bluuebunny/crossref_metadata_2025 huggingface dataset:
Speech-derived haptic stimulation enhances speech recognition in a multi-talker background
Authors: Răutu I. Sabina , De Tiège Xavier , Jousmäki Veikko , Bourguignon Mathieu , Bertels Julie
Published: October 2023

Speech understanding, while effortless in quiet conditions, is challenging in noisy environments. Previous studies have revealed that a feasible approach to supplement speech-in-noise (SiN) perception consists in presenting speech-derived signals as haptic input. In the current study, we investigated whether the presentation of a vibrotactile signal derived from the speech temporal envelope can improve SiN intelligibility in a multi-talker background for untrained, normal-hearing listeners. We also determined if vibrotactile sensitivity, evaluated using vibrotactile detection thresholds, modulates the extent of audio-tactile SiN improvement. In practice, we measured participants’ speech recognition in a multi-talker noise without (audio-only) and with (audio-tactile) concurrent vibrotactile stimulation delivered in three schemes: to the left or right palm, or to both. Averaged across the three stimulation delivery schemes, the vibrotactile stimulation led to a significant improvement of 0.41 dB in SiN recognition when compared to the audio-only condition. Notably, there were no significant differences observed between the improvements in these delivery schemes. In addition, audio-tactile SiN benefit was significantly predicted by participants’ vibrotactile threshold levels and unimodal (audio-only) SiN performance. The extent of the improvement afforded by speech-envelope-derived vibrotactile stimulation was in line with previously uncovered vibrotactile enhancements of SiN perception in untrained listeners with no known hearing impairment. Overall, these results highlight the potential of concurrent vibrotactile stimulation to improve SiN recognition, especially in individuals with poor SiN perception abilities, and tentatively more so with increasing tactile sensitivity. Moreover, they lend support to the multimodal accounts of speech perception and research on tactile speech aid devices.
Pushing the limits of PLA by exploring the power of MWCNTs in enhancing thermal, mechanical properties, and weathering resistance
Authors: Younus Mohammed M. , Naguib Hamdy M. , Fekry Mohamed , Elsawy Moataz A.
Published: October 2023

The present study focuses on enhancing the mechanical, thermal, and degradation behavior of polylactic acid (PLA) by adding carbon nanotubes (CNTs) with different concentrations of 0.5, 1, 3, and 5%. The CNTs were prepared using catalytic chemical vapor deposition, and the prepared PLA/CNTs nanocomposite films were characterized using techniques such as FT-IR, Raman spectroscopy, TGA, SEM, and XRD. The distinct diffraction patterns of multi-walled carbon nanotubes (MWCNTs) at 2θ angles of 25.7° and 42.7° were no longer observed in the prepared nanocomposites, indicating uniform dispersion of MWCNTs within the PLA matrix. The presence of MWCNTs enhanced the crystallinity of PLA as the CNT loading increased. Mechanical tests demonstrated that incorporating CNTs positively influenced the elongation at the break while decreasing the ultimate tensile strength of PLA. The PLA-3%CNTs composition exhibited the highest elongation at break (51.8%) but the lowest tensile strength (64 MPa). Moreover, thermal gravimetric analysis confirmed that the prepared nanocomposites exhibited greater thermal stability than pure PLA. Among the nanocomposites, PLA-5% CNTs exhibited the highest thermal stability. Furthermore, the nanocomposites demonstrated reduced surface degradation in accelerated weathering tests, with a more pronounced resilience to UV radiation and moisture-induced deterioration observed in PLA-3% CNTs.
Graph Laplacian-based spectral multi-fidelity modeling
Authors: Pinti Orazio , Oberai Assad A.
Published: October 2023

Low-fidelity data is typically inexpensive to generate but inaccurate, whereas high-fidelity data is accurate but expensive. To address this, multi-fidelity methods use a small set of high-fidelity data to enhance the accuracy of a large set of low-fidelity data. In the approach described in this paper, this is accomplished by constructing a graph Laplacian from the low-fidelity data and computing its low-lying spectrum. This is used to cluster the data and identify points closest to the cluster centroids, where high-fidelity data is acquired. Thereafter, a transformation that maps every low-fidelity data point to a multi-fidelity counterpart is determined by minimizing the discrepancy between the multi- and high-fidelity data while preserving the underlying structure of the low-fidelity data distribution. The method is tested with problems in solid and fluid mechanics. By utilizing only a small fraction of high-fidelity data, the accuracy of a large set of low-fidelity data is significantly improved.
CT and MR for bone mineral density and trabecular bone score assessment in osteoporosis evaluation
Authors: Lee Haein , Park Sunghoon , Kwack Kyu-Sung , Yun Jae Sung
Published: October 2023

