bluuebunny/crossref_metadata_2025 huggingface dataset:
3D printing of multifunctional hydrogel scaffolds based on recombinant collagen for bile duct repair
Authors: Zhang Jianquan , Gao Yuanhui , Yang Yijun , Cheng Qiuhua , Feng Longbao , Lei Zhongwen , Zhang Xiaoyu , Xiang Yang
Published: February 2025

Bile duct injuries remain a significant clinical challenge following hepatobiliary surgeries. Recently, 3D-printed tubular scaffolds have shown promise as effective solutions for bile duct tissue repair. This study presents a novel bi-layered bile duct scaffold, fabricated using advanced three-dimensional printing technology. The inner layer of this scaffold is constructed from poly(ε-caprolactone) methacrylate (PCLMA), which imparts high mechanical strength. The outer layer is composed of biocompatible methacrylated recombinant type I collagen (rColMA) and ε-poly(L-lysine)-methacrylamide (EPLMA), providing excellent antibacterial properties. In addition, encapsulated interleukin-6-loaded liposomes (IL-6@Lip) are incorporated into the outer layer to further promote tissue regeneration. This innovative design creates an optimal microenvironment for the growth and differentiation of bone marrow mesenchymal stem cells (BMSCs) into bile duct-like cells. These differentiated cells contribute to bile duct tissue regeneration, as evidenced by the expression of key differentiation markers, including CK7, CK19, AQP1, AE2, and CX43. The rColMA/EPLMA/IL-6@Lip hydrogel in the outer layer of the scaffold significantly enhances BMSC proliferation and their differentiation into bile duct epithelial cells. Furthermore, in vivo experiments show that the PCLMA//rColMA/EPLMA/IL-6@Lip bi-layered scaffold does not induce bile stasis. This novel, pre-differentiated 3D-printed active scaffold offers valuable insights into bile duct tissue regeneration and replacement research.
Rapid restoration of potent neutralization activity against the latest Omicron variant JN.1 via AI rational design and antibody engineering
Authors: Liao Yunji , Ma Hang , Wang Zhenyu , Wang Shusheng , He Yang , Chang Yunsong , Zong Huifang , Tang Haoneng , Wang Lei , Ke Yong , Cai Huiyu , Li Ping , Tang Jian , Chen Hua , Drelich Aleksandra , Peng Bi-Hung , Hsu Jason , Tat Vivian , Tseng Chien-Te K. , Song Jingjing , Yuan Yunsheng , Wu Mingyuan , Liu Junjun , Yue Yali , Zhang Xiaoju , Wang Ziqi , Yang Li , Li Jing , Ni Xiaodan , Li Hongshi , Xiang Yuning , Bian Yanlin , Zhang Baohong , Yin Haiyang , Dimitrov Dimiter S. , Gilly John , Han Lei , Jiang Hua , Xie Yueqing , Zhu Jianwei
Published: February 2025

The rapid evolution of the viral genome has led to the continual generation of new variants of SARS-CoV-2. Developing antibody drugs with broad-spectrum and high efficiency is a long-term task. It is promising but challenging to develop therapeutic neutralizing antibodies (nAbs) through in vitro evolution based on antigen–antibody binding interactions. From an early B cell antibody repertoire, we isolated antibody 8G3 that retains its nonregressive neutralizing activity against Omicron BA.1 and various other strains in vitro. 8G3 protected ACE2 transgenic mice from BA.1 and WA1/2020 virus infection without adverse clinical manifestations and completely cleared viral load in the lungs. Similar to most IGHV3–53 antibodies, the binding sites of 8G3 and ACE2 largely overlap, enabling competition with ACE2 for binding to RBD. By comprehensively considering the binding free energy changes of the antigen–antibody complexes, the biological environment of their interactions, and the evolutionary direction of the antibodies, we were able to select 50 mutants. Among them, 11 were validated by experiments showing better neutralizing activities. Further, a combination of four mutations were identified in 8G3 that increased its neutralization potency against JN.1, the latest Omicron mutant, by approximately 1,500-fold, and one of the mutations led to an improvement in activity against multiple variants to a certain extent. Together, we established a procedure of rapid selection of neutralizing antibodies with potent SARS-CoV-2 neutralization activity. Our results provide a reference for engineering neutralizing antibodies against future SARS-CoV-2 variants and even other pandemic viruses.
Zoo Tourism – A Typical Part of Central-European Travelling: An Example from Czechia
Authors: Nekolný Lukáš
Published: February 2025

Zoos are among the most visited tourist and leisure destinations. Moreover, for post-socialist Central and Eastern Europe, visits to zoos are typical. Unlike Western “capitalist” Europe, in post-socialist Europe there were for a long time almost no amusement parks and thanks to this zoos have been long-term key places of (urban) recreation. Due to the different historical developments, the zoos of Central and Eastern Europe differ in terms of time of establishment, location, and ownership compared to those in the west. The collapse of the socialist establishment had a fundamental impact on the future of zoos. After the fall of the Iron Curtain, there was a sharp drop in zoo attendance in the countries of today’s post-socialist Europe, but since the mid-1990s after large innovations, it has been rising again, reaching record highs. The period after 1990 allowed private ownership and brought about the development of private zoos and further expanded forms of zoo tourism.

