bluuebunny/crossref_metadata_2025 huggingface dataset:
Postoperative Musculoskeletal Imaging and Interventions Following Hip Preservation Surgery, Deformity Correction, and Hip Arthroplasty
Authors: Samim Mohammad , Khodarahmi Iman , Burke Christopher , Fritz Jan
Published: January 2025

Total hip arthroplasty and hip preservation surgeries have substantially increased over the past few decades. Musculoskeletal imaging and interventions are cornerstones of comprehensive postoperative care and surveillance in patients undergoing established and more recently introduced hip surgeries. Hence the radiologist's role continues to evolve and expand. A strong understanding of hip joint anatomy and biomechanics, surgical procedures, expected normal postoperative imaging appearances, and postoperative complications ensures accurate imaging interpretation, intervention, and optimal patient care. This article presents surgical principles and procedural details pertinent to postoperative imaging evaluation strategies after common hip surgeries, such as radiography, ultrasonography, computed tomography, and magnetic resonance imaging. We review and illustrate the expected postoperative imaging appearances and complications following chondrolabral repair, acetabuloplasty, osteochondroplasty, periacetabular osteotomy, realigning and derotational femoral osteotomies, and hip arthroplasty.
Optimal Cycle-Slip Detection Algorithm for GPS/GNSS Preprocessing Using Three Linear Combinations of Moderate-to-Low-Noise Data
Authors: : Clement Ogaja, Ph.D. : Clement
Published: January 2025

Cycle slips are discontinuity events in a receiver’s phase lock on a Global Navigation Satellite System (GNSS) signal. If cycle-slip events are not detected and repaired, the quality of positioning using carrier phase processing suffers. In this paper, we present an algorithm for flagging cycle slips during data preprocessing. This new algorithm is part of a new GNSS software that replaces a legacy software at the National Geodetic Survey (NGS). It uses the Hatch–Melbourne–Wübbena (HMW), ionosphere-free and geometry-free linear combinations to detect cycle slips. The use of the three observables in parallel helps improve sensitivity to cycle slips and overcome the challenge of detecting cycle slips of equal size and same sign on both/multiple frequencies. Different detection threshold values were evaluated in a well-controlled environment using GNSS data acquired from continuously operating reference stations (CORS) networks and artificially simulated cycle slips that were introduced into the datasets. The goal of evaluation was to determine the optimal values for cycle-slip detection parameters. In the absence of formal confidence limits, the results of the study show that, in a worst-case scenario involving small slips of magnitudes ranging from 1 to 3 cycles, there is a range of parameter values that resulted in at least 97% success rate without any false detections. Based on these and other findings, we provide a set of optimal values from which the results are an improvement of at least 34% in cycle-slip detection, compared to results from the legacy algorithm’s settings. The results of the study will support the National Oceanic and Atmospheric Administration’s (NOAA) GNSS services and tools for the public, such as the Online Positioning User Service (OPUS).
Magnetoresistance of point contacts with spatially nonuniform distribution of defects
Authors: Moskalets M. V. , Ass E. I. , Gribov N. N. , Koshkin I. V.
Published: January 2025

The dependence of the resistance of Cu–Bi heterojunctions on the magnitude of the magnetic field H oriented along the contact axis is investigated. It is shown that there are three characteristic intervals H < H1, H1 < H < H2 and H > H2 in which the R(H) dependence is linear, quadratic and again linear, respectively. In the framework of the proposed model, the presence of the first (H < H1) linear segment which cannot be described in the theory of magnetoresistance of homogeneous junctions is associated with the spatial localization of the contaminated region near the point contact. The theoretical analysis of the results of measurements makes it possible to determine the electron mean free path in a junction, its size and the contamination region. The barrier transmittance D at the Cu-Bi heterojunction region is determined.
57Fe NMR observation of the short-range order effects in erbium orthoferrite in the erbium subsystem ordering region
Authors: Vitebskii I. M. , Kovtun N. M. , Troitskii G. A. , Khmara V. M.
Published: January 2025

Peculiarities of 57Fe NMR spectra in ErFeO3 are investigated in the vicinity of Tc = TN2 (H) (for H∥ c-axis of the crystal) of the low-temperature spin-reorientation transition due to the erbium subsystem ordering. An analysis of the spectra shows that for T > Tc, a long-living short-range order with a symmetry of the low-temperature phase Γ1 which is nominally realized at T < Tc, is established in the erbium subsystem of ErFeO3.
Absorption of the plane wave energy by a spin chain
Authors: Zvyagin A. A.
Published: January 2025

The energy of a plane wave, absorbed by a spin chain (s = 1/2) in the case of longitudinal pumping is calculated. The dependence of resonance frequencies on the parameters of the spin system is determined.
Global existence and blowup of stochastic parabolic equations
Authors: Li Wei , Lv Guangying
Published: January 2025