Dual energy X-ray absorptiometry (DXA) is widely used modality for measuring bone mineral density (BMD). DXA is used to measure the quantitative areal BMD of bone, but has the disadvantage of not reflecting the bone architecture. To compensate for this disadvantage, trabecular bone score (TBS), a qualitative parameter of trabecular microarchitecture, is used. Meanwhile, there have been recent attempts to diagnose osteoporosis using the Hounsfield unit (HU) from CT and MR-based proton density fat fraction (PDFF) measurements. In our study, we aimed to find out the correlation between HU/PDFF and BMD/TBS, and whether osteoporosis can be diagnosed through HU/PDFF. Our study revealed that the HU value showed a moderate to good positive correlation with BMD and TBS. PDFF showed a fair negative correlation with BMD and TBS. In diagnosing osteopenia and osteoporosis, the HU value showed good performance, whereas the PDFF showed fair performance. In conclusion, both HU values and PDFF can play a role in predicting BMD and TBS. Both HU values and PDFF can be used to predict osteoporosis; further, CT is expected to show better results.
Dental injury offenses and compensation imposed by Spanish courts, before and during Covid-19. A cross-sectional study
Authors: Serrano Ana Isabel , Aragoneses Javier , Suárez Ana , Rodríguez Cinthia , Aragoneses Juan Manuel
Published: October 2023

Injuries to the dentofacial region caused by third parties can affect physiological, sensory and esthetic functions with legal repercussions. The personal and social circumstances generated by Covid-19 and the governmental measures taken to control it, have increased the risk factors for violence and with it, the resulting injury rate. The aim of the present investigation was to compare the amount of civil liability for dental injury crimes agreed by Spanish courts, in certain Autonomous Communities, before and during the pandemic situation caused by Covid-19. For this purpose, a analytic cross-sectional study was carried out by analyzing sentences from the database of the Judicial Documentation Center. A comparison of means (one-way ANOVA) was used on the amount of compensation between the different years, and between the Autonomous Communities of Madrid, Catalonia Cataluña, Andalusia, the Canary Islands and the Valencian Community. It was observed that the year 2020 stood out for the increase in the number of cases of dental injury offenses. For its part, the Autonomous Community of Andalusia showed the highest amount of compensation during the pandemic, although the highest number of cases corresponded to the Community of Madrid. The statistical analysis yielded a probability of more than 0.05, which eliminated the possibility of significant differences in each of the comparisons.
Behavioral-dependent recursive movements and implications for resource selection
Authors: Bakner Nicholas W. , Collier Bret A. , Chamberlain Michael J.
Published: October 2023

Within home ranges, animals repeatedly visit certain areas. Recursive movement patterns are widespread throughout the animal kingdom, but are rarely considered when developing resource selection models. We examined how behavioral state-dependent recursive movements influenced reource selection of eastern wild turkey (Meleagris gallopavo silvestris) broods as they aged from day 1 to 28. Because broods become more plastic in behaviors once they begin roosting off the ground, we separated data into broods that were ground roosting (1–13 days) and tree roosting (14–28 days). We used Hidden Markov Models to identify 2 behavioral states (restricted and mobile). We extracted state-specific recursive movements based on states and specific step lengths, which we integrated into a step selection analysis to evaluate resource selection. We found that in a restricted state, ground roosting broods spent less time in areas of mixed pine-hardwoods and more time in areas with greater vegetation density. Tree roosting broods revisited areas closer to shrub/scrub landcover types, and areas with greater vegetation density. Tree roosting broods also spent less time near mixed pine-hardwoods, while spending more time in areas with greater vegetation density. We found that in a mobile state, ground roosting broods revisited areas closer to secondary roads and mixed pine-hardwoods, but farther from hardwoods. Tree roosting broods revisited areas farther from secondary roads and with greater vegetation density. Tree roosting broods also spent more time in areas closer to pine. Resource selection varied depending on behavioral state and recursive movements. However, revisitation and residence time impacted selection in both ground and tree roosting broods. Our findings highlight the need to consider how behaviors can influence movement decisions and ultimately resource selection.
Expression of polymeric immunoglobulin receptor (PIGR) and the effect of PIGR overexpression on breast cancer cells
Authors: Asanprakit Wichitra , Lobo Dileep N. , Eremin Oleg , Bennett Andrew J.
Published: October 2023

Polymeric immunoglobulin receptor (PIGR) has a major role in mucosal immunity as a transporter of polymeric immunoglobulin across the epithelial cells. The aim of this study was to determine the effect of PIGR on cellular behaviours and chemo-sensitivity of MCF7 and MDA-MB468 breast cancer cell lines. Basal levels of PIGR mRNA and protein expression in MCF7 and MDA-MB468 cells were evaluated by real time quantitative polymerase chain reaction and Western blotting, respectively. MCF7/PIGR and MDA-MB468/PIGR stable cell lines, overexpressing the PIGR gene, were generated using a lentiviral vector with tetracycline dependent induction of expression. Cell viability, cell proliferation and chemo-sensitivity of PIGR transfected cells were evaluated and compared with un-transfected cells to determine the effect of PIGR overexpression on cell phenotype. The levels of PIGR mRNA and protein expression were significantly higher in MDA-MB468 cells than in MCF7 cells (380-fold, p < 0.0001). However, the differential expression of PIGR in these two cell lines did not lead to significant differences in chemosensitivity. Viral overexpression of PIGR was also not found to change any of the parameters measured in either cell line. PIGR per se did not affect cellular behaviours and chemosensitivity of these breast cancer cell lines.
Zinc-sensitive MRI contrast agents: importance of local probe accumulation in zinc-rich tissues
Authors: Malikidogo Kyangwi P. , Isaac Manon , Uguen Adrien , Même Sandra , Pallier Agnès , Clémençon Rudy , Morfin Jean-François , Lacerda Sara , Tóth Éva , Bonnet Célia S.
Published: October 2023

