bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance and robustness analysis of V-Tiger PID controller for automatic voltage regulator
Authors: Gopi Pasala , Reddy S. Venkateswarlu , Bajaj Mohit , Zaitsev Ievgen , Prokop Lukas
Published: April 2024

This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications.
Population-wide modelling reveals prospects of marker-assisted selection for parasitic mite resistance in honey bees
Authors: Lefebre Regis , Broeckx Bart J. G. , De Smet Lina , Peelman Luc , de Graaf Dirk C.
Published: April 2024

In 2019, a joint eight-variant model was published in which eight single nucleotide polymorphisms (SNPs) in seven Apis mellifera genes were associated with Varroa destructor drone brood resistance (DBR, i.e. mite non-reproduction in drone brood). As this model was derived from only one Darwinian Black Bee Box colony, it could not directly be applied on a population-overarching scale in the northern part of Belgium (Flanders), where beekeepers prefer the carnica subspecies. To determine whether these eight SNPs remained associated with the DBR trait on a Flemish colony-broad scope, we performed population-wide modelling through sampling of various A. mellifera carnica colonies, DBR scoring of Varroa-infested drone brood and variant genotyping. Novel eight-variant modelling was performed and the classification performance of the eight SNPs was evaluated. Besides, we built a reduced three-variant model retaining only three genetic variants and found that this model classified 76% of the phenotyped drones correctly. To examine the spread of beneficial alleles and predict the DBR probability distribution in Flanders, we determined the allelic frequencies of the three variants in 292 A. mellifera carnica queens. As such, this research reveals prospects of marker-assisted selection for Varroa drone brood resistance in honeybees.
Experimental and data-driven analysis for predicting nanofluid performance in improving foam stability and reducing mobility at critical micelle concentration
Authors: Issakhov Miras , Khanjani Maral , Muratkhozhina Adiya , Pourafshary Peyman , Aidarova Saule , Sharipova Altynay
Published: April 2024

Application of surfactant-based foam flooding is an effective approach to reduce mobility and control early breakthrough. Despite the proper performance of surfactant-based foams in decreasing the channeling of the flooded gas and water, high pressure, high temperature, and high salinity of the reservoirs put some limitations on the foam flooding efficiency. Nanoparticles are used to improve the quality of the foams, enhance stability, and transcend the limitations. Although there are many benefits of using nanoparticles in foam flooding, their performance at surfactant critical micelle concentration (CMC) is not fully investigated and the optimum nanoparticle concentration is not specified. In this study, an experimental investigation using nanosilica with surfactants at CMC to improve the stability (half-life) and mobility reduction factor (MRF) has been conducted. Furthermore, data from the literature were collected and analyzed to evaluate the change in MRF and stability for a nanofluid-based foam at CMC. Both experimental results and literature data showed that application of nanofluid-based foam is a successful approach to develop a more stable foam with lower mobility. Nanoparticle (NP) concentration is the dominant parameter at different salinities and temperatures that affects foam flow through porous media. The range of 0.2–0.4 wt% is the optimum nanoparticle concentration to develop a strong foam with acceptable performance in controlling mobility.
Positive association between sodium-to-chloride ratio and in-hospital mortality of acute heart failure
Authors: Wei Dongmei , Chen Shaojun , Xiao Di , Chen Rongtao , Meng Yuanting
Published: April 2024

Previous studies have suggested that levels of sodium and chloride in the blood may be indicative of the prognosis of different medical conditions. Nevertheless, the assessment of the prognostic significance of the sodium-to-chloride (Na/Cl) ratio in relation to in-hospital mortality among individuals suffering from acute heart failure (AHF) remains unexplored. In this study, the participants were selected from the Medical Information Mart for Intensive Care IV database and divided into three groups based on the Na/Cl ratio level upon admission. The primary results were the mortality rate within the hospital. Cox regression, Kaplan–Meier curves, receiver operator characteristic (ROC) curve analysis and subgroup analyses were utilized to investigate the correlation between the admission Na/Cl ratio and outcomes in critically ill patients with AHF. A total of 7844 patients who met the selection criteria were included in this study. After adjusting for confounders, the multivariable Cox regression analysis revealed that the baseline Na/Cl ratio significantly elevated the risk of in-hospital mortality among critically ill patients with AHF (HR = 1.34, 95% CI 1.21–1.49). Furthermore, when the Na/Cl ratio was converted into a categorical factor and the initial tertile was taken as a point of comparison, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the second and third tertiles were 1.27 (1.05–1.54) and 1.53 (1.27–1.84), respectively. Additionally, a P value indicating a significant trend of < 0.001 was observed. ROC curve analysis showed that Na/Cl ratio had a more sensitive prognostic value in predicting in-hospital mortality of AHF than the sodium or chloride level alone (0.564 vs. 0.505, 0.544). Subgroup examinations indicated that the association between the Na/Cl ratio upon admission and the mortality rate of critically ill patients with AHF remained consistent in the subgroups of hyponatremia and hypochlorhydria (P for interaction > 0.05). The linear relationship between the Na/Cl ratio and in-hospital mortality in AHF patients indicates a positive association.
Genome-wide CRISPR screens identify PKMYT1 as a therapeutic target in pancreatic ductal adenocarcinoma
Authors: Wang Simin , Xiong Yangjie , Luo Yuxiang , Shen Yanying , Zhang Fengrui , Lan Haoqi , Pang Yuzhi , Wang Xiaofang , Li Xiaoqi , Zheng Xufen , Lu Xiaojing , Liu Xiaoxiao , Cheng Yumei , Wu Tanwen , Dong Yue , Lu Yuan , Cui Jiujie , Jia Xiaona , Yang Sheng , Wang Liwei , Wang Yuexiang
Published: April 2024