This paper is concerned with the blowup phenomenon of stochastic parabolic equations both on bounded domain and in the whole space. We introduce a new method to study the blowup phenomenon on bounded domain. Compared with the existing results, we delete the assumption that the solutions to stochastic heat equations are nonnegative. Then the blowup phenomenon in the whole space is obtained by using the properties of heat kernel. We obtain that the solutions will blow up in finite time for nontrivial initial data.
An electro-optically tunable arrayed waveguide grating fabricated on thin film lithium niobate
Authors: Wang Zhe , Fang Zhiwei , Zhu Yiran , Liu Jian , Gao Lang , Yu Jianping , Zhang Haisu , Wang Min , Cheng Ya
Published: January 2025

We design and fabricate an eight-channel thin-film lithium niobate (TFLN) arrayed-waveguide grating (AWG) and demonstrate the electro-optical tunability of the device. The monolithically integrated microelectrodes are designed for waveguide phase modulation and wavelength tuning. Experiments show that the fabricated electro-optically controlled TFLN AWG has a channel spacing of 200 GHz and a wavelength tuning efficiency of 10 pm/V.
Realization and simulation of silicon-on-sapphire mid-infrared one-dimensional photonic crystal cavities
Authors: Si Yalan , Ju Zezhao , Ma Hui , Xia Kai , Lin Shuo , Tang Renjie , Sun Boshu , Sun Chunlei , Li Lan , Yang Peilong , Lin Hongtao
Published: January 2025

The mid-infrared (MIR) waveband is significant for chemical and biological sensing since it covers several atmospheric windows and molecular fingerprint regions. On-chip photonic integrated one-dimensional (1D) microcavities have great potential for high-performance mid-IR sensing because of their high sensitivity and compact structure. However, high-performance 1D microcavities based on the promising silicon-on-sapphire (SoS) MIR platform have not yet been designed or realized. Based on the photonic band structure induced by 1D photonic crystals (PhC), a high-performance Bragg reflector, an inward apodized Bragg grating, and a free spectral range (FSR)-free PhC microcavity integrated system operating in the MIR waveband were developed on the SoS platform. By carefully designing the period and penetration depth of the corrugation in the Bragg reflector, a stopband of 45 nm and an extinction ratio of −12 dB were achieved. The inward apodized Bragg grating was optimized by adjusting the apodization depth and the number of periods, resulting in a quality factor of 1043 at a wavelength of 3088.4 nm. Furthermore, introducing a Fabry–Pérot (F-P) cavity between two Bragg reflectors (with side-coupled light) and precisely tuning the stopband of the Bragg reflector and the FSR of the F-P cavity enabled the realization of an FSR-free PhC microcavity. This microcavity exhibited a single deep resonance dip with subnanometer bandwidth across a record-wide operational waveband from 3025 to 3200 nm, achieving a quality factor of approximately 5090. The MIR 1D PhC microcavities on the SoS platform hold great promise for high-performance gas detection and molecular sensing in future applications.
Exploring clomiphene inclusion in β-cyclodextrin: a computational approach
Authors: Dos Santos Hélio F. , Ávila Eloah P. , Anconi Cleber P. A.
Published: January 2025

Clomiphene (CL) is a widely used antiestrogenic drug for inducing ovulation. The drug is marketed as a mixture of two geometric isomers, E-CL (62%) and Z-CL (38%), with opposing actions and low water solubility. Chemical separation and enhanced solubility can be achieved through cyclodextrin (CD) association. Recent 1H NMR titration experiments have reported the thermodynamic association constant for CL@β-CD as Kaexpt=50.21×M−1. In this contribution, we conducted a detailed exploration of the association processes underlying this value, resulting in a calculated association constant of Kacalc=46.94×M−1 based on the multi-equilibrium assumption for a fixed composition. This value was obtained through 720 quantum computational (QC) calculations on configurations selected from molecular dynamics (MD) simulations, which indicated that the Z-CL@β-CD species predominates in solution. To align our results with the experimental data, we considered a fixed composition of the isomers (62% E-CL and 38% Z-CL) when calculating the association constant. Additionally, 1H NMR measurements were conducted for neutral clomiphene and compared to the calculated data for the free guests. For the guest–host inclusion complexes, the 1H NMR chemical shifts were predicted and discussed in relation to the available experimental data. Our findings provide a solid foundation for understanding the inclusion process and introduce the QC/MD multi-equilibrium integrated approach as a valuable theoretical strategy for studying cyclodextrin inclusion compounds.
When excuse me means excuse you!
Authors: Küttner Uwe-A.
Published: January 2025

This article examines the use of excuse me as a practice for invoking the complainability of
another person’s conduct in the service of sanctioning it as misconduct. It explores how a form that semantically
expresses its speaker’s desire to be excused (excuse me
) can be used to
flag another person’s doings as transgressive or untoward. It is proposed that, to elucidate this puzzle, it is
necessary to adopt a more holistic perspective and to incorporate other uses of the format (e.g., in other-initiated repair, as an
attention-drawing device), as well as possible relationships between them, into the analysis. The paper offers a sketch of such a
more holistic, integrative account. This account revolves around the idea that practices of speaking that mobilize similar or even
the same linguistic resources implicate partially overlapping sets of affordances for action which link different usages together
in a larger pragmatic landscape. As such, form-based practices of speaking and the various actions they can implement exhibit
demonstrable relationships across different domains of use which may need to be taken into account when thinking about a
practice’s fit to the action it implements. One of the key benefits of such an approach is that it allows for mapping out larger
pragmatic landscapes and to move beyond the isolated description of individual practices of speaking.
Self-supervised learning for machinery fault diagnosis under strong background noise and limited epochs
Authors: Chen Mingsong , Wang Hongwei , Zhang Fanghong
Published: January 2025