We present the contradictory in vitro and in vivo behaviour of a Gd3+-based contrast agent that respond to Zn2+ upon interaction with Human Serum Albumin.
Ni aptamer: DNA mimic of His-tag to recognize Ni-NTA
Authors: Jahan Raunak , Silwal Achut Prasad , Thennakoon Siddhartha Kalpa Samadhi , Arya Satya Prakash , Postema Rick Mason , Timilsina Hari , Reynolds Andrew Michael , Tan Xiaohong
Published: October 2023

We introduced Ni Apt as the first aptamer with a characterized dissociation constant for recognizing Ni-NTA.
Enhanced circularly polarized luminescence dissymmetry of [Ru(bpy)3]2+ complexes in a 3D chiral framework: a study of transparent thin films
Authors: Zhang Songwei , Schnable David , Elgin Jocelyn , Ung Gaël , Wu Yiying
Published: October 2023

A “chiral-in-chiral” structure is formed from chiral luminescent [Ru(bpy)3]2+ complexes within chiral inorganic frameworks for circularly polarized luminescence.
Towards maximizing the In2O3/m-ZrO2 interfaces for CO2-to-methanol hydrogenation
Authors: Luo Alin , Chang Haohao , Gao Feifan , Liu Yongmei , He Heyong , Cao Yong
Published: October 2023

The incorporation of diethylenetriaminepenta-acetic acid (DTPA) as a chelating agent resulted in abundant Zr–O–In structures at the catalyst interface, leading to exceptional CO2-to-methanol activity.
Modulating active oxygen species on α-MnO2 with K and Pb for SCR of NO at low temperatures
Authors: Yang Gang , Luo Xiang , Liu Shuai , Sun Chenggong , Wu Tao
Published: October 2023

In this study, a completely new mechanism for the effect of K and Pb on α-MnO2 was proposed. The findings provide valuable insights on the roles of active oxygen species and oxygen vacancies in the low-temperature SCR process.
Tuning the catalytic performance of CaSnO3 by developing an S-scheme p–n heterojunction through Ag6Si2O7 doping
Authors: Shah Navid Hussain , Abbas Muhammad , Qasim Muhammad , Sulman Muhammad , Imran Muhammad , Azmat Sohail , Cui Yanyan , Wang Yaling
Published: October 2023

Perovskites, especially alkaline earth stannates, have drawn enormous interest from the research community owing to their low chemical toxicity, environmental friendliness, excellent optical properties, and good thermal and chemical stabilities.
Preface: Iontronics: from fundamentals to ion-controlled devices
Authors: Faez Sanli , Lemay Serge G.
Published: October 2023

The Scientific Committee, from left to right: Professors Susan Perkin, Monica Olvera de la Cruz, Serge G. Lemay, René van Roij and Sanli Faez.
Seaweed intake modulates the association betweenVIPR2variants and the incidence of metabolic syndrome in middle-aged Koreans
Authors: Park Haeun , Jeon Hyunyu , Lee Kyung Ju , Kim Choong-Gon , Shin Dayeon
Published: October 2023

In men with the GG genotype of rs6950857, the highest quintile of seaweed consumption was associated with a decreased incidence of MetS compared with that of the lowest quintile (hazard ratio, 0.78; 95% confidence interval, 0.62–0.98).
Polyphenols as NLRP3 inflammasome modulators in cardiometabolic diseases: a review ofin vivostudies
Authors: Villalva Marisol , Martínez-García Juan José , Jaime Laura , Santoyo Susana , Pelegrín Pablo , Pérez-Jiménez Jara
Published: October 2023

Steps of the NLRP3 inflammasome activation pathway where some selected polyphenols have shown a positive modulatory effect on different cardiometabolic alterations.
Dehydration of gypsum waste to recyclable anhydrite using a nano-film reservoir under ambient conditions
Authors: Wang Chunli , Li Wenjing , Gou Chunli , Zhang Zhihao , Lin Zhang , Zhang Jing
Published: October 2023

A 39 nm thick sulfuric acid film (NSF) with extremely low water activity was deposited on gypsum particles to enable the phase transformation from gypsum to anhydrite via recrystallization at room temperature.
Developing a green and efficient biosynthesis system for l-aspartic acid by addressing enzyme imbalance and catalysis-extraction circulation processes
Authors: Wang Chang , Wang Xiangyu , Zhou Zhemin , Liu Zhongmei
Published: October 2023

A catalysis-extraction circulation process for production of l-aspartic acid is presented, which is significantly improved compared to the state-of-the-art green processes, and is environmentally friendly and cost-effective.
Reservoir computing using back-end-of-line SiC-based memristors
Authors: Guo Dongkai , Kapur Omesh , Dai Peng , Han Yisong , Beanland Richard , Jiang Liudi , de Groot C. H. (Kees) , Huang Ruomeng
Published: October 2023

This work experimentally implements a physical reservoir computing system using a back-end-of-line SiC thin film based memristor to achieve pattern recognition with high accuracy.
Unveiling protonated form of 2,6-di-m-phenylpyridine embedded isosmaragdyrin analogue and its organo-Pd(ii) complex
Authors: Pradhan Sourav Ranjan , Murugavel M. , Chitranshi Sangya , Kim Gakhyun , Kim Dongho , Das Mainak , Srinivasan A.
Published: October 2023