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with an overall 5-year survival rate of <12% due to the lack of effective treatments. Novel treatment strategies are urgently needed. Here, PKMYT1 is identified through genome-wide CRISPR screens as a non-mutant, genetic vulnerability of PDAC. Higher PKMYT1 expression levels indicate poor prognosis in PDAC patients. PKMYT1 ablation inhibits tumor growth and proliferation in vitro and in vivo by regulating cell cycle progression and inducing apoptosis. Moreover, pharmacological inhibition of PKMYT1 shows efficacy in multiple PDAC cell models and effectively induces tumor regression without overt toxicity in PDAC cell line-derived xenograft and in more clinically relevant patient-derived xenograft models. Mechanistically, in addition to its canonical function of phosphorylating CDK1, PKMYT1 functions as an oncogene to promote PDAC tumorigenesis by regulating PLK1 expression and phosphorylation. Finally, TP53 function and PRKDC activation are shown to modulate the sensitivity to PKMYT1 inhibition. These results define PKMYT1 dependency in PDAC and identify potential therapeutic strategies for clinical translation.
Shear-flow induced alignment of graphene enables the closest packing crystallography of the (002) textured zinc metal anode with high reversibility
Authors: Xi Murong , Liu Zhenjie , Wang Wei , Qi Zihan , Sheng Rui , Ding Juan , Huang Yudai , Guo Zaiping
Published: April 2024

A meter-grade graphene-modified copper collector (Cu@G) was prepared using a shear-flow induced method. Cu@G enables the closest packing crystallography of the (002) textured Zn metal anode with excellent plating/stripping reversibility.
A ROS storm generating nanocomposite for enhanced chemodynamic therapy through H2O2 self-supply, GSH depletion and calcium overload
Authors: Li Yong , Wang Jing , Zhu Tao , Zhan Ying , Tang Xiaoli , Xi Jianying , Zhu Xiaohui , Zhang Yong , Liu Jinliang
Published: April 2024

A CaO2-based multifunctional nanocomposite which possesses H2O2 self-supplying, GSH depletion and calcium overload properties was prepared, the nanocomposite can enhance the efficacy of CDT and accelerate tumor apoptosis.
Opportunities and challenges in perovskite–organic thin-film tandem solar cells
Authors: Meng Xin , Jia Zhengrong , Niu Xiuxiu , He Chunnian , Hou Yi
Published: April 2024

In this work, we focus on perovskite–organic tandem solar cells (PO TSCs) with advantages in device performance, manufacturing cost, and diverse applications and conclude the critical factors influencing the future development of PO TSCs.
Self-assembled monolayers for electrostatic electrocatalysis and enhanced electrode stability in thermogalvanic cells
Authors: Laws Kristine , Buckingham Mark A. , Aldous Leigh
Published: April 2024

Thermogalvanic cells can convert temperature gradients (e.g. waste heat) into electricity; here we demonstrate how electrostatically charged self-assembled monolayers can act as molecular electrocatalysts, plus reduce electrode passivation.
Ag-coated tetrapod gold nanostars (Au@AgNSs) for acetamiprid determination in tea using SERS combined with microfluidics
Authors: Ke Qian , Yin Limei , Jayan Heera , El-Seedi Hesham R. , Zou Xiaobo , Guo Zhiming
Published: April 2024

The combination of highly sensitive SERS substrate core–shell Au@AgNSs and microfluidic chip featuring four circular split hybrid structures were used for quantitative detection of acetamiprid in tea. The LOD of acetamiprid was 0.048 ng mL−1.
Nanoscale assembly of enantiomeric supramolecular gels driven by the nature of solvents
Authors: Gudmundsson Tómas A. , Kuppadakkath Geethanjali , Ghosh Dipankar , Ruether Manuel , Seddon Annela , Ginesi Rebecca E. , Doutch James , Adams Dave J. , Gunnlaugsson Thorfinnur , Damodaran Krishna K.
Published: April 2024

Different co-assembly modes depending on the nature of the solvents observed in multi-component systems with structurally similar components.
Exploiting controlled transesterification as a “top down” approach to tailor poly(ε-caprolactone)-poly(lactic acid) copolymer structures with bis-Zn catalysts
Authors: Neal Thomas J. , Neal Edward D. , Cumby James , Garden Jennifer A.
Published: April 2024

Mediated by a bis-Zn catalyst, poly(lactic acid)-block-poly(ε-caprolactone) diblock copolymers can be modified via controlled transesterification, leading to diverse copolymer structures.
Assessment of metabolome diversity in black and white pepper in response to autoclaving using MS- and NMR-based metabolomics and in relation to its remote and direct antimicrobial effects against food-borne pathogens
Authors: Baky Mostafa H. , Kamal Islam M. , Wessjohann Ludger A. , Farag Mohamed A.
Published: April 2024