Self-supervised learning (SSL) has been widely used for fault diagnosis of rotating machinery. However, real industrial environments often generate a large amount of noise, and existing SSL-based fault diagnosis methods are, firstly, difficult to apply to fault diagnosis under highly noisy working conditions due to the inherent scarcity of labeled samples. Secondly, most of the existing methods add projection head during pre-training and classification head during fine-tuning, such a design makes the number of parameters and computations of the model excessive, which requires a lot of time for training and cannot meet the needs of low-end edge device deployment. To solve the above problems, this paper proposes a multi-scale channel-mixed depthwise separable convolutional neural network-based fault diagnosis method under SSL. Experimental results on bearing datasets show that the proposed method has a significant advantage over other methods in terms of strong noise fault diagnosis accuracy under limited labeled samples, and also the number of parameters and computational cost of the model are minimized. Specifically, with only 10 pre-training epochs and 50 fine-tuning epochs under 5% labeled data, the proposed method can achieve up to 96.35% average accuracy on the PU dataset with strong noise interference.
Investigation of ion temperature in low-density undercritical foams
Authors: Hudec L , Limpouch J , Renner O , Tikhonchuk V , Dudžák R , Liska R , Blackman D R , Condamine F , Červeňák M , Dostál J , Gintrand A , Klimo O , Krupka M , Krůs M , Singh S , Weber S
Published: January 2025

The ion temperature in laser-heated foam materials can be considerably higher than the electron temperature due to the internal collisions of the plasma flows originating from the heterogeneous foam microstructure. Recently, we have developed a novel hybrid multiscale model for laser-foam interaction that successfully reproduces the experimentally measured heat front propagation in laser-heated subcritical foams of various densities. However, when applied to undercritical foams with average density closer to critical, the hybrid model simulations predict an ion–electron temperature ratio much larger than in any previously reported measurements and suggest that the influence of foam microstructure is more impactful for larger average densities. For such foams, the laser-driven heat front velocity was measured many times, but the ion temperature received much less attention. To investigate the ion temperature, the laser interaction with 10 mg 

cm

−
3

undercritical chlorine-doped TMPTA foams has been studied at the PALS facility, using an extended diagnostic complex emphasizing the x-ray time-resolved studies of the plasma wave propagation inside the foam and the distribution of macroscopic plasma parameters via high-resolution x-ray spectroscopy. The ion and electron temperatures have been measured from Doppler broadening and the relative intensity ratio of chlorine x-ray spectral lines. The averaged ion and electron temperature ratio ranges from 2 to 4 depending on the laser pulse energy. The simulations agree reasonably well with the experimental results.
Simulation of ion cyclotron range of frequencies heating in the proton–boron plasma of the spherical tokamak
Authors: Ma Hao-jie , Xie Hua-sheng , Sun Guang-lan , Zhao Han-yue , Gan Yan-biao
Published: January 2025

Ion cyclotron range of frequencies (ICRF) heating is crucial in magnetic confinement fusion devices that utilize proton–boron11 (p11B) as an advanced fuel, as it requires higher ion temperatures for their reactions. This work investigates the ICRF heating characteristics of hydrogen (H) ions at the second harmonic frequency and 11B ions at the fundamental frequency in a p11B plasma within a spherical tokamak. It is found that H ions second harmonic is better than 11B ions fundamental for ion power absorption. We simulate the ICRF heating effects of the 11B fraction in plasma and the wave vector parallel to the magnetic field (

k

‖

) of the antenna using full-wave codes and the kinetic dispersion relation solver. In second harmonic heating of H ions, the power deposition primarily occurs on the H ions themselves, and, the total power absorption will exceed 50%, up to 58%, when X[11B] > 6%. Heating the electrons is easier in the fundamental frequency heating of 11B ions scenario.
Bayesian method in optical emission spectroscopy: temporal evolution of electron density from time-integrated Hα emission and validation with time-resolved measurements for pulsed nanosecond discharges in water
Authors: Dorval Audren , Hamdan Ahmad , Stafford Luc
Published: January 2025

The characterization of in-liquid discharges is known to be a challenging feat due to their stochastic nature and nanosecond time scale evolution. In this study, the time-resolved electron density (n
e) of a spark discharge in water is analyzed by coupling optical emission spectroscopy (OES) measurements with a Bayesian model. It is first highlighted that a single Voigt profile cannot adequately describe the time-averaged Hα line profile; this is due to the significant time evolution of the discharge properties. To overcome this limitation, a model describing the temporal evolution of the line emission intensity and shape is developed and used to fit the time-integrated spectrum. The unknown parameters in the model are determined using the Dynesty python package, according to the Bayesian nested sampling method. With such model, the simulated and measured spectrum of the Hα transition agree very well. Over the range of experimental conditions investigated, it is found that the electron density rapidly reaches