Anion bound and organo-Pd(ii) complexes of isosmaragdyrin with N3C2 core are reported, where the structures are confirmed by single-crystal X-ray analysis.
A highly efficient light-driven non-enzymatic glucose sensor based on AuNi nanodendrites
Authors: Wang Lanfang , Ding Ruifang , Hao Yanqing , Li Yujia , Liu Wenjiao , Lu Wenbo , Xu Xiaohong
Published: October 2023

A novel light-driven non-enzymatic glucose sensor based on AuNi nanodendrites has been successfully constructed and applied in glucose detection.
Ionic liquids containing half-sandwich ruthenium complexes: in situ interconversions via photochemical and thermal ligand exchange
Authors: Mochida Tomoyuki , Maekawa Syou , Sumitani Ryo
Published: October 2023

Ionic liquids with cationic half-sandwich ruthenium complexes with various auxiliary ligands have been synthesized. They undergo interconversion through in situ ligand exchange, either photochemically or thermally.
Thin-film conformal fluorescent SU8-phenylenediamine
Authors: Barhum Hani , Kolchanov Denis S. , Attrash Mohammad , Unis Razan , Alnis Janis , Salgals Toms , Yehia Ibrahim , Ginzburg Pavel
Published: October 2023

On the surface and volume.
A resistance-driven H2 gas sensor: high-entropy alloy nanoparticles decorated 2D MoS2
Authors: Mondal Bidesh , Zhang Xiaolei , Kumar Sumit , Long Feng , Katiyar Nirmal Kumar , Kumar Mahesh , Goel Saurav , Biswas Krishanu
Published: October 2023

The rising demand for H2 in everyday applications necessitates robust sensors for early detection.
Organic photoredox catalyzed C(sp3)–H functionalization of saturated aza-heterocycles via a cross-dehydrogenative coupling reaction
Authors: Zhang Yi-Fan , Chen Han-Nan , Xiao Yi , Cui Zhencun , Wang Wei David , Xu Guo-Qiang
Published: October 2023

A novel organic photoredox catalyzed CDC reaction of aza-heterocycles with various groups including indole, naphthol, phenol, pyrrole, furyl, nitromethyl, and cyano, was established, providing a concise way to access α-functionalized cyclic amines.
Insight into a pure spinel Co3O4 and boron, nitrogen, sulphur (BNS) tri-doped Co3O4-rGO nanocomposite for the electrocatalytic oxygen reduction reaction
Authors: Bhatti Afia Kanwal , Jabeen Naila , Bashir Amna , Khan Latif U. , Bokhari Syeda Wishal , Akhter Zareen
Published: October 2023

Herein, we propose a smart composite nano system that can be used in a sustainable and dichotomous manner to resolve energy crises.
Geometry guided crystallization of anisotropic DNA origami shapes
Authors: Huang Shujing , Ji Min , Wang Yong , Tian Ye
Published: October 2023

The anisotropic E-octa DNA origami frames with non-specific connections are crystallized to form simple cubic and simple tetragonal superlattices by conducting multiple annealing processes and increasing the rigidity of the connections.
Temperature dependence of the viscoelastic properties of a natural gastropod mucus by Brillouin light scattering spectroscopy
Authors: Hanlon Dillon F. , Clouter Maynard J. , Andrews G. Todd
Published: October 2023

The temperature-dependent viscoelastic properties and phase behaviour of snail mucus implies that water molecules bind to glycoproteins above freezing, reducing their ability to facilitate freezing, causing the freezing point depression and the coexistence of liquid and solid phases.
New pilot protection method based on the current fault component waveform similarity
Authors: Gao Shuping , Zheng Han , Gao Yue , Song Guobing
Published: October 2023

In order to improve the ability of the modular multi‐level converter to quickly clear and isolate faults in the multi‐terminal flexible DC grid, this paper analyzes the characteristics of current faults in the multi‐terminal flexible direct current grid, introduces the comprehensive distance of current fault waveform, and proposes a line protection method based on the similarity of current fault waveform. This protection method firstly uses Euclid Dynamic Time Warping (DTW) distance and entropy weight method to process electrical quantity signals, calculates the comprehensive distance of current fault waveform of two converter stations, and builds the protection criterion based on the similarity of current fault waveform. Then, the fault identification is realized by using the calculated comprehensive distance, and the fault pole identification is realized by using the ratio of comprehensive distance between positive and negative poles. Finally, PSCAD was used to build a simulation model to output the fault data under different fault conditions, and MATLAB was used to process the fault data to verify the protection algorithm. The simulation results show that the proposed method has good resistance to high resistance, and its rapidity and adaptability are further improved. Compared with other similarity methods, this method combines Euclidean DTW distance and entropy method to process the signal, realizes the fault pole identification, and can still operate correctly under the interference of 500 Ω transition resistance and 20 dB noise ratio. The research results will provide a theoretical basis for the safe and reliable operation of flexible DC power grid.
A plausible link between dynamically unsettled molecular gas and the radio jet in NGC 6328
Authors: Papachristou M. , Dasyra K. M. , Fernández-Ontiveros J. A. , Audibert A. , Ruffa I. , Combes F. , Polkas M. , Gkogkou A.
Published: October 2023

