xueyi , Fang Zeming , He Xiao , Qu Muchao , Han Meng , Lu Dong , Xue Ke , Wang Ke 
Published: February 2023

Abstract
With the rapid development of electronic information technology in the 5G era towards high integration, short propagation delay, and elevated assembly temperatures, more academic and industrial attention has been focused on high-frequency and high-speed copper-clad laminates (CCLs). Compared with conventional polymeric matrices, thermoset polyphenylene oxide (PPO) has become one of the most attractive resins applied in high-performance CCLs (HPCCLs) because of its excellent comprehensive properties, including outstanding dielectric properties, high thermal stability, great processibility, and low moisture absorption, etc. This review focuses on the history of the development of PPO prepolymers/oligomers, PPO-based thermoset resin systems, and PPO/inorganic filler composites to optimize the dielectric constant, dielectric loss, thermal conductivity, coefficient of thermal expansion, and mechanical properties. Moreover, some current challenges of PPO-based thermoset systems have been identified, such as developing feasible solutions to ensure the anti-aging properties for long-term reliability under harsh environments of high temperature, high humidity, and even high-frequency electromagnetic radiation. In general, more in-depth investigations of PPO-based thermoset systems for HPCCLs are required in the future.