Information

© The Author 2025
Gravitational wave signal prediction technique based on advanced seasonal-trend decomposition using Loess
Authors: Jia Dongbao , Ma Rui , Xu Weixiang , Zhao Shiwei , Ruan Wenjun , Xu Zhongxun
Published: February 2025

Gravitational wave (GW) analysis is attracting widespread attention as an emerging research field. As the presence of substantial noise in GW signals, and the characteristics of inspiral and merger stage are different, coupled with the sidelobe effect caused by window length, traditional time–frequency analysis methods face significant challenges in accurately analyzing the frequency variations of GW signals. This poses a major limitation in the precise analysis stage following GW detection. Therefore, we proposed a novel method of seasonal-trend decomposition using Loess with multilayer perceptron (STLMLP), for predicting and validating the accuracy and effectiveness of GW frequency variations. Experiment results on three noiseless GW templates demonstrate that STLMLP exhibits the adaptability and highest prediction accuracy for the dynamic frequency variations of GW signals compared to five state-of-the-art machine learning and deep learning methods. Furthermore, experiments conducted on three noisy actual GW data compared with the state-of-the-art method of Fourier-based synchrosqueezing transform in the signal processing domain confirm that STLMLP maintains lower error in predicting frequency change over the whole duration of the actual noisy GW signals.
Constructing topological insulator-ferromagnet heterojunctions of Bi2Se3/Fe3GeTe2 and Bi2Te3/Fe3GaTe2
Authors: Liang Xinke , Chen Fuhong , Yang Liu , Yang Tingting , Xiao Peiyao , Liu Yuxiang , Wang Zhiwei , Xiao Wende
Published: February 2025

Heterostructures composed of topological insulators and ferromagnets are predicted to exhibit the quantum anomalous Hall effect (QAHE). The morphology and interfacial structure have a significant impact on physical properties and transport performances of such heterostructures. Here, we report the epitaxial growth of topological insulators Bi2Se3 and Bi2Te3 thin films on ferromagnetic substrates of Fe3GeTe2 and Fe3GaTe2, respectively. The morphology and composition of the Bi2Se3 and Bi2Te3 thin films were characterized using atomic force microscopy, x-ray photoelectron spectroscopy and Raman spectroscopy. After optimizing growth parameters, we successfully generated large-area films with high crystallinity, presenting new types of topological insulator-ferromagnet heterojunctions for the pursuit of QAHE.
Graphene-based materials and electrochemical biosensors: an overview
Authors: Joshi Rita , Ravindran K Veena , Lahiri Indranil
Published: February 2025

Graphene, an exceptional two-dimensional material, has attracted significant attention from the scientific community. Its unique physiochemical properties make it a suitable candidate for many applications in the field of biotechnology and medical sciences. High specific surface area, exceptionally high electrical conductivity, and good biocompatibility of graphene give it a large scope in disease diagnosis and biosensing applications. This review aims at presenting the advances in the journey of graphene-based materials and their successful implication as electrochemical nanobiosensors. The first part of the review summarizes the history, structure, and recent developments in the large-scale production of graphene. It further includes the sensing mechanism, the recent trends in biosensing, and improvements in graphene-based biosensors. The comparative analysis shows graphene-based electrochemical biosensors to have high sensitivity, long-term stability, and low detection limits compared to the various other biosensors.
The needle assembly mixed anomaly ray image detection method for needle roller bearings based on double threshold segmentation
Authors: Yang Yun , Liang ZhenYu
Published: February 2025

Needle roller bearings without cages are extensively utilized in the mechanical transmission systems of various equipment due to their high load-carrying capacity and compact design. However, due to the limited performance of the current needle loading equipment, abnormalities such as missing needles, skewed needles and toppling needles. If abnormal bearings are installed in the equipment above, it will make the equipment appear noisy, vibration is obvious, the smoothness of operation is reduced. To address this issue, this paper proposes a systematic detection method based on double-threshold segmentation for identifying mixed needle assembly anomalies. Initially, starting from the principles of ray detection, we analyze the characteristics of ray imaging for different needle assembly anomalies in needle roller bearings. Image samples of single and mixed needle assembly anomalies are collected using a ray detection platform. Subsequently, a dual-threshold segmentation method is introduced for mixed needle assembly abnormality images by combining different regions of the needle-bearing ray image and the grey value characteristics of the anomalies for threshold selection. A step-by-step detection method based on dual-threshold segmentation is then proposed. This method utilizes a mask to extract the non-needle assembly region in the high-threshold segmented image, achieving identification and quantification of skewed and toppling needles based on area threshold information of the abnormal needle roller contour. Additionally, a ring mask is employed to extract the needle roller gap in the low-threshold segmented image, allowing for the screening of the needle gap contour based on the area threshold, thus identifying and quantifying missing needle anomalies. Finally, experimental verification is conducted on various needle assembly anomaly images, demonstrating that the proposed method can effectively identify and quantify different needle assembly anomalies in needle roller bearings, offering valuable application insights for quality inspection during needle assembly processes.
A robust navigation algorithm without GNSS based on deep learning and variational Bayesian filter
Authors: Guo Yusheng , Sun Yihong , Zhuang Guangchen , Zhou Ding
Published: February 2025