We report the detection of outflowing molecular gas at the center of the nearby radio galaxy NGC6328 (z = 0.014), which has a gigahertz-peaked spectrum radio core and a compact (2 pc) young double radio lobe tracing jet. Utilizing Atacama Large Millimeter/submillimeter Array (ALMA) CO(3 − 2) and CO(2 − 1) observations, as well as a novel code developed to fit the 3D gas distribution and kinematics, to study the molecular gas kinematics, we find that the bulk of the gas is situated within a highly warped disk structure, most likely the result of a past merger event. Our analysis further uncovers, within the inner regions of the gas distribution (R < 300 pc) and at a position angle aligning with that of the radio jet (150°), the existence of two anti-diametric molecular gas structures kinematically detached from the main disk. These structures most likely trace a jet-induced cold gas outflow with a total lower limit mass of 2 × 106 M⊙ mass, corresponding to an outflow rate of 2 M⊙ yr−1 and a kinetic power of 2.7 × 1040 erg s−1. The energy required to maintain such a molecular outflow is aligned with the mechanical power of the jet.
Effect of low-mass galaxy interactions on their star formation
Authors: Subramanian Smitha , Mondal Chayan , Kalari Venu
Published: October 2023

According to the Λ cold dark matter model of galaxy formation, the hierarchical assembly process is scale-free and interactions between galaxies in all mass ranges are expected. The effects of interactions between dwarf galaxies on their evolution are not well understood. In this study, we aim to understand the effect of low-mass galaxy interactions on their star formation rate (SFR). We estimated the SFR of 22 interacting and 36 single gas-rich dwarf galaxies in the Lynx-Cancer void region using their far-ultraviolet (FUV) images from the GALEX mission. We find an enhancement in SFR by a factor of 3.4 ± 1.2 for interacting systems compared to single dwarf galaxies in the stellar mass range of 107–108 M⊙. Our results indicate that dwarf–dwarf galaxy interactions can lead to an enhancement in their SFR. These observations are similar to the predictions based on the simulations of dwarf galaxies at lower redshifts. Future deeper and higher-spatial-resolution UV studies will help us to understand the effect of dwarf galaxy interactions on the spatial distribution of star forming clumps and to identify star formation in tidal tails.
Galaxy mergers in Subaru HSC-SSP: A deep representation learning approach for identification, and the role of environment on merger incidence
Authors: Omori Kiyoaki Christopher , Bottrell Connor , Walmsley Mike , Yesuf Hassen M. , Goulding Andy D. , Ding Xuheng , Popping Gergö , Silverman John D. , Takeuchi Tsutomu T. , Toba Yoshiki
Published: October 2023

Context.Galaxy mergers and interactions are an important process within the context of galaxy evolution, however, there is still no definitive method which identifies pure and complete merger samples is still not definitive. A method for creating such a merger sample is required so that studies can be conducted to deepen our understanding of the merger process and its impact on galaxy evolution.

Aims.In this work, we take a deep-learning-based approach for galaxy merger identification in Subaru HSC-SSP, using deep representation learning and fine-tuning, with the aim of creating a pure and complete merger sample within the HSC-SSP survey. We can use this merger sample to conduct studies on how mergers affect galaxy evolution.

Methods.We used Zoobot, a deep learning representation learning model pretrained on citizen science votes on Galaxy Zoo DeCALS images. We fine-tuned Zoobot for the purpose of merger classification of images of SDSS and GAMA galaxies in HSC-SSP public data release 3. Fine-tuning was done using ∼1200 synthetic HSC-SSP images of galaxies from the TNG simulation. We then found merger probabilities on observed HSC images using the fine-tuned model. Using our merger probabilities, we examined the relationship between merger activity and environment.

Results.We find that our fine-tuned model returns an accuracy on the synthetic validation data of ∼76%. This number is comparable to those of previous studies in which convolutional neural networks were trained with simulation images, but with our work requiring a far smaller number of training samples. For our synthetic data, our model is able to achieve completeness and precision values of ∼80%. In addition, our model is able to correctly classify both mergers and non-mergers of diverse morphologies and structures, including those at various stages and mass ratios, while distinguishing between projections and merger pairs. For the relation between galaxy mergers and environment, we find two distinct trends. Using stellar mass overdensity estimates for TNG simulations and observations using SDSS and GAMA, we find that galaxies with higher merger scores favor lower density environments on scales of 0.5 to 8h−1Mpc. However, below these scales in the simulations, we find that galaxies with higher merger scores favor higher density environments.

Conclusions.We fine-tuned a citizen-science trained deep representation learning model for purpose of merger galaxy classification in HSC-SSP, and make our merger probability catalog available to the public. Using our morphology-based catalog, we find that mergers are more prevalent in lower density environments on scales of 0.5–8h−1Mpc.
Finding the dispersing siblings of young open clusters
Authors: Vaher E. , Hobbs D. , McMillan P. , Prusti T.
Published: October 2023

Context. Stars tend to form in clusters, but many escape their birth clusters very early. Identifying the escaped members of clusters can inform us about the dissolution of star clusters, but also about the stellar dynamics in the galaxy. Methods capable of finding escaped stars from many clusters are required to fully exploit the large amounts of data in the Gaia era.

Aims. We present a new method of identifying escaped members of nearby clusters and apply it to ten young clusters.

Methods. We assumed the escaped stars were close to the cluster in the past and performed traceback computations based on the Gaia DR3 radial velocity subsample. For each individual star, our method produces a probability estimate that it is an escaped member of a cluster, and for each cluster it also estimates the field star contamination rate of the identified fugitives.