Piper nigrum L. (black and white peppercorn) is one of the most common culinary spices used worldwide.
Nanopore-based glycan sequencing: state of the art and future prospects
Authors: Yao Guangda , Ke Wenjun , Xia Bingqing , Gao Zhaobing
Published: April 2024

This perspective outlines three potential routes for nanopore-based glycan sequencing, highlighting their potential applications and offering insights to meet associated challenges. It also introduces the concept of nanopore-based glycan sequencer.
A two‐stage substation equipment classification method based on dual‐scale attention
Authors: Yao Yiyang , Wang Xue , Zhou Guoqing , Wang Qing
Published: April 2024

Accurate classification of substation equipment images remains challenging due to various factors such as unexpected illumination, viewing angles, scale variations, shadows, surface contaminants, and different elements sharing similar appearances. This paper presents a novel two‐stage substation equipment classification method based on dual‐scale attention. Leveraging the region proposal technique from Faster‐regions with CNN features (RCNN), the input images are initially decomposed into multiple scales to capture latent features. A dual‐scale attention module is introduced to enhance the precision of feature extraction. Furthermore, a two‐stage network is proposed to address the challenge of classifying closely similar substation equipment. A multi‐layer perceptron performs a coarse classification to categorize the equipment into broad categories. Then, a lightweight classifier is employed for fine‐grained subclassification, further distinguishing equipment within the same broad category. To mitigate the issue of limited training data, a specialized dataset is collected and annotated for the substation equipment classification. Experimental results demonstrate that the proposed method achieves remarkable accuracy, recall, and F1‐score surpassing 0.91, outperforming mainstream approaches in terms of recall and F1 scores. Ablation experiments further validate the significant contributions of both the dual‐scale attention and the two‐stage classification module in improving the overall performance of the classification network.
Integrated bioinformatics analysis identified leucine rich repeat containing 15 and secreted phosphoprotein 1 as hub genes for calcific aortic valve disease and osteoarthritis
Authors: Gong Shuji , Xiang Kun , Chen Le , Zhuang Huanwei , Song Yaning , Chen Jinlan
Published: April 2024

Calcific aortic valve disease (CAVD) and osteoarthritis (OA) are common diseases in the ageing population and share similar pathogenesis, especially in inflammation. This study aims to discover potential diagnostic and therapeutic targets in patients with CAVD and OA. Three CAVD datasets and one OA dataset were obtained from the Gene Expression Omnibus database. We used bioinformatics methods to search for key genes and immune infiltration, and established a ceRNA network. Immunohistochemical staining was performed to verify the expression of candidate genes in human and mice aortic valve tissues. Two key genes obtained, leucine rich repeat containing 15 (LRRC15) and secreted phosphoprotein 1 (SPP1), were further screened using machine learning and verified in human and mice aortic valve tissues. Compared to normal tissues, the infiltration of immune cells in CAVD tissues was significantly higher, and the expressions of LRRC15 and SPP1 were positively correlated with immune cells infiltration. Moreover, the ceRNA network showed extensive regulatory interactions based on LRRC15 and SPP1. The authors’ findings identified LRRC15 and SPP1 as hub genes in immunological mechanisms during CAVD and OA initiation and progression, as well as potential targets for drug development.
Zooming in on the circumgalactic medium with GIBLE
Authors: Ramesh Rahul , Nelson Dylan , Fielding Drummond , Brüggen Marcus
Published: April 2024

We used a cosmological zoom-in simulation of a Milky Way-like galaxy to study and quantify the topology of magnetic field lines around cold gas clouds in the circumgalactic medium (CGM). This simulation is a new addition to Project GIBLE, a suite of cosmological magnetohydrodynamic simulations of galaxy formation with preferential super-Lagrangian refinement in the CGM, reaching an unprecedented CGM gas mass resolution of ∼225 M⊙. To maximize statistics and resolution, we focused on a sample of ∼200 clouds with masses of ∼106 M⊙. The topology of magnetic field lines around clouds is diverse, from threading to draping, and there is large variation in the magnetic curvature (κ) within cloud-background interfaces. We typically find little variation of κ between upstream and downstream cloud faces, implying that strongly draped configurations are rare. In addition, κ correlates strongly with multiple properties of the interface and the ambient background, including cloud overdensity and relative velocity, suggesting that cloud properties impact the topology of interface magnetic fields.
An optimization-based method for sign-changing elliptic PDEs
Authors: Abdulle Assyr , Lemaire Simon
Published: April 2024

We study the numerical approximation of sign-shifting problems of elliptic type. We fully analyze and assess the method briefly introduced in [A. Abdulle, M.E. Huber and S. Lemaire, C. R. Math. 355 (2017) 472–478]. Our method is based on domain decomposition and optimization. Upon assuming extra integrability on the exact normal flux trace along the sign-changing interface, our method is proved to be convergent as soon as, for a given loading, the PDE admits a unique solution of finite energy. Departing from the T-coercivity approach, which relies on the use of geometrically fitted mesh families, our method works for arbitrary (interface-compliant) mesh sequences. Moreover, it is shown convergent for a class of problems for which T-coercivity is not applicable. A comprehensive set of test-cases complements our analysis.
On approximating the symplectic spectrum of infinite-dimensional operators
Authors: Kumar V. B. Kiran , Tonny Anmary
Published: April 2024