Integrated navigation systems, combining inertial navigation system (INS) and global navigation satellite system (GNSS), are extensively used in land vehicle navigation. However, they often exhibit poor performance during GNSS outages and lack robustness in challenging urban environments. In order to reduce reliance on GNSS and fully leverage the vehicle dynamics hidden in the data, this study proposes a novel robust navigation algorithm without GNSS, based on deep learning and variational Bayesian methods. Firstly, a cascaded long and short term memory (LSTM) model with an ‘attitude-velocity’ two-step sequential structure is proposed. By incorporating quaternions, it overcomes the non-differentiable property of attitude caused by its bounded nature, resulting in more accurate attitude predictions. Subsequently, the attitude prediction results are utilized to enhance speed prediction, leading to a significant improvement in accuracy. Building upon the cascaded LSTM model, variational Bayesian filtering is employed to further address the complex time-varying error of its results. Through an adaptive data fusion of LSTM predictions and INS data, the data fluctuations are reduced, and the accuracy is significantly improved. The efficacy of the proposed robust navigation algorithm is validated through multiple vehicle experiments conducted on diverse paths. Experimental results demonstrate that even in scenarios where GNSS fails continuously for 15 min, the proposed algorithm maintains of speed and horizontal attitude errors within 0.6 m s−1 (root mean squared error (RMSE)) and 0.3° (RMSE) respectively. Consequently, the proposed algorithm has broad application prospects in GNSS-denied environments such as building occlusion, underground parking garages, and indoor positioning. In addition, we also provide attempts to improve the model for situations such as odometer assistance and different motion states.
CycleH-CUT: an unsupervised medical image translation method based on cycle consistency and hybrid contrastive learning
Authors: Jiang Weiwei , Qin Yingyu , Wang Xiaoyan , Chen Qiuju , Guan Qiu , Lu Minhua
Published: February 2025

Unsupervised medical image translation tasks are challenging due to the difficulty of obtaining perfectly paired medical images. CycleGAN-based methods have proven effective in unpaired medical image translation. However, these methods can produce artifacts in the generated medical images. To address this issue, we propose an unsupervised network based on cycle consistency and hybrid contrastive unpaired translation (CycleH-CUT). CycleH-CUT consists of two CUT (H-CUT) networks. In the H-CUT network, a query-selected attention mechanism is adopted to select queries with important features. The boosted contrastive learning loss is employed to reweight all negative patches via the optimal transport strategy. We further apply spectral normalization to improve training stability, allowing the generator to extract complex features. On the basis of the H-CUT network, a new CycleH-CUT framework is proposed to integrate contrastive learning and cycle consistency. Two H-CUT networks are used to reconstruct the generated images back to the source domain, facilitating effective translation between unpaired medical images. We conduct extensive experiments on three public datasets (BraTS, OASIS3, and IXI) and a private Spinal Column dataset to demonstrate the effectiveness of CycleH-CUT and H-CUT. Specifically, CycleH-CUT achieves an average SSIM of 0.926 in the BraTS dataset, an average SSIM of 0.796 on the OASIS3 dataset, an average SSIM of 0.932 on the IXI dataset, and an average SSIM of 0.890 on the private Spinal Column dataset.
High-performance KNN-based piezoelectric ceramics for buzzer application
Authors: Xiong Cheng , Li Bosen , Liao Zhongxin , Qiu Yan , Gao Daqiang
Published: February 2025

Piezoelectric ceramic material is an important component of piezoelectric buzzer, where the parameter of inverse piezoelectric coefficient (d
33
*) plays the decisive role in the performance of the buzzer. Here, we reported the manufacture and performance of lead-free ceramics (0.96(K0.5Na0.5)(Nb0.96Sb0.04)O3-0.04(Bi0.5Na0.5)ZrO3-1mol% Al2O3, abbreviated as KNNS-BNZ-1mol% Al2O3) based piezoelectric buzzer, compared with commercial (PbZr0.5Ti0.5O3, abbreviated as PZT) ceramics. Briefly, KNN-based ceramics had a typical perovskite structure and revealed the piezoelectric properties of d
33=480 pC/N, k
p =0.62 and d
33
*=830 pm/V, compared to d
33=500 pC/N, k
p=0.6 and d
33
*=918 pm/V of the commercial PZT-4 ceramics. Our results showed that the KNNS-BNZ-1% Al2O3 ceramics had a similar sound pressure level (SPL) performance over the testing frequency range with commercial PZT ceramics (even better in range of 3-4 kHz). These findings open vast possibilities toward the great application potential of the KNN-based piezoelectric ceramics.
Automated DC voltage and DC resistance real-time multiple standard for artifact calibration of calibrators and multimeters
Authors: Galliana F. , Capra P. , Cerri R. , Francese C. , Lanzillotti M. , Roncaglione Tet L. , Pennecchi F. , Pollarolo A.
Published: February 2025