Results. Our method is capable of finding fugitives that have escaped from their cluster in the last few ten million years. In many cases the fugitives form an elongated structure that covers a large volume.

Conclusions. The results presented here show that traceback computations using Gaia DR3 data can identify stars that have recently escaped their cluster. Our method will be even more useful when applied to future Gaia data releases that contain more radial velocity measurements.
Stable approximation of Helmholtz solutions in the disk by evanescent plane waves
Authors: Parolin Emile , Huybrechs Daan , Moiola Andrea
Published: October 2023

Superpositions of plane waves are known to approximate well the solutions of the Helmholtz equation. Their use in discretizations is typical of Trefftz methods for Helmholtz problems, aiming to achieve high accuracy with a small number of degrees of freedom. However, Trefftz methods lead to ill-conditioned linear systems, and it is often impossible to obtain the desired accuracy in floating-point arithmetic. In this paper we show that a judicious choice of plane waves can ensure high-accuracy solutions in a numerically stable way, in spite of having to solve such ill-conditioned systems. Numerical accuracy of plane wave methods is linked not only to the approximation space, but also to the size of the coefficients in the plane wave expansion. We show that the use of plane waves can lead to exponentially large coefficients, regardless of the orientations and the number of plane waves, and this causes numerical instability. We prove that all Helmholtz fields are continuous superposition of evanescent plane waves, i.e., plane waves with complex propagation vectors associated with exponential decay, and show that this leads to bounded representations. We provide a constructive scheme to select a set of real and complex-valued propagation vectors numerically. This results in an explicit selection of plane waves and an associated Trefftz method that achieves accuracy and stability. The theoretical analysis is provided for a two-dimensional domain with circular shape. However, the principles are general and we conclude the paper with a numerical experiment demonstrating practical applicability also for polygonal domains.
Expanding the scope of quantum annealing applicability
Authors: Isshiki Hiroshi , Asari Koki
Published: October 2023

With the emergence of D-wave’s quantum annealing machine, the power of quantum computing has become tangible, and the development of quantum computers is accelerating rapidly. Unfortunately, at present, the minimum value search that D-wave’s quantum annealing machine can handle is limited to quadratic functions of binary integer variables. This constraint is due to both hardware and software limitations. If this constraint was to be lifted, it would undoubtedly bring about a revolution in the world. Therefore, in this study, we obtained the basic mathematics of using quantum annealing, which enables hyper-parallel computing using qubits, to find the global minimum of any minimum value problem. Furthermore, we conducted simple simulations using classical computers to demonstrate the effectiveness of the ideas and algorithms. Furthermore, we conducted simple simulations using classical computers to demonstrate the effectiveness of the ideas and algorithms. We obtained also the mathematical method of using quantum annealing in learning neural networks and solving linear equations.
Design and mathematical modeling of scintillator-based electron–ion Thomson parabola spectrometer
Authors: Li Kun , Zong Shunhui
Published: October 2023

A compact scintillator-based electron–ion Thomson Parabola Spectrometer (ei-TPS) is designed and built up, which is able to measure the spectrum of electron and ion beams simultaneously in the same angular axis and real-time mode. The energy range of electrons is around 0.27–3.8 MeV with a relative energy resolution better than 2.5%, and the energy range of proton is around 0.16–21 MeV with a relative energy resolution better than 4% at the kinetic energy of 1 MeV, which makes it suitable for laser-driven ion acceleration experiments with 100-TW level laser. Detailed mathematical modeling is performed to reveal the dependence of properties, such as energy range and resolution, response, and detection threshold, on various parameters of ei-TPS, which is useful to modify the parameters according to specific requirements of electrons and ions.
Texture recognition based on magnetostrictive tactile sensor array and convolutional neural network
Authors: Li Zhuolin , Weng Ling , Zhang Yuanye , Liu Kaile , Liu Yang
Published: October 2023

Tactile sensors are key devices in surface information perception for robots that can recognize the surface texture of fabrics with different materials and winding patterns in unstructured environments, thus helping the robot process fabrics more effectively. In this study, a magnetostrictive tactile sensor array was designed and loaded onto the robotic fingertips, and the output voltage waveform was obtained by manipulating the sensor array to slide in contact with fabrics. The output voltage waveform diagram was normalized to build the FTS-15 tactile texture dataset. The convolutional neural network ResNet-18 model was built to pre-process the dataset, and the accuracy of recognizing 15 fabrics reached 97.95%. The results show that this texture recognition method can be effectively applied to the field of fabric texture recognition.
Numerical modeling and simulation of underwater explosions interacting with discrete rigid bodies
Authors: Zhang Tao , Zhuang Tieshuan , Gao Chao , Dong Xiangwei
Published: October 2023