∼

2
×

10

25

m

−
3

and then decreases exponentially with a decay time of

∼

238

 ns

. These values are consistent with those determined using time-resolved measurements and analysis of the Hα and O I line broadenings. Overall, this study shows that time-resolved plasma properties can be obtained from time-integrated OES data by applying a Bayesian-based modeling approach. Further studies are needed to expand the scope of the developed model and determine plasma properties over a broad range of conditions.
A cordial introduction to double scaled SYK
Authors: Berkooz Micha , Mamroud Ohad
Published: January 2025

We review recent progress regarding the double scaled Sachdev–Ye–Kitaev model and other p-local quantum mechanical random Hamiltonians. These models exhibit an expansion using chord diagrams, which can be solved by combinatorial methods. We describe exact results in these models, including their spectrum, correlation functions, and Lyapunov exponent. In a certain limit, these techniques manifest the relation to the Schwarzian quantum mechanics, a theory of quantum gravity in AdS
2. More generally, the theory is controlled by a rigid algebraic structure of a quantum group, suggesting a theory of quantum gravity on non-commutative q-deformed AdS
2. We conclude with discussion of related universality classes, and survey some of the current research directions.
On the Response of Massive Main Sequence Stars to Mass Accretion and Outflow at High Rates
Authors: Bear Ealeal , Soker Noam
Published: January 2025

With a one-dimensional stellar evolution model, we find that massive main sequence stars can accrete mass at very high mass accretion rates without expanding much if they lose a significant fraction of this mass from their outer layers simultaneously with mass accretion. We assume the accretion process is via an accretion disk that launches powerful jets from its inner zones. These jets remove the outer high-entropy layers of the mass-accreting star. This process operates in a negative feedback cycle, as the jets remove more envelope mass when the star expands. With the one-dimensional model, we mimic the mass removal by jets by alternating mass addition and mass removal phases. For the simulated models of 30M
⊙ and 60M
⊙, the star does not expand much if we remove more than about half of the added mass in not-too-short episodes. This holds even if we deposit the energy the jets do not carry into the envelope. As the star does not expand much, its gravitational potential well stays deep, and the jets are energetic. These results are relevant to bright transient events of binary systems powered by accretion and the launching of jets, e.g., intermediate luminosity optical transients, including some luminous red novae, the grazing envelope evolution, and the 1837–1856 Great Eruption of Eta Carinae.
Mutual exclusion statistics and the infinite-range Hubbard model: critical behavior in the quantum regime
Authors: Ramos G F O , Rosendo W L S , Raposo E P , Coutinho-Filho M D
Published: January 2025

We investigate the critical behavior in the quantum regime of the Hubbard model in d-dimensional hypercubic lattices with infinite-range Coulomb interaction. The Haldane–Wu mutual exclusion statistics approach, which comprises three species of exclusions, allows us to derive the singular part of the free energy, entropy, and specific heat in the quantum regime g > T, where g is the scaling interaction parameter and T is the temperature. We present results from the analytic series expansions of observables near the quantum critical point:

T
=
g
=
μ
=
0

, where µ is the chemical potential. The signature of the mutual exclusion statistics manifests through the appearance of polylogarithms related to Lerch functions in the coefficients of the free energy series in powers of

T

/

g

. The calculated critical exponents from the analytic series are consistent with our scaling analysis in the quantum regime. In particular, the specific heat is shown to display a variety of critical behaviors,

C

/

T
∼

g

−

α
g

,

g
→

0
+

, depending on the lattice dimension: from a singular behavior in d = 1 (

α
g

=
1

/

2

) to a constant value in d = 2 (

α
g

=
0

), and regular behavior for d > 2 (

α
g

=
1
−
d

/

2
<
0

).
Lateral flow immunoassay combined with color saturation for smartphone-based quantitative point-of-care detection of Klebsiella pneumoniae
Authors: Pham Thu Thao , Huyen Nguyen T T , Tran Lam Dai , Lien Truong T N
Published: January 2025

Klebsiella pneumoniae is one of the most common pathogenic, multidrug-resistant Gram-negative bacteria that triggers postoperative infections, leading to septic shock and fatality. Therefore, there is an urgent need to generate rapid and sensitive diagnosis techniques for timely and effective intervention. The present work described the fabrication of lateral flow immunoassays (LFIA) based on antibody-gold nanoparticle covalent conjugation combined with an RGB system to detect Klebsiella pneumoniae quantitatively. The LFIAs showed the lines after 15 min with good sensitivity and a low limit of detection of 2.40 CFUs ml−1 in the linear detection range of this immunosensor from 101 to 108 CFUs ml−1 when combined with the color saturation system. No false positives and cross-reactions were observed on the test strips in this study, indicating that the system was optimized with high specificity. This finding might provide a well-suited solution for a quick, inexpensive, and easy-to-use detection method for potential commercial manufacture.
Microstructural transformation of GO to rGO by ascorbate acid green-agent enhanced using sonication method
Authors: Masruroh  , Sukma Freygieon Ogiek Rizal , Saputra Kormil , Mufti Nandang , Kusumandari  , Prasetyo Anton , Tjahjanto Rachmat T , D H Santjojo Dionysius J
Published: January 2025