The symplectic eigenvalues play a significant role in the finite-mode quantum information theory, and Williamson’s normal form proves to be a valuable tool in this area. Understanding the symplectic spectrum of a Gaussian Covariance Operator is a crucial task. Recently, in 2018, an infinite-dimensional analogue of Williamson’s Normal form was discovered, which has been instrumental in studying the infinite-mode Gaussian quantum states. However, most existing results pertain to finite-dimensional operators, leaving a dearth of literature in the infinite-dimensional context. The focus of this article is on employing approximation techniques to estimate the symplectic spectrum of certain infinite-dimensional operators. These techniques are well-suited for a particular class of operators, including specific types of infinite-mode Gaussian Covariance Operators. Our approach involves computing the Williamson’s Normal form and deriving bounds for the symplectic spectrum of these operators. As a practical application, we explicitly compute the symplectic spectrum of Gaussian Covariance Operators. Through this research, we aim to contribute to the understanding of symplectic eigenvalues in the context of infinite-dimensional operators, opening new avenues for exploration in quantum information theory and related fields.
Integration of vorticity–velocity formulation in a lattice Boltzmann method for porous media
Authors: Kefayati Gholamreza
Published: April 2024

A lattice Boltzmann method (LBM) is proposed to address the two-dimensional macroscopic equations of velocity–vorticity for porous media in incompressible flows. The macroscopic equations of two-dimensional porous media using the representative element volume scale approach, employing various models, are shown. The momentum equations are transformed and presented in the velocity and vorticity format. Additionally, the energy and concentration equations are thoroughly examined. Subsequently, the LBM is presented to restore the dimensional macroscopic equations of the velocity–vorticity format for various porous models, accounting for external forces. The paper provides proof and derivations of the equations for the LBM, which are then demonstrated and discussed. The suggested approach is evaluated across a variety of well-established benchmark examples within the realm of fluid flow, heat, and mass transfer in porous media. Importantly, the LBM approach significantly reduces computational time compared to previous methods in the field by eliminating pressure in the momentum equation, thereby reducing the number of unknown variables and transforming the equation into a convection–diffusion form. This modification leads to a linear equilibrium distribution function and a noteworthy decrease in computational costs.
Subgenome-aware analyses reveal the genomic consequences of ancient allopolyploid hybridizations throughout the cotton family
Authors: Sun Pengchuan , Lu Zhiqiang , Wang Zhenyue , Wang Shang , Zhao Kexin , Mei Dong , Yang Jiao , Yang Yongzhi , Renner Susanne S. , Liu Jianquan
Published: April 2024

Malvaceae comprise some 4,225 species in 243 genera and nine subfamilies and include economically important species, such as cacao, cotton, durian, and jute, with cotton an important model system for studying the domestication of polyploids. Here, we use chromosome-level genome assemblies from representatives of five or six subfamilies (depending on the placement ofOchroma) to differentiate coexisting subgenomes and their evolution during the family’s deep history. The results reveal that the allohexaploid Helicteroideae partially derive from an allotetraploid Sterculioideae and also form a component of the allodecaploid Bombacoideae and Malvoideae. The ancestral Malvaceae karyotype consists of 11 protochromosomes. Four subfamilies share a unique reciprocal chromosome translocation, and two other subfamilies share a chromosome fusion. DNA alignments of single-copy nuclear genes do not yield the same relationships as inferred from chromosome structural traits, probably because of genes originating from different ancestral subgenomes. These results illustrate how chromosome-structural data can unravel the evolutionary history of groups with ancient hybrid genomes.
Conformational changes in the Niemann–Pick type C1 protein NCR1 drive sterol translocation
Authors: Frain Kelly M. , Dedic Emil , Nel Lynette , Bohush Anastasiia , Olesen Esben , Thaysen Katja , Wüstner Daniel , Stokes David L. , Pedersen Bjørn Panyella
Published: April 2024

The membrane protein Niemann–Pick type C1 (NPC1, named NCR1 in yeast) is central to sterol homeostasis in eukaryotes.
Saccharomyces cerevisiae
NCR1 is localized to the vacuolar membrane, where it is suggested to carry sterols across the protective glycocalyx and deposit them into the vacuolar membrane. However, documentation of a vacuolar glycocalyx in fungi is lacking, and the mechanism for sterol translocation has remained unclear. Here, we provide evidence supporting the presence of a glycocalyx in isolated
S. cerevisiae
vacuoles and report four cryo-EM structures of NCR1 in two distinct conformations, named tense and relaxed. These two conformations illustrate the movement of sterols through a tunnel formed by the luminal domains, thus bypassing the barrier presented by the glycocalyx. Based on these structures and on comparison with other members of the Resistance–Nodulation–Division (RND) superfamily, we propose a transport model that links changes in the luminal domains with a cycle of protonation and deprotonation within the transmembrane region of the protein. Our model suggests that NPC proteins work by a generalized RND mechanism where the proton motive force drives conformational changes in the transmembrane domains that are allosterically coupled to luminal/extracellular domains to promote sterol transport.
Precision proteoform design for 4R tau isoform selective templated aggregation
Authors: Longhini Andrew P. , DuBose Austin , Lobo Samuel , Vijayan Vishnu , Bai Yeran , Rivera Erica Keane , Sala-Jarque Julia , Nikitina Arina , Carrettiero Daniel C. , Unger Matthew T. , Sclafani Olivia R. , Fu Valerie , Beckett Emily R. , Vigers Michael , Buée Luc , Landrieu Isabelle , Shell Scott , Shea Joan E. , Han Songi , Kosik Kenneth S.
Published: April 2024