The smoothed particle hydrodynamics (SPH) method is widely used to simulate underwater explosion phenomena. However, previous studies have focused on the interaction between the underwater explosion and continuous structures (e.g., steel plates and dams), while studies on the interaction between the explosion and discrete objects (e.g., debris) have not been reported. In this study, a multi-media coupled model containing water, explosion gas, discrete objects, and steel plates is developed based on the SPH method. The discrete object is modeled as a rigid body with a certain shape, which is discretized by SPH particles. The interaction between the discrete object and the adjacent fluid particles is realized by the kernel approximation, while the collision between different objects is realized by the contact algorithm. To improve the numerical stability, an artificial viscous term containing a threshold switch is added to the SPH momentum equation, while a density dissipation term is introduced into the continuity equation to reduce the noise of the pressure field. Subsequently, the established SPH model is used to simulate the underwater explosion process containing discrete rigid bodies, and the effects of the distribution, stacking form, and number of rigid bodies on the propagation of shock waves, bubble expansion, and deformation of steel plates and the effect of damage are analyzed. The results show that the rigid body will hinder the propagation of shock waves, help reduce the peak pressure of the shock wave behind, and then affect the direction of the diffusion of the explosion energy. Shock waves would produce diffraction, reflection, and transmission when passing through the rigid bodies, and the superposition of various waves would make the pressure distribution near the liquid–gas interface irregular. The rigid bodies stacked above the explosives would enhance the damage effect of the explosion on the steel plates below, and the damage effect is affected by the stacking form. The established model can simulate the multi-medium coupling process in a unified framework without coupling other methods and can effectively restore the complex interaction process between underwater explosion, discrete object, and structure.
Enhancing single-cell biology through advanced AI-powered microfluidics
Authors: Gao Zhaolong , Li Yiwei
Published: October 2023

Microfluidic technology has largely benefited both fundamental biological research and translational clinical diagnosis with its advantages in high-throughput, single-cell resolution, high integrity, and wide-accessibility. Despite the merits we obtained from microfluidics in the last two decades, the current requirement of intelligence in biomedicine urges the microfluidic technology to process biological big data more efficiently and intelligently. Thus, the current readout technology based on the direct detection of the signals in either optics or electrics was not able to meet the requirement. The implementation of artificial intelligence (AI) in microfluidic technology matches up with the large-scale data usually obtained in the high-throughput assays of microfluidics. At the same time, AI is able to process the multimodal datasets obtained from versatile microfluidic devices, including images, videos, electric signals, and sequences. Moreover, AI provides the microfluidic technology with the capability to understand and decipher the obtained datasets rather than simply obtaining, which eventually facilitates fundamental and translational research in many areas, including cell type discovery, cell signaling, single-cell genetics, and diagnosis. In this Perspective, we will highlight the recent advances in employing AI for single-cell biology and present an outlook on the future direction with more advanced AI algorithms.
Large amplitude dust-acoustic solitary waves and double layers in nonthermal warm complex plasmas
Authors: Alam N. , Mannan A. , Mamun A. A.
Published: October 2023

Using a Sagdeev pseudo-potential approach, where the nonlinear structures are stationary in a comoving frame, the arbitrary or large amplitude dust-acoustic solitary waves and double layers have been studied in dusty plasmas containing warm positively charged dust and nonthermal distributed electrons and ions. Depending on the values of the critical Mach number, which varies with the plasma parameter, both supersonic and subsonic dust-acoustic solitary waves are found. It is found that our plasma system under consideration supports both positive and negative supersonic solitary waves and only positive subsonic solitary waves and negative double layers. The parametric regimes for the existence of subsonic and supersonic dust-acoustic waves and how the polarity of solitary waves changes with plasma parameters are shown. It is observed that the solitary wave and double layer solutions exist at the values of Mach number around its critical Mach number. The basic properties (amplitude, width, speed, etc.) of the solitary pulses and double layers are significantly modified by the plasma parameters (viz., ion to positive dust number density ratio, ion to electron temperature ratio, nonthermal parameter, and positive dust temperature to ion temperature ratio). The applications of our present work in space environments (viz., cometary tails, Earth’s mesosphere, and Jupiter’s magnetosphere) and laboratory devices, where nonthermal ion and electron species along with positively charged dust species have been observed, are briefly discussed.
When learning physics mirrors doing physics
Authors: Etkina Eugenia
Published: October 2023

The Investigative Science Learning Environment approach replaces traditional teaching with active-learning methods that emulate scientific processes.
Ca2+-induced release of IQSEC2/BRAG1 autoinhibition under physiological and pathological conditions
Authors: Bai Guanhua , Li Hao , Qin Pengwei , Guo Yiqing , Yang Wanfa , Lian Yinmiao , Ye Fei , Chen Jianxin , Wu Meiling , Huang Ruifeng , Li Jinsong , Lu Youming , Zhang Mingjie
Published: October 2023

IQSEC2 (aka BRAG1) is a guanine nucleotide exchange factor (GEF) highly enriched in synapses. As a top neurodevelopmental disorder risk gene, numerous mutations are identified in Iqsec2 in patients with intellectual disabilities accompanied by other developmental, neurological, and psychiatric symptoms, though with poorly understood underlying molecular mechanisms. The atomic structures of IQSECs, together with biochemical analysis, presented in this study reveal an autoinhibition and Ca2+-dependent allosteric activation mechanism for all IQSECs and rationalize how each identified Iqsec2 mutation can alter the structure and function of the enzyme. Transgenic mice modeling two pathogenic variants of Iqsec2 (R359C and Q801P), with one activating and the other inhibiting the GEF activity of the enzyme, recapitulate distinct clinical phenotypes in patients. Our study demonstrates that different mutations on one gene such as Iqsec2 can have distinct neurological phenotypes and accordingly will require different therapeutic strategies.
Estimation of 2D profile dynamics of electrostatic potential fluctuations using multi-scale deep learning
Authors: Jajima Yuki , Sasaki Makoto , Ishikawa Ryohtaroh T , Nakata Motoki , Kobayashi Tatsuya , Kawachi Yuichi , Arakawa Hiroyuki
Published: October 2023