Reduced graphene oxide (rGO) was successfully synthesized from graphene oxide (GO) using ascorbic acid as a reducing agent, combined with a sonication process to improve microstructural transformation and enhance optical properties. The primary objectives of this study were to evaluate the role of ascorbic acid in altering the microstructure of rGO and to examine the effect of sonication duration on the band gap. Characterization of particle size distribution and band gap was carried out using PSA and UV–vis, while changes in microstructure, crystallization, and morphology were analyzed using XRD, Raman spectroscopy, and SEM/EDX. The results showed that increasing the sonication duration decreased the particle size of rGO significantly, contributing to microstructural transformation. The decrease in the bandgap of rGO was also confirmed through UV–vis characterization. FTIR analysis showed a decrease in the absorption intensity of the O=C=O (2200–2450 cm−1), C–O (1024–1150 cm−1), and O–H (3650–3800 cm−1) peaks, indicating a decrease in oxygen groups. SEM showed a change in the morphology of the compact GO surface to a looser and folded rGO, with a decrease in the oxygen ratio detected by elemental mapping. The increase in the intensity of the D band in the Raman spectrum indicated an increase in structural defects due to the reduction of oxygen groups. Crystallite size calculations from Raman and XRD revealed that rGO had a smaller crystallite size than GO, where rGO with a sonication duration of 120 min had a smaller crystallite size than rGO with 180 min, indicating an expansion of the sp2 domain. The combination of ascorbic acid and sonication proved effective in reducing GO to rGO with significant improvements in material characteristics.
GradeDiff-IM: an ensembles model-based grade classification of breast cancer
Authors: Manna Sweta , Mistry Sujoy , Dahal Keshav
Published: January 2025

Cancer grade classification is a challenging task identified from the cell structure of healthy and abnormal tissues. The practitioners learns about the malignant cell through the grading and plans the treatment strategy accordingly. A major portion of researchers used DL models for grade classification. However, the behavior of DL models is hidden type, it is unknown which features contribute to the accuracy and how the features are chosen for grading. To address the issue the study proposes a Grade Differentiation Integrated Model (GradeDiff-IM) to classify the grades G1, G2, and G3. In GradeDiff-IM, different ML models, are used for grade classification from clinical and pathological reports. The biological-significant features with ranking technique prioritize influential features are used to identify grades G. Subsequently, histopathological images are used by DL models for grade classification and compared with ML models. Instead of employing a single ML model, the GradeDiff-IM model uses the stack-ensembled approach to improve the grade G classification performance. The maximum accuracy is attained by stacking G1-98.2, G2-97.6, and G3-97.5. The proposed study shows that the ML ensemble model is more accurate than the DL models. As a result, the proposed model achieved higher accuracy for G by implementing the stacking technique than the other state-of-the-art models.
Multimodal multiview bilinear graph convolutional network for mild cognitive impairment diagnosis
Authors: Wu Guanghui , Li Xiang , Xu Yunfeng , Wei Benzheng
Published: January 2025

Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease (AD) and can serve as an important indicator of disease progression. However, many existing methods focus mainly on the image when processing brain imaging data, ignoring other non-imaging data (e.g., genetic, clinical information, etc.) that may have underlying disease information. In addition, imaging data acquired from different devices may exhibit varying degrees of heterogeneity, potentially resulting in numerous noisy connections during network construction. To address these challenges, this study proposes a Multimodal Multiview Bilinear Graph Convolution (MMBGCN) framework for disease risk prediction. Firstly, grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) features are extracted from magnetic resonance imaging (MRI), and non-imaging information is combined with the features extracted from MRI to construct a multimodal shared adjacency matrix. The shared adjacency matrix is then used to construct the multiview network so that the effect of potential disease information in the non-imaging information on the model can be considered. Finally, the MRI features extracted by the multiview network are weighted to reduce noise, and then the spatial pattern is restored by bilinear convolution. The features of the recovered spatial patterns are then combined with the genetic information for disease prediction. The proposed method is tested on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Extensive experiments demonstrate the superior performance of the proposed framework and its ability to outperform other related algorithms. The average classification accuracy in the binary classification task in this study is 89.6%. The experimental results demonstrate that the method proposed in this study facilitates research on MCI diagnosis using multimodal data.
Fully integrated wearable control system for micro/nanorobot navigation
Authors: Zhang Zhanxiang , Wang Lin , Jiang Fengqi , Yu Shimin , Ji Fengtong , Sun Tianhao , Zhang He , Zhu Yanhe , Chang Hao , Li Tianlong , Zhao Jie
Published: January 2025