Prion-like spread of disease-specific tau conformers is a hallmark of all tauopathies. A 19-residue probe peptide containing a P301L mutation and spanning the R2/R3 splice junction of tau folds and stacks into seeding-competent fibrils and induces aggregation of 4R, but not 3R tau. These tau peptide fibrils propagate aggregated intracellular tau over multiple generations, have a high β-sheet content, a colocalized lipid signal, and adopt a well-defined U-shaped fold found in 4R tauopathy brain-derived fibrils. Fully atomistic replica exchange molecular dynamics (MD) simulations were used to compute the free energy landscapes of the conformational ensemble of the peptide monomers. These identified an aggregation-prohibiting β-hairpin structure and an aggregation-competent U-fold unique to 4R tauopathy fibrils. Guided by MD simulations, we identified that the N-terminal-flanking residues to PHF6, which slightly vary between 4R and 3R isoforms, modulate seeding. Strikingly, when a single amino acid switch at position 305 replaced the serine of 4R tau with a lysine from the corresponding position in the first repeat of 3R tau, the seeding induced by the 19-residue peptide was markedly reduced. Conversely, a 4R tau mimic with three repeats, prepared by replacing those amino acids in the first repeat with those amino acids uniquely present in the second repeat, recovered aggregation when exposed to the 19-residue peptide. These peptide fibrils function as partial prions to recruit naive 4R tau—ten times the length of the peptide—and serve as a critical template for 4R tauopathy propagation. These results hint at opportunities for tau isoform–specific therapeutic interventions.
Cross-prediction-powered inference
Authors: Zrnic Tijana , Candès Emmanuel J.
Published: April 2024

While reliable data-driven decision-making hinges on high-quality labeled data, the acquisition of quality labels often involves laborious human annotations or slow and expensive scientific measurements. Machine learning is becoming an appealing alternative as sophisticated predictive techniques are being used to quickly and cheaply produce large amounts of predicted labels; e.g., predicted protein structures are used to supplement experimentally derived structures, predictions of socioeconomic indicators from satellite imagery are used to supplement accurate survey data, and so on. Since predictions are imperfect and potentially biased, this practice brings into question the validity of downstream inferences. We introduce cross-prediction: a method for valid inference powered by machine learning. With a small labeled dataset and a large unlabeled dataset, cross-prediction imputes the missing labels via machine learning and applies a form of debiasing to remedy the prediction inaccuracies. The resulting inferences achieve the desired error probability and are more powerful than those that only leverage the labeled data. Closely related is the recent proposal of prediction-powered inference [A. N. Angelopoulos, S. Bates, C. Fannjiang, M. I. Jordan, T. Zrnic,
Science
382
, 669–674 (2023)], which assumes that a good pretrained model is already available. We show that cross-prediction is consistently more powerful than an adaptation of prediction-powered inference in which a fraction of the labeled data is split off and used to train the model. Finally, we observe that cross-prediction gives more stable conclusions than its competitors; its CIs typically have significantly lower variability.
Reversible Optical Isolators and Quasi-Circulators Using a Magneto-Optical Fabry–Pérot Cavity
Authors: Zhang 张 Tiantian 天天 , Zhou 周 Wenpeng 文鹏 , Li 李 Zhixiang 志向 , Tang 唐 Yutao 宇涛 , Xu 许 Fan 帆 , Wu 吴 Haodong 浩东 , Zhang 张 Han 涵 , Tang 唐 Jiang-Shan 江山 , Ruan 阮 Ya-Ping 亚平 , Xia 夏 Keyu 可宇
Published: April 2024

Nonreciprocal optical devices are essential for laser protection, modern optical communication and quantum information processing by enforcing one-way light propagation. The conventional Faraday magneto-optical nonreciprocal devices rely on a strong magnetic field, which is provided by a permanent magnet. As a result, the isolation direction of such devices is fixed and severely restricts their applications in quantum networks. In this work, we experimentally demonstrate the simultaneous one-way transmission and unidirectional reflection by using a magneto-optical Fabry–Pérot cavity and a magnetic field strength of 50 mT. An optical isolator and a three-port quasi-circulator are realized based on this nonreciprocal cavity system. The isolator achieves an isolation ratio of up to 22 dB and an averaged insertion loss down to 0.97 dB. The quasi-circulator is realized with a fidelity exceeding 99% and an overall survival probability of 89.9%, corresponding to an insertion loss of ∼0.46 dB. The magnetic field is provided by an electromagnetic coil, thereby allowing for reversing the light circulating path. The reversible quasi-circulator paves the way for building reconfigurable quantum networks.
Theoretical characterization of the temperature-dependent saturation magnetization of magnetic metallic materials
Authors: Wu 吴 Jin-Long 金龙 , Dong 董 Pan 攀 , He 贺 Yi 屹 , Ma 马 Yan-Li 艳丽 , Li 李 Zi-Yuan 梓源 , Yao 姚 Qin-Yuan 沁远 , Qiu 邱 Jun 俊 , Ma 麻 Jian-Zuo 建坐 , Li 李 Wei-Guo 卫国
Published: April 2024