An automated temperature-controlled electrical DC voltage
and DC resistance multiple reference standard (MRS) has been
developed by Measurements International (MI) with the scientific
support from the Istituto Nazionale di Ricerca Metrologica
(INRIM). The MRS includes a 10 V, a 1 Ω, and a
10 kΩ standards selectable via a switch unit. This setup
allows the artifact calibration of high-end calibrators and
multimeters used in low-frequency electrical measurements. The two
resistors are high-stability standards from MI, while the 10 V
standard is based on a low-noise circuit developed by INRIM in
collaboration with MI. A key innovation is the internal real-time
clock calendar, which displays the calibration values of the MRS
standards and their updated values internally calculated. This
ensures reliable use of the MRS standards over extended periods
between calibrations, effectively minimizing uncertainties due to
their drift. The standards are housed in a thermal box, minimizing
temperature variations. The MRS standards meet the uncertainty
requirements defined by calibrators and multimeters manufacturers
for artifact calibration and can also serve as laboratory references
or travelling standards for interlaboratory comparisons (ILCs). MI
is currently commercializing the MRS.
Temperature dependence of the electric field strength in a pyroelectric deflector of charged relativistic particles
Authors: Ivashchuk O.O. , Kishin I.A. , Kidanova E.Y. , Dronik V.I. , Gilts M.E. , Kenzhebayeva Zh.E. , Allaniyazova M.A.
Published: February 2025

The paper presents the dependence of the electric field
strength between the crystals of a pyroelectric deflector on their
temperature at various rates of temperature change in a
vacuum. Three measurement cycles were conducted at different heating
rates (0.059∘C/s, 0.015∘C/s, and
0.008∘C/s) followed by subsequent natural cooling. A
phenomenon of electric field strength saturation was observed in the
temperature range of 40–72∘C during heating and
50–22∘C during cooling of the crystals in the pyroelectric
deflector under vacuum conditions. A discrepancy in trends between
the extreme states is observed on the graphs of the temperature
dependence of the electric field strength in the pyroelectric
deflector. The maximum electric field strength between the crystals
reaches 40 kV/cm. A tentative explanation is provided for the
occurrence of electrical breakdowns between pyroelectric crystals at
an electric field strength of 30 kV/cm and a residual gas pressure
of 1.5 × 10-5 Torr. The potential application of the
pyroelectric deflector in accelerator systems and the prospects for
the development of miniature charged particle deflectors are
discussed.
Attribution and projection of regional winter wind energy drought in Europe
Authors: Yu Shuang , Vautard Robert
Published: February 2025

The decline of surface wind speed in many regions of the world is an important phenomenon as it is potentially expected to decrease wind power production. It is not clear, however, whether this decline takes the form of a gradual wind speed decrease or an increase in “wind energy droughts”, long periods with weak wind speeds. Both types of wind speed reductions contribute to a decline in wind power production. Prolonged and more frequent wind energy droughts, in particular, may reduce revenue and jeopardize wind farm projects. Past and future changes in wind energy droughts, as well as their underlying drivers, remain poorly understood. Here we show that winter wind energy droughts will become more probable in Europe and the return period of 10.3-year events during 1971-2000 have been shortened to about 10 years in the whole Europe, and it would be shortened to about 6.6 years during 2041-2070, under uncurbed greenhouse gases emission (scenario RCP8.5). In the current period, low wind energy winter has become more probable in most European countries, especially in the northern countries, showing a higher probability ratio of wind droughts. In the future, for some southern countries, the frequency of wind energy winter droughts is projected to decrease compared with the current period, which is helpful for the development of wind power generation in these countries. In addition, the changes in wind energy droughts are sensitive to the global warming level. With global warming at 1.5, 2, 3, 4 ℃ levels, low wind energy winter in Europe will occur more frequently as the probability is more than 1.13, 1.46, 1.53, 1.60 times as much as that in the current climate, respectively. The regional difference of attribution is meaningful for the optimization of wind energy transmission networks in Europe, which may be considered by large-scale wind energy producers.
Influence of asymmetric microchannels in the structure and function of engineered neuronal circuits
Authors: Mateus J C , Melo P , Aroso M , Charlot B , Aguiar P
Published: February 2025

Understanding the intricate structure–function relationships of neuronal circuits is crucial for unraveling how the brain achieves efficient information transfer. In specific brain regions, like the hippocampus, neurons are organized in layers and form unidirectional connectivity, which is thought to help ensure controlled signal flow and information processing. In recent years, researchers have tried emulating these structural principles by providing cultured neurons with asymmetric environmental cues, namely microfluidics’ microchannels, which promote directed axonal growth. Even though a few reports have claimed to achieve unidirectional connectivity of in vitro neuronal circuits, given the lack of functional characterization, it remains unknown if this structural connectivity correlates with functional connectivity. We have replicated and tested the performance of asymmetric microchannel designs previously reported in the literature to be successful in promoting directed axonal growth, as well as other custom variations. A new variation of ‘Arrowhead’, termed ‘Rams’, was the best-performing motif with a ∼76% probability per microchannel of allowing strictly unidirectional connections at 14 d in vitro. Importantly, we assessed the functional implications of these different asymmetric microchannel designs. For this purpose, we combined custom microfluidics with microelectrode array technology to record the electrophysiological activity of two segregated populations of hippocampal neurons (‘Source’ and ‘Target’). This functional characterization revealed that up to ∼94% of the spiking activity recorded along microchannels with the ‘Rams’ motif propagates towards the ‘Target’ population. Moreover, our results indicate that these engineered circuits also tended to exhibit network-level synchronizations with defined directionality. Overall, this functional characterization of the structure–function relationships promoted by asymmetric microchannels has the potential to provide insights into how neuronal circuits use specific network architectures for effective computations. Moreover, the here-developed devices and approaches may be used in a wide range of applications, such as disease modeling or preclinical drug screening.
Simulating open quantum systems with giant atoms
Authors: Chen Guangze , Frisk Kockum Anton
Published: February 2025