Micro/nanorobots have exhibited excellent application potential in the biomedical field, such as drug delivery, minimally invasive surgery, and bio-sensing. Furthermore, in order to achieve practical application, it is essential for swimming micro/nanorobots to navigate towards specific targets or adjust their speed and morphology in complete environments. The navigation of swimming micro/nanorobots with temporal and spatial precision is critical for fulfilling the demand of applications. Here, we introduced a fully integrated wearable control system for micro/nanorobots navigation and manipulation, which is composed of a multifunctional sensor array, an artificial intelligence (AI) planner, and a magnetic field generator. The sensor array could perceive real-time changes in gestures, wrist rotation, and acoustic signals. AI planner based on machine learning offers adaptive path planning in response to dynamically changing signals to generate magnetic fields for the on-demand manipulation of micro/nanorobots. Such a novel, feasible control strategy was validated in the biological experiment in which cancer cells were targeted and killed by photothermal therapy using micro/nanorobots and integrated control platform. This wearable control system could play a crucial role in future intelligent medical applications and could be easily reconfigured toward other medical robots’ control.
South Atlantic subtropical anticyclone responses to stratospheric aerosol injection
Authors: Chile Baldoni Thales , Reboita Michelle Simões , Machado Crespo Natália , Ribeiro João Gabriel Martins , da Rocha Rosmeri Porfírio
Published: January 2025

The South Atlantic Subtropical Anticyclone (SASA) is a key component of large-scale atmospheric circulation and is responsible for driving the climate in eastern Brazil and western Africa. Climate projections under warming scenarios suggest a strengthening, as well as a westward and southward expansion of this system. However, little is known about how the combination of global warming and climate intervention affects this system. To address this, SASA was identified from 2015 to 2099 in a set of projections with and without stratospheric aerosol injection (SAI). Projections were obtained from different initiatives: the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System with SAI using Community Earth System Model version 2 (CESM2) global climate model, the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) using CESM1, and the Geoengineering Model Intercomparison Project (GeoMIP/G6sulfur) using Max Planck Institute Earth System Model. As each project has its own specific model, scenario, SAI location, etc, no intercomparison was carried out among them. Instead, there is an indication of what occurs in each project when comparing the near (2040–2059) and the far future (2080–2099) projections under SAI and no-SAI scenarios. SASA under no-SAI scenarios, compared to the reference period (2015–2024), follows the pattern described in the literature, i.e. a tendency to be stronger and wider. However, these features are more evident in the GLENS project. This same project suggests that SAI scenarios contribute to reducing the impact of global warming on the SASA climatology, as SASA in the future acquires characteristics similar to those of the reference period. One of the possibilities for it is that GLENS has the largest SAI forcing, given that the goal was to cancel out the strong greenhouse gas-induced warming in Representative Concentration Pathway 8.5.
Attributing heatwave-related mortality to climate change: a case study of the 2009 Victorian heatwave in Australia
Authors: Perkins-Kirkpatrick Sarah E , Selvey Linda , Aglas-Leitner Philipp , Lansbury Nina , Hundessa Samuel , Stone Dáithí , Ebi Kristie L , Osborne Nicholas John
Published: January 2025

Determining the influence of climate change behind human mortality is of interest to many sectors. However, it is a fledgling field where studies have centered on northern hemisphere events. This study presents the first attribution assessment on the mortality burden of an Australian heatwave to climate change. We focus on excess heatwave- (defined by climatological definitions) related mortality in the state of Victoria that occurred during the 2009 southeast Australian heatwave. An epidemiological model derived from well-established methods defining the relationship between observed heatwave temperatures (95th, 97.5th and 99th percentiles) and mortality is applied to heatwaves in simulations that either include or omit anthropogenic climate forcing from eight climate models. Across all models, the frequency of a heatwave-related mortality event similar to the 2009 Victorian event has, on average, doubled under factual conditions relative to counterfactual conditions. Moreover, on average, around 6 ± 3–4 extra individuals out of 31 (an increase of 20%) died as a direct result of extreme temperatures due to anthropogenic influence on the climate. Despite the small total number of attributable deaths as per the epidemiological model, six out of eight climate models predicted a statistically significant anthropogenic influence, indicating that climate change increased the heatwave-related mortality impact of this event. We make clear that, in line with previous Australian-based studies, the focus on mortality relative to the top 5% of temperatures logically infers a smaller mortality signal relative to the top 50% of temperatures, as would be defined by a more general temperature-related epidemiological model. As research, planning and policy interest in the role of climate change behind the burden health—and other adverse impacts of weather and climate extremes—continues to grow, it is vital that interdisciplinary collaborations are nurtured, so that the resulting science is of high-quality rigour, and policy relevance.
Causally inferred evidence of the impact of green and blue spaces (GBS) on maternal and neonatal health: a systematic review and meta-analysis
Authors: Khalaf Rukun K S , Akaraci Selin , Baldwin Faye D , Geary Rebecca S , Kolamunnage-Dona Ruwanthi , Hunter Ruth F , Rodgers Sarah E
Published: January 2025