Based on the force–heat equivalence energy density principle, a theoretical model for magnetic metallic materials is developed, which characterizes the temperature-dependent magnetic anisotropy energy by considering the equivalent relationship between magnetic anisotropy energy and heat energy; then the relationship between the magnetic anisotropy constant and saturation magnetization is considered. Finally, we formulate a temperature-dependent model for saturation magnetization, revealing the inherent relationship between temperature and saturation magnetization. Our model predicts the saturation magnetization for nine different magnetic metallic materials at different temperatures, exhibiting satisfactory agreement with experimental data. Additionally, the experimental data used as reference points are at or near room temperature. Compared to other phenomenological theoretical models, this model is considerably more accessible than the data required at 0 K. The index included in our model is set to a constant value, which is equal to 10/3 for materials other than Fe, Co, and Ni. For transition metals (Fe, Co, and Ni in this paper), the index is 6 in the range of 0 K to 0.65T
cr (T
cr is the critical temperature), and 3 in the range of 0.65T
cr to T
cr, unlike other models where the adjustable parameters vary according to each material. In addition, our model provides a new way to design and evaluate magnetic metallic materials with superior magnetic properties over a wide range of temperatures.
Role of magnetic fields on the outer crust in a magnetar*
Authors: Jiang 蒋 Wei 威 , Chen 陈 Yan-jun 晏军
Published: April 2024

We explore the properties of 4110 nuclides from

to

with the Sky3D code and the composition of the outer crust in magnetars under extreme magnetic fields. The effects of the variation in nuclear masses due to magnetic fields on the outer crust are comprehensively studied. The neutron-drip transition pressure, equation of state, and neutron fraction in the outer crust are also discussed.
Moving doubly heavy baryon in a strongly coupled plasma via holography*
Authors: Liu 刘 Xuan 旋 , Jiang 江 Jia-Jie 佳杰 , Chen 陈 Xun 勋 , Fujita Mitsutoshi , Watanabe Akira
Published: April 2024

Gauge/gravity duality is used to study the properties of the doubly heavy baryon

at finite rapidity and temperature in heavy-ion collisions. We investigate the impact of rapidity on string breaking and screening of

and compare these effects with the results for

in detail. Computations reveal that the string-breaking distances of

and

are close in the confined state, and the effects of rapidity and temperature on the string breaking are not significant. An interesting result shows that

cannot be determined at sufficiently high temperatures and rapidities. However,

can exist under any conditions as long as the separation distance is sufficiently small. Furthermore, the screening distances of

and

are compared at finite rapidity and temperature. Based on the above analysis, we infer that

is more stable than

at finite rapidity and temperature.
Dust Condensation of SiC, SiO in Asymptotic Giant Branch Stellar Winds-SiC Spectrum
Authors: Wu Ruiqing , Zhu Chunhua , Lü Guoliang , Yang Shuming , Meng Zhisen , Zhang Xiaojiao , Lu Xizhen , Yu Jinlong , Chen Wujin , Long Mengqiu
Published: April 2024

We have chosen the Large Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code to calculate the coalescence of silicon carbide (SiC), silicon oxide dust (SiO) in the AGB stellar wind. LAMMPS is a classical molecular dynamics simulation code. At the same time, we consider the effect of temperature on the evolution of molecular dynamics. We also calculated the temperature change of non-spherical SiC, SiO dust coalescence. The condensation temperature range of SiC dust in the AGB stellar wind is [300–500]k and [900–1100]k for SiO. Finally, the infrared spectrum of SiC was calculated using Gaussian 16 software. The 77SiC, 70Si3C3, and 121Si3C3 models have clear characteristic peaks of infrared spectra responding at 5, 8.6, 11.3, 15, 19, and 37 μm.
BSEC Method for Unveiling Open Clusters and its Application to Gaia DR3: 83 New Clusters
Authors: Li Zhong-Mu , Mao Cai-Yan
Published: April 2024