Open quantum many-body systems are of both fundamental and applicational interest. However, it remains an open challenge to simulate and solve such systems, both with state-of-the-art classical methods and with quantum-simulation protocols. To overcome this challenge, we introduce a simulator for open quantum many-body systems based on giant atoms, i.e. atoms (possibly artificial), that couple to a waveguide at multiple points, which can be wavelengths apart. We first show that a simulator consisting of two giant atoms can simulate the dynamics of two coupled qubits, where one qubit is subject to different drive amplitudes and dissipation rates. This simulation enables characterizing the quantum Zeno crossover in this model. We further show that by equipping the simulator with post-selection, it becomes possible to simulate the effective non-Hermitian Hamiltonian dynamics of the system and thereby characterize the transition from oscillatory to non-oscillatory dynamics due to varying dissipation rates. We demonstrate and analyze the robustness of these simulation results against noise affecting the giant atoms. Finally, we discuss and show how giant-atom-based simulators can be scaled up for digital–analog simulation of large open quantum many-body systems, e.g. generic dissipative spin models.
Reporting units in life-cycle assessments of hospitals: a systematized review of the literature
Authors: Keil Mattis
Published: February 2025

This systematized literature review aims to assess reporting units used by hospital LCAs to communicate their environmental impact through life-cycle assessment (LCA). As the healthcare sector increasingly prioritizes sustainability, understanding the choice of reporting unit is crucial. This analysis aims to provide recommendations for effective communication of environmental performance. A systematized literature search was conducted for LCAs and carbon footprint studies of healthcare organizations or systems in the databases PubMed and Web of Science. The identified units were analyzed using seven criteria, including the differentiation between input and output flows, treatment complexities, quantity of provided services, quality of provided services, longevity of services, matching with system boundaries, and data availability. Seven reporting flows were identified: (i) floor area, (ii) number of beds, (iii) workforce, (iv) expenditure, (v) patient load, (vi) revenue, and (vii) the diagnosis-related groups case mix. Each flow has its own advantages and disadvantages; the best reporting flow for an assessment depends on the specific goals and objectives and should be meaningful to stakeholders. However, none of the reporting flows measure the actual function of healthcare organizations, i.e. the impact on the health of the patients. However, data on this flow, such as quality-adjusted life years, are not available in a meaningful quantity. In conclusion, this literature review highlights the importance of reporting unit selection in communicating the environmental impact of healthcare organizations through LCA. The present analysis identified seven reporting flows, each with its own advantages and disadvantages. These findings are of importance for decision makers to contextualize given data and to choose the most suitable reporting flow for their own assessment. Future research might evaluate the quantitative impact of the reporting flow decision.
Stallings’s Fibring Theorem and 𝑃𝐷³-pairs
Authors: Bridson Martin , Kielak Dawid , Kudlinska Monika
Published: February 2025

We give a relatively self-contained proof that if a group

G
G

fibres algebraically and is part of a

P
D

3

\mathrm {PD}^3

-pair, then

G
G

is the fundamental group of a fibred compact aspherical 3-manifold. This yields a homological proof of a classical theorem of Stallings: if

G
=

π
1

(

M
3

)

G = \pi _1(M^3)

is the fundamental group of a compact irreducible 3-manifold

M
3

M^3

and

ϕ
:
G
→

Z

\phi \colon G \to \mathbb {Z}

is a surjective homomorphism with finitely generated kernel, then

ϕ
\phi

is induced by a topological fibration of

M
3

M^3

over the circle.
Ends of large scale groups
Authors: Dydak Jerzy , Ma Yuankui , Rashed Hussain
Published: February 2025

The aim of this paper is to create a theory of ends of large scale groups, a class containing both finitely generated groups and locally compact, metrizable and connected topological groups. Our generalization amounts to defining the space of ends of any coarse space and then applying it to large scale groups. We prove that, if the number of ends is finite, then it must be at most

2
2

. Groups of two ends are characterized as having an infinite cyclic subgroup of bounded index.