The benefits of green and blue space (GBS) exposure on improving public health are accepted by a range of stakeholders, including policy makers. Extensive GBS research into health supports the theory that GBS promotes physical activity and has mental restorative and environmental mitigative properties. Studies exploring the impact of GBS exposure on maternal, prenatal, and/or neonatal health have mainly utilised cross-sectional methods. This does not allow for causal inference. Thus, our systematic review aimed to analyse the evidence of the impact of GBS on maternal, prenatal, and/or neonatal health. Our study adhered to PRISMA guidelines. We searched seven online databases (Medline, Scopus, Web of Science, PsycInfo, Embase, Environment Complete, and Maternity & Infant Care Database) and excluded cross-sectional studies without mediation analysis. Our risk of bias assessment framework was adapted from the ROBINS-E tool. We conducted narrative syntheses of studies examining maternal, prenatal, and/or neonatal outcomes. We carried out meta-analyses using random effects models for five birth outcomes (i.e. birthweight, low birthweight (LBW), gestational age, pre-term birth (PTB), and small-for-gestational-age (SGA)). Studies found to be high risk of bias, or very high risk of bias were excluded from our analyses. Initial searches yielded 1099 articles. Following full text screening, our review included 62 studies. Most studies were conducted in either Europe or North America (n = 41, 66%). All studies reported green space exposure as an independent variable while seven studies also included blue space exposure as an independent variable. The most reported green space variable was the Normalized Difference Vegetation Index (NDVI) (n = 46, 74%). Our meta-analyses results indicated that greater greenness is protective against LBW (OR = 0.95, 95% CI: 0.92–0.98, p = 0.002), SGA (OR = 0.95, 95% CI: 0.92–0.99, p = 0.01), PTB (OR = 0.92, 95% CI: 0.88–0.97, p = 0.001), and affects birthweight (β = 13.02 g, 95% CI: 9.99–16.05, p < 0.0001).
A presentation of relative unitary Steinberg groups
Authors: Voronetsky E.
Published: January 2025

An explicit presentation is found for relative odd unitary Steinberg groups constructed by odd form rings and for relative Steinberg groups associated with the Chevalley group schemes of types

B

ℓ

\mathsf {B}_\ell

,

C

ℓ

\mathsf {C}_\ell

,

F

4

\mathsf {F}_4

for

ℓ
≥
3

\ell \geq 3

. For simply laced root systems, a similar result was obtained earlier.
Electromagnetics of Superconductor/Paramagnet Heterostructures
Authors: Genenko Yuri , Rauh Hermann
Published: January 2025

Redistribution of the transport current in a superconductor affected by paramagnetic shields provides a possibility of strongly overcritical states and a drastic reduction of AC losses in thin superconductor films and tubes. Such superconductors subject to para- or diamagnetic shielding are studied by means of the potential theory and the critical state model when carrying a transport current or exposed to an external magnetic field. Analytical results are obtained for a number of shielding geometries and confirmed by numerical solutions. It is shown that using magnetostatic-electrostatic analogies allows consideration of paramagnetic shielding configurations of arbitrary shapes and magnetic permeabilities by means of common finite-element solvers to enhance the dissipation-free transport currents in superconductors and reduce AC losses in them. Furthermore, using the generalized London theory, the penetration of magnetic flux into magnetically shielded bulk superconductors is studied and the enhancement of the Bean-Livingston barrier is established.
UN Peacekeeping, Democracy, and Authoritarianism
Authors: von Billerbeck Sarah , Gippert Birte Julia , Oksamytna Kseniya , Tansey Oisín
Published: January 2025

In Chapter 2, we present our theoretical argument in depth. We begin by providing a detailed examination of the United Nations (UN)’s complex and evolving relationship with democracy and authoritarianism, in particular in relation to its conflict management and peacekeeping activities. We engage with scholarship on the impact of UN peacekeeping on domestic-level politics, and we show how it has focused on the effects of peacekeeping on democracy, largely treating authoritarianism as a residual category and simply as the opposite of democracy, rather than a political system in its own right. Having identified this gap in the literature, we then introduce the concept of enabling and outline the two mechanisms through which enabling works: capacity-building and signaling. We then explore the sources of enabling, identifying the trade-offs and contradictions in peacekeeping that give rise to these two mechanisms.
Acquiesce for Success: UNTAC in Cambodia
Authors: von Billerbeck Sarah , Gippert Birte Julia , Oksamytna Kseniya , Tansey Oisín
Published: January 2025

Chapter 3 examines the UN Transitional Administration in Cambodia (UNTAC). UNTAC was one of the first large post-Cold War multidimensional peacekeeping missions and included a significant commitment to democratic development through the organization of free and fair elections. The mission faced considerable challenges, not least from the de facto ruling authorities (led by long-time Cambodian leader Hun Sen) who sought to frustrate the democratic process and engage in a variety of authoritarian behaviors to maintain their dominant power structures. The mission struggled to respond forcefully, and when faced with competing pressures often prioritized stability and good working relations with the host authorities over criticism and confrontation. While the mission played a central role in organizing the elections, its approach to the pre- and post-election periods clearly signaled a permissive environment for authoritarian behavior.
Ranked Choice Voting and Election Reform
Authors: Endersby James W , Towle Michael J
Published: January 2025