Open clusters (OCs) are common in the Milky Way, but most of them remain undiscovered. There are numerous techniques, including some machine-learning algorithms, available for the exploration of OCs. However, each method has its limitations and therefore, different approaches to discovering OCs hold significant values. We develop a comprehensive approach method to automatically explore the data space and identify potential OC candidates with relatively reliable membership determination. This approach combines the techniques of Hierarchical Density-Based Spatial Clustering of Applications with Noise, Gaussian mixture model, and a novel cluster member identification technique, color excess constraint. The new method exhibits efficiency in detecting OCs while ensuring precise determination of cluster memberships. Because the main feature of this technique is to add an extra constraint (EC) for the members of cluster candidates using the homogeneity of color excess, compared to typical blind search codes, it is called Blind Search-Extra Constraint (BSEC) method. It is successfully applied to the Gaia Data Release 3, and 83 new OCs are found, whose color–magnitude diagrams (CMDs) are fitted well to the isochrones. In addition, this study reports 621 new OC candidates with discernible main sequence or red giant branch. It is shown that BSEC technique can discard some false negatives of previous works, which takes about three percentage of known clusters. It shows that as an EC, the color excess (or two-color) constraint is useful for removing fake cluster member stars from the clusters that are identified from the positions and proper motions of stars, and getting more precise CMDs, when differential reddening of member stars of a cluster is not large (e.g., ΔE(G
BP − G
RP) < 0.5 mag). It makes the CMDs of 15% clusters clearer (in particular for the region near turnoff) and therefore is helpful for CMD and stellar population studies. Our result suggests that the color excess constraint is more appropriate for clusters with small differential reddening, such as globular clusters or older OCs, and clusters that the distances of member stars cannot be determined accurately.
First Light Curve Analysis of NSVS 8294044, V1023 Her, and V1397 Her Contact Binary Systems
Authors: Poro Atila , Baudart Sabrina , Nourmohammad Mahshid , Sabaghpour Arani Zahra , Farhadi Fatemeh , Ranjbar Salehian Selda , Sarostad Ahmad , Ranjbaryan Iri Olya Saeideh , Hadizadeh Maryam , Khodaei AmirHossein
Published: April 2024

The first photometric light curve investigation of the NSVS 8294044, V1023 Her, and V1397 Her binary systems is presented. We used ground-based observations for the NSVS 8294044 system and Transiting Exoplanet Survey Satellite data for V1023 Her and V1397 Her. The primary and secondary times of minima were extracted from all the data, and, by collecting the literature, a new ephemeris was computed for each system. Linear fits for the O − C diagrams were conducted using the Markov Chain Monte Carlo (MCMC) method. Light curve solutions were performed using the PHysics Of Eclipsing BinariEs Python code and the MCMC approach. The systems were found to be contact binary stars based on the fillout factor and mass ratio. V1023 Her showed the O’Connell effect, and a cold starspot on the secondary component was required for the light curve solution. The absolute parameters of the system were estimated based on an empirical relationship between orbital period and mass. We presented a new T–M equation based on a sample of 428 contact binary systems and found that our three target systems were in good agreement with the fit. The positions of the systems were also depicted on the M–L, M–R, q–L
ratio, and M
tot–J
0 diagrams in the logarithmic scales.
Coalescent processes emerging from large deviations
Authors: Levien Ethan
Published: April 2024

The classical model for the genealogies of a neutrally evolving population in a fixed environment is due to Kingman. Kingman’s coalescent process, which produces a binary tree, emerges universally from many microscopic models in which the variance in the number of offspring is finite. It is understood that power-law offsprings distributions with infinite variance can result in a very different type of coalescent structure with merging of more than two lineages. Here, we investigate the regime where the variance of the offspring distribution is finite but comparable to the population size. This is achieved by studying a model in which the log offspring sizes have stretched exponential tails. Such offspring distributions are motivated by biology, where they emerge from a toy model of growth in a heterogeneous environment, but also from mathematics and statistical physics, where limit theorems and phase transitions for sums over random exponentials have received considerable attention due to their appearance in the partition function of Derrida’s random energy model (REM). We find that the limit coalescent is a β-coalescent—a previously studied model emerging from evolutionary dynamics models with heavy-tailed offspring distributions. We also discuss the connection to previous results on the REM.
On the atypical solutions of the symmetric binary perceptron
Authors: Barbier Damien , El Alaoui Ahmed , Krzakala Florent , Zdeborová Lenka
Published: April 2024

We study the random binary symmetric perceptron problem, focusing on the behavior of rare high-margin solutions. While most solutions are isolated, we demonstrate that these rare solutions are part of clusters of extensive entropy, heuristically corresponding to non-trivial fixed points of an approximate message-passing algorithm. We enumerate these clusters via a local entropy, defined as a Franz–Parisi potential, which we rigorously evaluate using the first and second moment methods in the limit of a small constraint density

α

(corresponding to vanishing margin

κ

) under a certain assumption on the concentration of the entropy. This examination unveils several intriguing phenomena: (i) we demonstrate that these clusters have an entropic barrier in the sense that the entropy as a function of the distance from the reference high-margin solution is non-monotone when

κ
⩽
1.429

−
α

/

log
⁡

α

, while it is monotone otherwise, and that they have an energetic barrier in the sense that there are no solutions at an intermediate distance from the reference solution when

κ
⩽
1.239

−
α

/

log
⁡

α

. The critical scaling of the margin

κ

in

−
α

/

log
⁡
α

corresponds to the one obtained from the earlier work of Gamarnik et al (2022 (arXiv:2203.15667)) for the overlap-gap property, a phenomenon known to present a barrier to certain efficient algorithms. (ii) We establish using the replica method that the complexity (the logarithm of the number of clusters of such solutions) versus entropy (the logarithm of the number of solutions in the clusters) curves are partly non-concave and correspond to very large values of the Parisi parameter, with the equilibrium being reached when the Parisi parameter diverges.
Wet 3D printing of biodegradable porous scaffolds to enable room-temperature deposition modeling of polymeric solutions for regeneration of articular cartilage
Authors: Yu Xiaoye , Wang Peng , Gao Jingming , Fu Ye , Wang Qunsong , Chen Jun , Chen Shiyi , Ding Jiandong
Published: April 2024