Additionally, we prove a version of Svarc-Milnor Lemma for large scale groups and we prove that coarsely hyperbolic large scale groups have finite asymptotic dimension provided they have bounded geometry.
Near and full quasi-optimality of finite element approximations of stationary second-order mean field games
Authors: Osborne Yohance , Smears Iain
Published: February 2025

We establish a priori error bounds for monotone stabilized finite element discretizations of stationary second-order mean field games (MFG) on Lipschitz polytopal domains. Under suitable hypotheses, we prove that the approximation is asymptotically nearly quasi-optimal in the

H
1

H^1

-norm in the sense that, on sufficiently fine meshes, the error between exact and computed solutions is bounded by the best approximation error of the corresponding finite element space, plus possibly an additional term, due to the stabilization, that is of optimal order with respect to the mesh-size. We thereby deduce optimal rates of convergence of the error with respect to the mesh-size for solutions with sufficient regularity. We further show full asymptotic quasi-optimality of the approximation error in the more restricted case of sequences of strictly acute meshes. Our third main contribution is to further show, in the case where the domain is convex, that the convergence rate for the

H
1

H^1

-norm error of the value function approximation remains optimal even if the density function only has minimal regularity in

H
1

H^1

.
Solid lines in axial algebras of Jordan type \tfrac{1}2 and Jordan algebras
Authors: Desmet Jari
Published: February 2025

We show that a primitive axial algebra of Jordan type

1
2

\tfrac {1}{2}

is a Jordan algebra if and only if every

2
2

-generated subalgebra is solid, a notion introduced recently by Ilya Gorshkov, Sergey Shpectorov and Alexei Staroletov. As a byproduct, we show that a subalgebra generated by axes

a
,
b

a,b

is solid if and only if the associator

[

L
a

,

L
b

]

[L_a,L_b]

is a derivation. Moreover, we show that

2
2

-generated subalgebras that are not solid contain precisely

3
3

axes.
The Emotions of Nonviolence
Authors: Krishnamurthy Meena
Published: February 2025

The Emotions of Nonviolence offers a novel interpretation of Martin Luther King Jr.’s beloved “Letter from Birmingham Jail”: it is not merely a discussion of civil disobedience—as is usually thought—but is also and perhaps even primarily an essay on political motivation. On this reading, the Letter seeks to answer a central question in democratic theory: namely, how can and ought one motivate the racially oppressed to engage in civil disobedience—in what King called nonviolent direct action? King’s answer is that one must appeal to and encourage the political emotions, both positive and negative. Fear, courage, faith, dignity, indignation, and love can together motivate nonviolent action, and nonviolent action can reciprocally motivate and sustain these same emotions. This new and exciting reading of King’s Letter restores its complexity. The Letter’s true addressees are not merely the eight clergymen to whom King explicitly responded but are also the white moderates, Black clergymen, and Black middle-class moderates, and perhaps most of all, the Black masses. Read in this light, the Letter points to an underlying theory of political emotions, details the impediments to action under conditions of injustice, calls various audiences to account for their hypocritical, self-serving, or fearful inaction, engages in propagandizing—working on both intellect and emotion—to motivate a change, and to commend and support the thousands of ordinary Black people already in motion in pursuit of democracy, freedom, and justice.
cfDiffusion: diffusion-based efficient generation of high quality scRNA-seq data with classifier-free guidance
Authors: Zhang Tianjiao , Zhao Zhongqian , Ren Jixiang , Zhang Ziheng , Zhang Hongfei , Wang Guohua
Published: February 2025

Single-cell RNA sequencing (scRNA-seq) technology provides a powerful means to measure gene expression at the individual cell level, thereby uncovering the intricate cellular heterogeneity that underlies various biological processes, including embryonic development, tumor metastasis, and microbial reproduction. However, the variable amounts of data generated across different cell types within tissues can compromise the accuracy of downstream analyses. Traditional approaches for generating scRNA-seq simulation data often rely on predefined data distributions, which can negatively impact the quality of the simulated data. Furthermore, these methods typically focus on simulating single-attribute cells, necessitating substantial additional data for the simulation of multi-attribute cells, which can lead to increased training times. To address these limitations, we propose cfDiffusion, a novel method grounded in diffusion models that incorporates Classifier-Free Guidance and a high-level feature caching mechanism. By leveraging Classifier-Free Guidance, cfDiffusion significantly reduces the training costs associated with model development compared to traditional Classifier Guidance methods. The integration of a caching mechanism further enhances efficiency by shortening inference times. While the inference duration of cfDiffusion remains longer than that of scDiffusion, it exhibits superior expressiveness and efficiency in generating multi-attribute single-cell data. Evaluated across datasets from multiple sequencing platforms, cfDiffusion consistently outperforms state-of-the-art models across various performance metrics. Additionally, cfDiffusion enables the simulation of single-cell data along a pseudo-time scale, facilitating advanced analyses such as tracking cell differentiation, investigating intercellular communication, and elucidating cellular heterogeneity.
mapPat: tracking pathogens evolution in space and time
Authors: Ferrandi Erika , Pesole Graziano , Chiara Matteo
Published: February 2025

Motivation

The COVID-19 pandemic highlighted the importance of genomic surveillance for monitoring pathogens evolution, mitigating the spread of infectious disorders, and informing decision-making by public health authorities. Since the need for the summarization and interpretation of large bodies of data, computational methods are critical for the implementation of effective genomic surveillance strategies.