Dynamics in magnetically confined plasmas are dominated by turbulence driven by spatial inhomogeneities in density and temperature. Simultaneous measurement of velocity field and density fluctuations is necessary to observe the particle transport, but the measurement of the velocity field fluctuations is often challenging. Here, we propose a method to estimation velocity field fluctuations from density fluctuations by using plasma turbulence simulations and a deep technique learning. In order to take multi-scale characteristics into account, the several number of spatial filters are used in the convolutional neural network. The velocity field fluctuations are successfully predicted, and the particle transport estimated from the predicted velocity field fluctuations is within 93.1% accuracy. The deep learning could be used for the prediction of physical variables which are difficult to be measured.
A fractional-order quantum neural network: dynamics, finite-time synchronization
Authors: Wang S-F , Xu X-J
Published: October 2023

A model of fractional-order quantum cellular neural network (FoQCNN) by using fractional-order quantum-dot cellular automata (QCA) is constructed and its dynamics are analyzed. Then, a robust finite-time synchronization scheme using terminal sliding mode control (SMC) technique is proposed. And then, taking the perturbed FoQCNN model with uncertainties and external disturbances as an example, the results are simulated which present the proposed scheme is effective. It has robust synchronization performance and good anti-interference ability, which provides a theoretical basis for the application of neural network in security.
Highly uniform nanocomposite through the decoration of MnS on graphitic carbon nitride as electrodes for symmetric supercapacitor
Authors: Ben Gouider Trabelsi Amira , Elsayed Asmaa M , Alkallas Fatemah H , Rabia Mohamed
Published: October 2023

The decoration of MnS on the graphitic carbon nitride (G-C3N4) is demonstrated through solvothermal synthesis, in which the MnS/G-C3N4 nanocomposite is formed. Under combustion at 300 oC for 5 min, the incorporation of MnO2 materials is obtained as a dopant material. The morphological properties are performed through the TEM and SEM analyses, in which a spherical-like nanocomposite is formed. The elemental and crystalline structures are confirmed using the XPS and XRD analyses. Testing this composite as a supercapacitor is performed through a (1.0 M) Na2SO4 electrolyte. This capacitor illustrates a specific capacitance (CS) of 43.5 F g−1 at 0.2 A g−1, while the energy value (E) is 8.6 W.h.kg−1. This capacitor has an excellent stability of 98.2% till 1000 cycles. The great stability of the supercapacitor till 1000 cycles confirms the ability of this supercapacitor to work well under the charge and discharge process for a long time.
Numerical analysis of electro-thermo-convection in a differentially heated square cavity with electric conduction
Authors: Peng Yuxing , Wang Junxiu , Du Zhonglin , Vázquez Pedro A , Wu Jian
Published: October 2023

Natural convection with an electric field in the classic differentially heated square cavity is numerically studied. The electric conduction model for the generation of free space charges, which applies to weak and moderate electric field with weakly conducting liquids, is specially considered. The whole set of governing equations is implemented in the open-source finite-volume framework of OpenFOAM. Thorough investigation has been undertaken to analyze the thermal and flow characteristics of electro-thermo convection. The results reveal that the introduction of an electric field leads to a suppressive influence on flow motion across all considered Rayleigh numbers (Ra), aligning with recent experimental findings. This effect becomes more pronounced with increasing conduction number (C
0), resulting in the reduction of flow intensity and a thicker thermal boundary layer. Consequently, heat transfer is subdued due to the electric field, causing a decrease in the Nusselt number (Nu) as C
0 increases. To elucidate the mechanism how the electric field impacts natural convection, the torques induced by the electric and buoyancy forces are computed. Higher C
0 will lead to a lower buoyancy torque and stronger electric torque, where the electric torque is opposite to the buoyancy torque, thus the weaker flow strength is shown at higher C
0. Finally, to quantify the reduction in heat loss, the relative Nusselt number (Rnu) is introduced. It is found that there is a critical Ra corresponding to minimal Rnu, and for the parameters considered in this study, the minimum Rnu of 0.563 is observed at C
0 = 0.2 and Ra = 1.2 × 104. For large Ra, the Rnu almost keeps constant with increasing Ra.
Development of a coulometry system at the Korea Research Institute of Standards and Science and evaluation of the measurement uncertainty originating from the system
Authors: Jo Kyungmin , Lim Youngran , Lee Kyoung-Seok , Hwang Euijin
Published: October 2023

Coulometry is used to realize the definition of the mole and enables the direct determination of the purity of high-purity substances that are used as standards for other relative measurements with very small measurement uncertainty. However, despite several studies reporting the development of accurate and precise coulometry systems, there is a lack of detailed description of the system and systematic evaluation of the measurement uncertainty arising from the system. In this study, coulometry systems constructed at the Korea Research Institute of Standards and Science (KRISS) are described in detail and the uncertainties associated with these systems are systematically evaluated using a bottom-up approach. The relative expanded uncertainty resulting from the measurement system for the amount-of-substance content of acid in high-purity potassium hydrogen phthalate is approximately 0.0005%. The performance of the KRISS coulometry systems has been verified through several international comparisons and comparative measurements using certified reference materials.