A brief discussion of single-member districts with plurality elections introduces ranked choice voting (RCV) through objections to plurality elections. Hypothetical and empirical political examples of RCV are presented, along with applications for other, nonpolitical decision-making situations such as Academy Award nominations. Seven goals, presented by proponents of RCV, are majoritarianism, an efficient runoff without change in the electorate’s composition, increased voter turnout and decreased propensity of wasted votes, incentives for voters to offer their sincere preferences, the representation of marginalized interests, improved civility of campaigns and corresponding democratic satisfaction, and (for single transferable vote only) proportional representation. Six challenges frequently raised in opposition are the intense information demands on voters, mathematical problems with tabulation of election tabulation, the potential to select a less satisfactory consensus candidate, the potential differences between runoff election and RCV outcomes, the priorities placed on preferences of extremist voters, and the lack of transparency of elections.
Provided and received positive and negative social control, relationship satisfaction, and sedentary behavior in parent-child dyads
Authors: Siwa Maria , Banik Anna , Szczuka Zofia , Kulis Ewa , Boberska Monika , Wietrzykowska Dominika , Knoll Nina , DeLongis Anita , Knäuper Bärbel , Luszczynska Aleksandra
Published: January 2025

Background

The close relationship processes and health model and the dyadic health influence model posit that relationship beliefs (eg, relationship satisfaction) and influence strategies (eg, provision and receipt of positive and negative social control) mediate health behavior change. However, evidence for such mediation in parent-child dyads is limited.

Purpose

Two complementary mediation hypotheses were tested: (1) social control forms indirect relationships with sedentary behavior (SB), via relationship satisfaction acting as a mediator; and (2) relationship satisfaction forms indirect relationships with SB, with social control operating as a mediator.

Methods

Data from 247 parent-child dyads (9- to 15-year-old children) were analyzed using manifest mediation models. SB was measured with GT3X-BT accelerometers at Time 1 (T1; baseline) and Time 3 (T3; 8-month follow-up). Relationship satisfaction and social control were assessed at T1 and Time 2 (T2; 2-month follow-up). Path analysis models, controlling for baseline SB, were fit.

Results

Received positive control (children, T1) was associated with higher relationship satisfaction in both children and parents (T2), which in turn were related to lower and higher parental SB at T3, respectively. Provided positive control (parents; T1) was related to higher SB (T3) in children. Relationship satisfaction among children (T1) predicted higher levels of received positive and negative control (children, T2).

Conclusions

Provided and received positive social control may form direct and indirect associations with SB in parent-child dyads. Future research may need to consider further subtypes of positive control, which may explain the divergent effects of this form of control on SB.
Physical Intimate Partner Violence Among Women Experiencing Homelessness Before and During Pregnancy
Authors: Sakai-Bizmark Rie , Gemmill Allison , Kumamaru Hiraku , Marr Emily H , Estevez Dennys , Wu Frank , Henwood Benjamin F
Published: January 2025

Intimate partner violence (IPV) and homelessness can have devastating health consequences for pregnant women. Using the Pregnancy Risk Assessment Monitoring System, we assessed differences in the association of physical IPV before and/or during pregnancy with adverse health outcomes between women experiencing homelessness (WEH) and domiciled women. Among 186,891 respondents, representing an estimated 11,489,161 women, 27.1% and 3.4% of WEH and domiciled women, respectively, reported experiencing physical IPV. Physical IPV was associated with higher odds of having postpartum depression and preterm birth and lower odds of having a postpartum checkup among domiciled women (adjusted odds ratio [aOR] 1.83, 95% confidence interval [CI] 1.62 – 2.08 for postpartum depression, aOR 1.29, 95%CI 1.08 – 1.53 for preterm birth, and aOR 0.56, 95%CI 0.49 -0.64 for postpartum checkup). The differences in these outcomes between women who experienced physical IPV and those who did not were smaller among WEH, as indicated by aORs of interaction terms (aOR 0.74, 95%CI 0.58 – 0.94 for postpartum depression, aOR 0.68, 95%CI 0.49 – 0.93 for preterm birth, and aOR 1.32, 95%CI 1.01 – 1.74 for postpartum checkup). Further research is needed to identify factors that may offer WEH a protective effect against the negative impacts of IPV.
scGO: interpretable deep neural network for cell status annotation and disease diagnosis
Authors: Wu You , Xu Pengfei , Wang Liyuan , Liu Shuai , Hou Yingnan , Lu Hui , Hu Peng , Li Xiaofei , Yu Xiang
Published: January 2025

Machine learning has emerged as a transformative tool for elucidating cellular heterogeneity in single-cell RNA sequencing. However, a significant challenge lies in the “black box” nature of deep learning models, which obscures the decision-making process and limits interpretability in cell status annotation. In this study, we introduced scGO, a Gene Ontology (GO)–inspired deep learning framework designed to provide interpretable cell status annotation for scRNA-seq data. scGO employs sparse neural networks to leverage the intrinsic biological relationships among genes, transcription factors, and GO terms, significantly augmenting interpretability and reducing computational cost. scGO outperforms state-of-the-art methods in the precise characterization of cell subtypes across diverse datasets. Our extensive experimentation across a spectrum of scRNA-seq datasets underscored the remarkable efficacy of scGO in disease diagnosis, prediction of developmental stages, and evaluation of disease severity and cellular senescence status. Furthermore, we incorporated in silico individual gene manipulations into the scGO model, introducing an additional layer for discovering therapeutic targets. Our results provide an interpretable model for accurately annotating cell status, capturing latent biological knowledge, and informing clinical practice.