Results

Here, we introduce mapPat, an R Shiny application for the interactive visualization of pathogens genomic data in space and time. mapPat is designed as a user-friendly dashboard and allows the dynamic monitoring of the evolution of variants, lineages, and mutations in the genome of a pathogen at glance through informative geographic maps and elegant data visuals. mapPat provides a fine-grained map of pathogens evolution and circulation and represents a useful addition to the catalogue of bioinformatics methods for the genomic surveillance of pathogens.

Availability and implementation

mapPat is available at GitHub (https://github.com/F3rika/mapPat.git).
Understanding Ecological Systems Using Knowledge Graphs: An Application to Highly Pathogenic Avian Influenza
Authors: Robertson Hailey , Han Barbara A , Castellanos Adrian A , Rosado David , Stott Guppy , Zimmerman Ryan , Drake John M , Graeden Ellie
Published: February 2025

Motivation

Ecological systems are complex. Representing heterogeneous knowledge about ecological systems is a pervasive challenge because data are generated from many subdisciplines, exist in disparate sources, and only capture a subset of interactions underpinning system dynamics. Knowledge graphs have been successfully applied to organize heterogeneous data and to predict new linkages in complex systems. Though not previously applied broadly in ecology, knowledge graphs have much to offer in an era when system dynamics are responding to rapid changes across multiple scales.

Results

We developed a knowledge graph to demonstrate the method’s utility for ecological problems focused on highly pathogenic avian influenza (HPAI), a highly transmissible virus with a broad host range, wide geographic distribution, and rapid evolution with pandemic potential. We describe the development of a graph to include data related to HPAI including pathogen-host associations, species distributions, and population demographics, using a semantic ontology that defines relationships within and between datasets. We use the graph to perform a set of proof-of-concept analyses validating the method and identifying patterns of HPAI ecology. We underscore the generalizable value of knowledge graphs to ecology including ability to reveal previously known relationships and testable hypotheses in support of a deeper mechanistic understanding of ecological systems.

Availability and implementation

The data and code are available under the MIT License on GitHub at https://github.com/cghss-data-lab/uga-pipp.
Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters
Authors: Lapp Zena , Yoon Hyejin , Foley Brian , Leitner Thomas
Published: February 2025

Motivation

The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment.

Results

Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified.

Availability and implementation

Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html.
Successful resolution of gastric pneumatosis due to a strangulated hiatus hernia and malrotation through non-surgical management: a case report
Authors: Hadani Shiv , Bhatt Dhaara , Bhagat Ashish , Malhotra Vivek
Published: February 2025

Gastric pneumatosis is a rare finding, and clinicians, when under pressure, find it challenging to immediately identify the cause and decide if the patient requires emergency surgery. We present a case where an initial CT scan demonstrated gastric pneumatosis involving only the greater curvature of the antrum caused by a strangulated hiatus hernia and malrotation of the distal stomach. The CT features suggested the patient required immediate surgery; however, a conservative approach was taken, and a follow-up CT scan 4 days after the onset demonstrated complete resolution and no long-term complications.
Common variable immunodeficiency 10, due to a novel variant in the NFKB2 gene, presenting as alopecia universalis and vitiligo
Authors: Wang Lijuan , Zhang Bin
Published: February 2025

Our work demonstrates one CVID patient with novel variants in NFKB2, which emphasizes the importance of genetic testing and long-term follow-up in patients with combined autoimmune manifestations.
Quality matters: chronic kidney disease progression is associated to reduced muscle strength independently of changes in skeletal muscle mass: an observational study
Authors: Chatrenet Antoine , de Müllenheim Pierre-Yves , Torreggiani Massimo , Hernández Julia Nava , Arronte Rocío Urbina , Espinoza Abril Gutiérrez , Piccoli Giorgina Barbara
Published: February 2025

Background and hypothesis

Chronic kidney disease (CKD) is commonly associated with multifactorial neuromuscular impairments. Few studies have investigated CKD-induced changes in maximal voluntary force (MVF), and even fewer have longitudinal follow-up. The aim of this study is to investigate whether CKD progression modifies the relationship between skeletal muscle mass and force and the prevalence of sarcopenia and sarcopenic obesity.

Methods

The data used were prospectively collected during routine check-ups in a network of nutritional centres in Mexico and retrospectively analysed. From a dataset of 5430 patients, we selected 1098 patients with available anthropometric, kidney function, handgrip and bioimpedance data. The relationship between appendicular skeletal muscle mass (ASM) and MVF was investigated using mixed models and adjusted for age, sex, BMI, physical activity level and CKD aetiology. Sarcopenia prevalence were tested across period of follow-up using the Cochran-Mantel-Haenzen for repeated measures and across CKD stages using the Chi-2 test.

Results

After normalization with ASM, MVF was higher in CKD G1-G3 compared to G4 and G5 (p ≤ 0.001, Cohen's d = 0.270–0.576). Slopes between MVF and ASM were lower in CKD G3, G4 and G5 than in CKD G1-G2 (-2.268 [-3.927,-0.609], p = 0.008; -2.694 [-4.593,-0.794], p = 0.006; -3.675 [-5.326,-1.725], p < 0.001, respectively). The prevalence of sarcopenia and sarcopenic obesity did not differ across CKD stages, but recovery was most commonly observed in CKD G1-G2. Slope analysis showed an independent interaction between the slopes of kidney function and ASM on MVF evolution over time.