Tissue engineering has emerged as an advanced strategy to regenerate various tissues using different raw materials, and thus it is desired to develop more approaches to fabricate tissue engineering scaffolds to fit specific yet very useful raw materials such as biodegradable aliphatic polyester like poly (lactide-co-glycolide) (PLGA). Herein, a technique of ‘wet 3D printing’ was developed based on a pneumatic extrusion three-dimensional (3D) printer after we introduced a solidification bath into a 3D printing system to fabricate porous scaffolds. The room-temperature deposition modeling of polymeric solutions enabled by our wet 3D printing method is particularly meaningful for aliphatic polyester, which otherwise degrades at high temperature in classic fuse deposition modeling. As demonstration, we fabricated a bilayered porous scaffold consisted of PLGA and its mixture with hydroxyapatite for regeneration of articular cartilage and subchondral bone. Long-term in vitro and in vivo degradation tests of the scaffolds were carried out up to 36 weeks, which support the three-stage degradation process of the polyester porous scaffold and suggest faster degradation in vivo than in vitro. Animal experiments in a rabbit model of articular cartilage injury were conducted. The efficacy of the scaffolds in cartilage regeneration was verified through histological analysis, micro-computed tomography (CT) and biomechanical tests, and the influence of scaffold structures (bilayer versus single layer) on in vivo tissue regeneration was examined. This study has illustrated that the wet 3D printing is an alternative approach to biofabricate tissue engineering porous scaffolds based on biodegradable polymers.
A new lower bound for the number of conjugacy classes
Authors: Çınarcı Burcu , Keller Thomas
Published: April 2024

In 2000, Héthelyi and Külshammer [Bull. London Math. Soc. 32 (2000), pp. 668–672] proposed that if

G
G

is a finite group,

p
p

is a prime dividing the group order, and

k
(
G
)

k(G)

is the number of conjugacy classes of

G
G

, then

k
(
G
)
≥
2

p
−
1

k(G)\geq 2\sqrt {p-1}

, and they proved this conjecture for solvable

G
G

and showed that it is sharp for those primes

p
p

for which

p
−
1

\sqrt {p-1}

is an integer. This initiated a flurry of activity, leading to many generalizations and variations of the result; in particular, today the conjecture is known to be true for all finite groups. In this note, we put forward a natural new and stronger conjecture, which is sharp for all primes

p
p

, and we prove it for solvable groups, and when

p
p

is large, also for arbitrary groups.
On normalized tails of series expansion of generating function of Bernoulli numbers
Authors: Zhang Gui-Zhi , Yang Zhen-Hang , Qi Feng
Published: April 2024

In the paper, the authors present the positivity and decreasing property of the normalized tails of the series expansion of the generating function of the classical Bernoulli numbers and prove the increasing property of the ratio between two normalized tails of the series expansion of the generating function of the classical Bernoulli numbers by showing the increasing property of the ratio between two Bernoulli polynomials.
Lipschitz bounds for nonuniformly elliptic integral functionals in the plane
Authors: Schäffner Mathias
Published: April 2024

We study local regularity properties of local minimizer of scalar integral functionals with controlled

(
p
,
q
)

(p,q)

-growth in the two-dimensional plane. We establish Lipschitz continuity for local minimizer under the condition

1
>
p
≤
q
>
∞

1>p\leq q>\infty

with

q
>
3
p

q>3p

which improve upon the classical results valid in the regime

q
>
2
p

q>2p

. Along the way, we establish an

L
∞

L^\infty

-

L
2

L^2

-estimate for solutions of linear uniformly elliptic equations in the plane which is optimal with respect to the ellipticity contrast of the coefficients.
Implicit weight bias: shared neural substrates for overweight and angry facial expressions revealed by cross-adaptation
Authors: Luo Xu , Zhao Danning , Gao Yi , Yang Zhihao , Wang Da , Mei Gaoxing
Published: April 2024

The perception of facial expression plays a crucial role in social communication, and it is known to be influenced by various facial cues. Previous studies have reported both positive and negative biases toward overweight individuals. It is unclear whether facial cues, such as facial weight, bias facial expression perception. Combining psychophysics and event-related potential technology, the current study adopted a cross-adaptation paradigm to examine this issue. The psychophysical results of Experiments 1A and 1B revealed a bidirectional cross-adaptation effect between overweight and angry faces. Adapting to overweight faces decreased the likelihood of perceiving ambiguous emotional expressions as angry compared to adapting to normal-weight faces. Likewise, exposure to angry faces subsequently caused normal-weight faces to appear thinner. These findings were corroborated by bidirectional event-related potential results, showing that adaptation to overweight faces relative to normal-weight faces modulated the event-related potential responses of emotionally ambiguous facial expression (Experiment 2A); vice versa, adaptation to angry faces relative to neutral faces modulated the event-related potential responses of ambiguous faces in facial weight (Experiment 2B). Our study provides direct evidence associating overweight faces with facial expression, suggesting at least partly common neural substrates for the perception of overweight and angry faces.