Conclusions

CKD negatively, progressively and independently affects the neuromuscular system, and force production is reduced for any given muscle mass as CKD progresses. While no association was found between CKD stage and prevalence of sarcopenia, recovery was more frequent in the early CKD stages. These results suggest the importance of early rehabilitation programs to improve musculoskeletal health, quality of life and survival in CKD patients.
Alternating-update-strategy based Graph Autoencoder for graph neural network
Authors: Shan Lingxiao , Li Jian , Liu Guanjun
Published: February 2025

Self-supervised learning (SSL) has become a promising and popular learning paradigm for graph data, offering the advantage of capturing informative knowledge without reliance on manual labels. As a representative class of generative graph SSL models, existing graph autoencoders (GAE) excel in link prediction tasks and are steadily improving in node classification tasks. However, GAE is essentially based on the Information Maximization (InfoMax) principle, always captures much redundant information. In this paper, we propose an Alternating-update-strategy based Graph Autoencoder, including alternating update module (AUM) and GAE. For AUM, we design an Alternating-update-strategy to generate a new graph with reduced redundancy, in order to reduce the amount of redundant information that the encoder may capture. For GAE, we feed it the new graph and employ a re-mask decoding strategy to generate node representations. Our model is evaluated on five common real-world datasets for the node classification task, and the experimental results demonstrate its superiority. Meanwhile, our model has also achieved excellent results in specific e-commerce warehousing application scenarios.
Development and assessment of a prototype of an interproximal image receptor-holding device for use in pediatric dentistry
Authors: Ocampo Thaís Santos Cerqueira , de Alencar-Palha Caio , Cascante-Sequeira Deivi Antonio , Tarosso Réa Marcela , Queiroz Freitas Deborah , Haiter-Neto Francisco
Published: February 2025

Objective

To develop and test a prototype for interproximal radiography positioning intended for pediatric dentistry and compare the technical quality of image receptor-holding devices (IRHD) commonly used in clinical practice.

Methods

Six prototypes, with three wedge dimensions (0.5 mm, 1 mm, and 2 mm) in upper and lower positions on the bitewing surface were compared regarding their capacity to acquire interproximal radiographs without overlapping surfaces with other IRHDs: RinnXCPTM, Hawe KerrTM, and Cone Indicator. Fifteen graduate students obtained images of deciduous molars in a child’s skull and mandible. The chi-square and Fisher's exact tests were employed to analyze significant differences in the number of repetitions and failures in obtaining correct images. A one-way ANOVA assessed the difference between the mean times required for image acquisition according to each IRHD, adopting a significance level of 5%.

Results

The effectiveness of the tested devices, evaluated by the number of correct and incorrect acquisitions using Fisher's exact test, revealed a p-value of 0.057. The ANOVA demonstrated statistically significant differences in the mean acquisition times (p < 0.0000). The upper and lower wedge prototypes 2 mm performed better in acquiring only one radiograph (76.7%) and took less time to execute the technique (1.17 min and 1.12 min, respectively).

Conclusion

The prototypes showed comparable performance to alternative IRHDs but provided advantages in time efficiency and radiation exposure.
Cardiac imaging highlights from European Society of Cardiology 2024: the future is within our grasp!
Authors: Figliozzi Stefano , Hutt Erika , Gimelli Alessia , Jaber Wael A
Published: February 2025

The European Society of Cardiology has held its annual Congress in London, UK, from 30 August to 2 September 2024. With a total of 31 800 participants, 5400 faculty and presenters, and many National Cardiac Societies and industry partners, the Congress has taken an enormous step forward to present and discuss the latest advances in cardiovascular medicine. The sizable intercontinental reach was proved by the fact that 5 of the 10 top countries, in terms of submission of abstracts, were from outside Europe: China, the USA, Japan, Korea, and Australia. This brought a great impetus for international collaboration and exchange of views, learning from different perspectives. Specifically, the field of cardiovascular imaging has been in the spotlight, remarking its growing, central, and transversal role in modern cardiovascular medicine. In this communication, we offer a summary of some notable advances in research, either in terms of novelty or clinical applicability, within the realm of four imaging modalities: echocardiography, cardiovascular magnetic resonance, computed tomography, and nuclear imaging.
From Connections to Merit: Anti-Corruption Reform and Occupational Mobility in China's Civil Service
Authors: Ang Geer , Qin Yu , Tan Ya , Zhang Fan
Published: February 2025

In China, employment in civil service is perceived as a primary path to leadership roles in government. This paper examines the role of family background in shaping the choice to enter civil service and investigates the impact of the 2012 anti-corruption campaign on this process. We find that college graduates with cadre parents are more likely to work as a civil servant. However, using a difference-in-differences approach, we show an 18% decline in this occupational persistence post-campaign. Evidence suggests that reduced use of parental social networks may drive this change. Furthermore, the campaign appears to have improved civil servants’ quality.